Impact of Managerial Influence Tactics on Job Creativity and Performance: A Focus on Korean Airline Service Employees

Abstract

Little is known about the effectiveness of managerial influence tactics on job creativity and performance in the airline industry. Based on previous research, eleven hypotheses and a theoretical model was conducted under the assumption that individual influence tactics affect job creativity, job creativity has a positive influence on job performance, and job creativity mediates both influence tactics and job performance. This study implemented a quantitative method using multiple regression analysis, a three-step multiple regression analysis, and a Sobel test. According to an empirical method, among nine total influence tactics, inspirational appeals, ingratiation, exchange, and pressure acted as crucial drivers of job creativity, which had the greatest influence on job performance. Job creativity also had a mediating effect. On the other hand, the tactic of legitimating also positively influenced job creativity unlike previous studies. These findings may help managers by providing some insights for promoting job creativity and performance.

1. Introduction

A key determinant of managerial efficiency is the ability to influence employees to increase their commitment to job goals [1]. Research on these influencing tactics is very important not only in the academic field, but also in practical terms. A leader must behave in a way designed to achieve goals regardless of the form and size of their organization [2]. An influence tactic is “a type of behavior that is intentionally used to influence the attitudes and behaviors of others” [3]. Studies on influence tactics are both academic and practical. This is because leadership behavior must actually influence others to achieve goals regardless of the form or scale of the organization [2]. Previous research has focused on evaluating upward influence tactics that members use when communicating with supervisors [4]. However, the downward influence of a leader or superordinate within an organization is more practically significant because such behavior affects both individual members and the overall organization itself [2]. In this scenario, leadership is conceptualized in terms of how bosses influence their employees [5,6,7]. It is, thus, important to study influence tactics from a downward perspective.

Organizational leadership influences the behaviors, thinking styles, and creativity of company members [8]. In this context, creativity refers to how a group of individuals cooperates to produce new and useful ideas [9,10,11,12]. It has recently become possible to manipulate and measure creativity by treating it as a variable [13]. In addition, employees can actively stimulate their creative performance by soliciting feedback on their work frequently and from a wide variety of sources [14]. Moreover, leadership may not always have positive effects on creativity. It has both positive and negative effects [15]. To manifest organizational creativity, managers must support and inspire creativity. They must determine how to effectively promote employee creativity by impacting the context in which creativity arises [16].

Mun Tae Won et al. (2017) [17] found that employee creativity positively affected job performance. It can, thus, be inferred that employee creativity can positively affect job performance within the organization. Meanwhile, World Tourism Indicators (2018) [18] revealed that there were 1.4 billion tourists worldwide in 2018. Since many inbound and outbound tourists travel on aircraft, the aviation industry can be seen as an area that is closely related to tourism. Therefore, seeking a solution to improve job performance of airline crews can significantly contribute to the tourism sector.

In this regard, it is necessary to determine how to improve performance among airline employees who are most directly involved with tourists. In turn, this will improve the overall tourism industry. In terms of management efficiency, there are both theoretical and practical implications to confirm the impact of managerial influence on employee creativity and how this relates to job performance. However, there has been limited research on the relationships between influence tactics, creativity, and job performance in the airline industry. This study, thus, examined nine managerial influence tactics to determine how they affected employee creativity in this context. We also aimed to understand the correlation between employee job creativity and performance, which is also affected by influence tactics. The results offer some implications on the type of management needed to improve employee performance in this area.

2. Literature Review

2.1. Influence Tactics

Influence can be defined as an actual change in the attitudes, values, beliefs, or behaviors of a subject [19]. It can, thus, be measured by determining how these factors change as a result of the leader’s influence tactics. Influence can be divided into upward, lateral, and downward types based on the position of the influencer [2]. First, upward influence refers to how someone in a lower position or class influences someone (the target) in a higher position or class. Existing research on top-level influence has mainly focused on organizational political behaviors [20]. Second, Schein (1986) [21] explained that lateral influence was the process by which group dynamics and socialization result in an agent and target relationship involving peers. Agents influence their peers to behave according to group norms and expectations. Third, downward influence refers to how a superordinate influences their subordinates based on their hierarchical status within the organization. In other words, a downward influence can be regarded as a leadership behavior [2].

Influence tactics are central to the Interpersonal Influence Theory [22,23,24,25] and are particularly helpful for understanding organizational membership behavior. In this case, leadership is conceptualized in terms of how the superordinate influences company members [5,6,7], while influence tactics are defined as leadership behaviors that gain policy support and, thus, enable members to appropriately implement policies and decisions [4]. Kipnis et al. (1980) [26] first comprehensively identified influence tactics. The same study also developed a self-reporting questionnaire called the Profiles of Organizational Influence Strategies (POIS). Schriesheim and Hinkin (1990) [27] confirmed the effects of six influential tactics (i.e., Rationality, Exchange, Ingratiation, Assertiveness, Coalition, and Upper Appeal) through a factor analysis. Their findings have been empirically supported by later studies [28]. However, the POIS only focus on the upward direction of influence. It is, therefore, not useful for determining downward or lateral influence tactics. The Influence Behavior Questionnaire (IBQ) was developed to provide managers with feedback from a variety of sources [29,30]. The early IBQ included scales for measuring six tactics that were similar to those in the POIS, but were later revised to measure nine tactics based on leadership and power literature [31]. Robbins and Judge (2008) [32] summarized these and identified a total of nine tactics based on Yukl’s (2006) study [33]. They revealed a total of nine individual influence tactics, including Rational Persuasion, Inspirational Appeals, Consultation, Ingratiation, Personal Appeals, Exchange, Coalition, Legitimating, and Pressure.

First, Rational Persuasion is a logical way to influence sufficient argumentation and facts to assert that a request or proposal can be successfully implemented and that it is related to achieving a task or goal [33]. Influence can be successfully accomplished through rational persuasion if performed on a subject that trusts the assertion based on the presence of common goals [4].

Second, Inspirational Appeals are an effective way of influencing emotional aspects based on the target’s emotions or values. This is opposed to rational persuasion, which is based on empirical evidence and logical assertion to secure influence on the subject [33]. For this tactic to be effective, the subject must be able to accurately grasp the values or ideals of the subject and must be capable of appealing vividly and emotionally so that proposals or requests can be successfully implemented [34]. Consultation is invited to present practical improvements to the preliminary plan or proposal from the subject as a means of influencing the direct involvement of those who are in need of support, provide support for the influencer [33], or by discussing the thoughts and concerns of the subject. This is an influencial tactic that actively engages the process of change. Next, Ingratiation is an influencing tactic involving actions that make the subject feel more comfortable with the issue [33]. Scholars have suggested that it may be more useful to use ingratiation tactics when attempting to develop a long-term relationship with the subject [35]. Personal Appeals is a method of influencing the execution of a request or proposal based on friendship or loyalty. This may also come in the form of a personal favor rather than a formal request or form of knowledge [33]. Thus, Personal Appeals may be an influential tactic that cannot be effectively implemented if the subject is indifferent to or has a poor relationship with the influencer.

The exchange tactic implies that the influencer exerts influence through a proposal in which the subject will reveal what they want in return for fulfilling the influencer’s request [33]. Next, the coalition is a way to influence others by seeking their help or by persuading them to do something cooperatively [33]. This tactic is usually used in conjunction with other influencing methods [36]. Legitimating is a means of influencing the attempt to establish an individual’s legal right or right to make a particular request or offer [33]. Securing the legitimacy of a request is a necessary means for influencing the result in both object compliance and commitment [34]. Pressure is an influencing tactic that is accompanied by self-assertive behaviors, including threats, warnings, frequent confirmations, and persistent reminders in order to force the influenced party to fulfill the request [33].

Kipnis et al. (1980) developed a meta-classification of individual influence tactics that is divided into three different categories [26], including hard, soft, and rational tactics [37]. Hard influence tactics can be used to influence a subject through threats and control. The influence is based on the way a subject behaves [38]. As a result, hard influence tactics are usually driven by the compensatory, compulsive, and legitimate power of the subject [39]. On the other hand, soft influence tactics are used to influence the psychological aspects of a subject through socioemotional means. In this case, the subject may be convinced to voluntarily comply with the influencer’s suggestion or request [40]. Lastly, Rational influence tactics are used to influence the cognitive and rational judgments of the subject by presenting logical arguments and empirical evidence [41]. Falbe and Yukl (1992) [41] examined the effectiveness of nine individual influence tactics and compared them with these meta-classifications. They classified Coalition, Legitimating, Pressure, and Exchange as hard influence tactics, classified set Rational Persuasion as a rational influence tactic, and classified Inspirational Appeals, Ingratiation, and Personal Appeals as soft influence tactics. Their results suggested that hard influence tactics were less effective than soft influence tactics, which also had a generally positive impact on employee performance [41].

Zhou (2003) [42] discovered that employees exhibit creativity when supervisors engage less closely in monitoring and provide more developmental feedback. Close monitoring can be seen as a controlling practice that makes employees worry that their supervisors may disapprove of their actions. They are, thus, distracted and preoccupied with task-irrelevant concerns and fears [42]. When supervisors provide developmental feedback, however, they are essentially engaging in an informational practice that provides employees with behaviorally relevant advice. This may lead to improved performance in the absence of pressure about a particular outcome [42]. These two concepts (i.e., close monitoring and developmental feedback) are closely related to hard, soft, and rational influence tactics. Similarly, according to Cortini and Scaratti [43], if an organization controlled their employees’ blog activities (e.g., blog policies), employees cannot express their free expression. Hence, this managing style can become an obstacle to organizational creativity. This research support previous studies. It can, thus, be assumed that individual influence tactics significantly impact job creativity.

2.2. Job Creativity

Amabile (1996) [44] defined creativity as the ability to combine or connect ideas in a unique way. Creativity is greatly influenced by the work environment. Oldham and Cummings (1996) [45] defined creativity as a useful product, idea, or process that focuses on performance. Perry-Smith (2006) [46] similarly defined workplace creativity as an approach for finding novel and useful ideas, processes, and solutions. The literature on creativity has followed three major streams. One focuses on personal characteristics that affect creativity and specifically examines the crucial roles of both personality and cognitive style [47], while the other focuses on contextual and organizational factors defined as “dimensions of the working environment that potentially affect employee creativity but are not part of the individual” [48]. More specifically, they studied contextual and organizational factors that can support creativity and the role of training and improvements in enhancing creativity [43,48,49,50,51,52]. With respect to these perceptions, we focused on the working environment that the leader exerted an effect on employee creativity. In addition, a number of previous studies have examined the precedents of job creativity. In this context, results have shown that personal factors, special values, job motivation, causal relationships, and professional characteristics and relationships within an organization are closely related to service-staff creativity [47,53,54]. Amabile (1987) [55] suggested a close correlation between productivity and creativity. The same study established that creativity directly affected corporate and job performance. Moreover, Hur, Moon, and Rhee (2016) [56] revealed that job creativity performs a mediating role for comparing work and job performance. Job creativity, thus, has an important relationship with job performance.

2.3. Job Performance

Performance refers to how employee behavior is viewed according to organizational desirability and appropriateness (e.g., how well reports are written and problems are solved) [57]. Price (1968) [58] defined the extent to which a target could be achieved in this context. Because job performance is conceptually ambiguous, it is often replaced by factors such as productivity, the goal attainment process, cohesiveness, commitment, and attachment. Job performance is also generally used to refer to productivity since it is conceptualized by industrial psychologists, who see it as the extent to which an organization’s goals are successfully achieved [59]. Vatankhah, Javid, and Raoofi discovered that high-performance work practices such as empowerment, reward, and promotion is positively related to perceived organizational support, and, thus, reduce counter-productive work behavior in the airline area [60]. Moreover, in the organizational behavior contexts, competent flight attendants who are capable of implementing their tasks successfully can positively affect to the airline’s service quality and customers’ satisfaction [61] As such, job performance does not simply refer to the accomplishments of a single team member. Rather, it is a comprehensive assessment of desired organizational behavior according to organizational measurements and influences. Employee performance is, thus, intertwined throughout the overall job.

2.4. Research Model and Hypotheses

This study’s theoretical model was developed on the basis of the conceptual background discussed above (Figure 1). It depicts the hypothesized relationships among influence tactics, job creativity, and job performance. Job creativity was also integrated as a mediator. The model contained a total of 11 research hypotheses, which include the following.

Hypothesis 1 (H1).

Rational persuasion positively influences job creativity.

Hypothesis 2 (H2).

Inspirational appeals positively influence job creativity.

Hypothesis 3 (H3).

Consultation positively influences job creativity.

Hypothesis 4 (H4).

Ingratiation positively influences job creativity.

Hypothesis 5 (H5).

Personal appeals positively influence job creativity.

Hypothesis 6 (H6).

Exchange negatively influences job creativity.

Hypothesis 7 (H7).

Coalition negatively influences job creativity.

Hypothesis 8 (H8).

Legitimating negatively influences job creativity.

Hypothesis 9 (H9).

Pressure negatively influences job creativity.

Hypothesis 10 (H10).

Job creativity positively influences job performance.

Hypothesis 11 (H11).

Job creativity can positively mediate between influence tactics and job performance.

3. Methods

3.1. Measures

The validated measurement items were adopted from previous studies [31,47,62]. Multiple items were measured according to a five-point scale, such as ‘1 = completely disagree to 5 = completely agree.’ Among three variables above, influence tactics were conducted to the independent variable, and we regarded job performance as a dependent variable. A total of 52 items were utilized for our research including sample characteristics (See Tables 2–4). For influence tactics, we employed 27 items from Yukl, Seifert, and Chavez [31]. For instance, proposed activity or change refers to an opportunity to complete a really exciting or rewarding activity. Twelve items were adopted from Coelho and Augusto [47] to measure job creativity (e.g., I try a new approach to doing my job), while another 12 items were adopted from Liao and Chuang [62] to measure job performance (e.g., I am friendly and helpful to customers).

3.2. Survey Questionnaire and Data Collection

The survey questionnaire used in this study comprised these measurement items, a research description, and questions about personal characteristics. The questionnaire was pre-tested and revised based on feedback from faculty and graduate students majoring in hospitality and tourism. We then developed a final version based on reviews and feedback from other scholars. Next, data were collected from a total of 210 Korean flight attendants at the Incheon International Airport. Specifically, a battery of self-reported questionnaires was administered to these participants, who were also given appropriate information about the research aims. We obtained a total of 182 questionnaires from among the 210 respondents. Those with missing data and silent responses were excluded from analysis.

3.3. Sample Characteristics

Of the participants, 86.8% were female and 13.2% were male. A total of 55.8% indicated they were between 26–30 years of age, while 18.7% reported they were between 31–35, 12.0% indicated they were older than 36, and 13.7% reported they were 25 or younger. All participants were over 20 years of age. A total of 64.8% were unmarried, while 35.2% were married. For income, 5.4% reported income over $50,000, 8.7% reported income from $40,000 to $49,999, 52.1% reported income from $30,000 to $39,999, and 33.5% reported income under $30,000. For education, 62.0% reported they were college graduates, followed by 35.7% who indicated some college/2-year college graduates, and 2.2% had attended graduate school or above. A total of 26.4% reported that they had worked at their current jobs for less than two years, while 41.7% indicated 2–4 years, 23.0% reported 5–9 years, 5.4% indicated 10–14 years, and 3.3% indicated more than 15 years. Most participants were flight attendants (89.6%), followed by assistant pursers (7.6%), pursers (1.6%), and senior pursers (1.1%).

4. Results

4.1. Descriptive Analysis

Descriptive analysis was conducted to examine the tendency of the variables.

Table 1. Result of descriptive analysis on each measurement.

	N	Minimum	Maximum	Mean	Standard Deviation	Skewness	Kurtosis
1.Rational Persuasion	182	1.00	5.00	3.38	0.918	−0.076	−0.169
2.Inspirational Appeals	182	1.00	5.00	3.32	0.862	0.064	−0.221
3. Consultation	182	1.00	5.00	3.36	0.806	−0.189	0.149
4. Ingratiation	182	1.00	5.00	3.32	0.782	−0.009	0.159
5.Personal Appeals	182	1.00	5.00	2.99	0.883	0.283	−0.006
6. Exchange	182	1.00	5.00	2.20	0.869	0.777	0.753
7. Coalition	182	1.00	5.00	2.12	0.864	0.250	−0.937
8. Legitimating	182	1.00	5.00	2.35	0.990	0.321	−0.339
9. Pressure	182	1.00	5.00	2.10	1.046	0.960	0.200
10. Job creativity	182	1.00	5.00	3.25	0.819	−0.016	0.120
11. Job performance	182	1.75	5.00	3.65	0.729	0.056	−0.484

shows the result of descriptive analysis. In order to implement descriptive analysis, the number of respondent (=N), minimum value, maximum value, mean, standard deviation, skewness, and kurtosis were performed.

4.2. Reliability and Exploratory Factor Analyses

Reliability analyses and exploratory factor analyses (EFAs) were conducted to verify internal consistency, solve multicollinearity problems for further analysis, and simplify the analysis by reducing the number of variables. Cronbach’s alpha values were performed as the criteria of reliability. Many researchers deemed that if Cronbach’s alpha values are higher than 0.6, reliability was established. Thus, we adopted this perspective. For all EFAs, principal component extraction and varimax rotation methods (orthogonal rotation) were applied to keep factors independent. Five items that did not fit the theoretical structure were deleted after the EFA for influence tactics. The correlations among items were significant (KMO = 0.847, Bartlett’s test: 2634.638 [df = 231, p = 0.000]). Nine factors were formed and defined as “Rational Persuasion,” “Inspirational Appeals,” “Consultation,” “Ingratiation,” “Personal Appeals,” “Exchange,” “Coalition,” “Legitimating,” and “Pressure.” The total percentage of variance was 84.115%. All Cronbach’s alpha values were greater than 0.70 (

Table 2. Results of factor and reliability analyses on influence tactics.

Factors (Eigenvalue, % of Variance) Cronbach’s α	Items	Commonality	Factor Loading
1. Rational persuasion (1.594, 7.244) 0.925	Use facts and logic to persuade a request or suggestion Explain clearly why a request or proposed change is needed to achieve business goals	0.913 0.902	0.747 0.762
2. Inspirational Appeals (3.140, 14.272) 0.860	The proposed activity or change is an opportunity to do something really exciting and rewarding Talk about values and ideals when suggesting new activities or changes Make encouraging speeches or presentations that invite passion for the proposed activity or change	0.793 0.775 0.806	0.824 0.833 0.884
3. Consultation (1.193, 5.425) 0.749	Discuss ideas for proposed activities or changes that you want to support or enforce Encourage them to suggest ways to improve the preliminary plans or proposals to be supported or enforced	0.743 0.901	0.545 0.806
4. Ingratiation (1.589, 7.222) 0.733	Say that you have the skills or knowledge necessary to perform the request Praise past achievements and accomplishments while assigning tasks	0.860 0.810	0.850 0.777
5. Personal Appeals (1.689, 7.679) 0.730	Says they need to ask for a favor before telling you what it is Asks you as a friend to do them a favor	0.827 0.842	0.815 0.841
6. Exchange (2.337, 10.624) 0.867	Offers to do something for you in exchange for carrying out a request Offers to do a specific task or favor for you in return for your help and support Offers to do something for you in the future in return for your help now	0.847 0.871 0.817	0.863 0.848 0.703
7. Coalition (2.652, 12.053) 0.885	Mentions the names of other people who endorse a proposal when asking you to support it Comes with someone else to support you when you make a request or offer In order to fulfill the request or to support the proposal, asks for help from a respectable person to perform it	0.826 0.864 0.802	0.803 0.871 0.761
8. Legitimating (1.687, 7.442) 0.896	Says that the request or proposal meets official rules and policies Claims or proposals are consistent with previous agreements or contracts	0.889 0.876	0.772 0.769
9. Pressure (2.674, 12.154) 0.889	Demands that you carry out a request Repeatedly checks to see if you have carried out a request Tries to pressure you into carrying out a request	0.851 0.856 0.836	0.862 0.876 0.851

Notes: KMO = 0.847. Bartlett’s test: 2634.638 (df = 231, p = 0.000). % of total variance: 84.115%.

). The result of the EFA for job creativity showed that each item’s commonality was greater than 0.70, with all factor loadings over 0.85. The correlations among items were significant (KMO = 0.803, Bartlett’s test: 545.281 [df = 6, p = 0.000]). One factor was formed and defined as “job creativity.” The total percentage of variance was 80.223%. The Cronbach’s alpha value was greater than 0.90 (

Table 3. Results of factor and reliability analyses on job creativity.

Factors (Eigenvalue, % of Variance) Cronbach’s α	Items	Commonality	Factor Loading
1. Job creativity (3.209, 80.223) 0.917	I/team members try to be as creative as possible when dealing with work. I/team members try new approaches to work. The team leader thinks that I/team members am/are creative when working. When working, I/team members demonstrate creativity to overcome difficulties.	0.809 0.798	0.899 0.894
		0.814	0.902
		0.787	0.887

Notes: KMO = 0.803. Bartlett’s test: 545.282 (df = 6, p = 0.000). % of total variance: 80.223%.

). The EFA for job performance showed that each item’s commonality was greater than 0.60, with all factor loadings over 0.85. The correlations among items were significant (KMO = 0.803, Bartlett’s test: 398.944 [df = 6, p = 0.000]). One factor was formed and defined as “job performance.” The total percentage of variance was 74.183%. The Cronbach’s alpha value was greater than 0.80 (

Table 4. Results of factor and reliability analyses on job performance.

Factors (Eigenvalue, % of Variance) Cronbach’s α	Items	Commonality	Factor Loading
1. Job performance (2.967, 74.183) 0.880	I/team members am/are friendly and helpful to customers. I/team members quickly undertake the work desired by customers. I/team members ask good questions about what they need and find what they want. I/team members can help customers when they need something.	0.699 0.803	0.836 0.896
		0.725	0.852
		0.740	0.860

Notes: KMO = 0.803. Bartlett’s test: 398.944 (df = 231, p = 0.000). % of total variance: 74.183%.

).

4.3. Correlation and Multiple Regression Analyses

A correlation analysis was utilized to verify discriminant validity before conducting regression analyses. Since EFAs were conducted using the varimax rotation method, influence tactics (i.e., Rational Persuasion, Inspirational Appeals, Consultation, Ingratiation, Personal Appeals, Exchange, Coalition, Legitimating, and Pressure), job creativity, and job performance presented no correlations (

Table 5. Results of the correlation analyses.

	1	2	3	4	5	6	7	8	9	10	11
1. Rational Persuasion	1
2. Inspirational Appeals	0.671 **	1
3. Consultation	0.686 **	0.618 **	1
4. Ingratiation	0.416 **	0.393 **	0.507 **	1
5. Personal Appeals	0.237 **	0.155 **	0.362 **	0.451 **	1
6. Exchange	−0.075	0.018	0.010	0.081	0.247 **	1
7. Coalition	−0.133	−0.061	0.024	−0.002	0.298 **	0.601 **	1
8. Legitimating	0.149 *	0.045	0.208 **	0.175 *	0.311 **	0.446 **	0.590 **	1
9. Pressure	−0.086	−0.124	0.029	0.077	0.057	0.432 **	0.404 **	0.516 **	1
10. Job creativity	0.516 **	0.502 **	0.477 **	0.390 **	0.154 *	−0.212 **	−0.111	0.083	−0.221 **	1
11. Job performance	0.456 **	0.399 **	0.462 **	0.449 **	0.429 **	−0.096	−0.024	0.093	−0.113	0.608 **	1

Note: * p < 0.05 and ** p < 0.01.

).

A multiple regression analysis was conducted to empirically examine the relationships among influence tactics, job creativity, and job performance, as seen in the proposed model (Figure 1).

Table 6. Results of the regression analysis for influence tactics → job creativity (H1–H9).

	β	t-Value	p
1. Rational Persuasion	0.158	1.707	0.090
2. Inspirational Appeals	0.225	2.654 **	0.009
3. Consultation	0.114	1.261	0.209
4. Ingratiation	0.206	2.808 **	0.006
5. Personal Appeals	−0.059	−0.816	0.416
6. Exchange	−0.231	−3.018 **	0.003
7. Coalition	0.052	0.607	0.545
8. Legitimating	0.191	2.305 *	0.022
9. Pressure	−0.215	−2.955 **	0.004
Adjusted $R^2$	0.397
F	14.228 ***

Notes: Independent Variable. Influence tactics. Dependent Variable: Job Creativity. VIF < 10 in all cases, β = standardized β, * p < 0.05, ** p < 0.01, and *** p < 0.001.

and

Table 7. Results of the regression analysis for job creativity → job performance (H10).

	β	t-Value	p
1. Rational Persuasion	0.608	10.269 ***	0.000
Adjusted $R^2$	0.366
F	105.446 ***

Notes: Independent Variable: Job creativity. Dependent Variable: Job Performance. VIF < 10 in all cases. β = standardized β. *** p < 0.001.

show the results. As seen in Table 6, the degree to which influence tactics explained job creativity was detected at 39.7% (Adjusted $R^2$ = 0.397). This regression model was significant (F-value = 14.228, p = 0.00). It is evident that the influence of Rational Persuasion (β = 0.158, p > 0.05) was not significant. Therefore, Hypothesis 1 was not supported. On the other hand, the influence of Inspirational Appeals (β = 0.225, p < 0.01) and Ingratiation (β = 0.206, p < 0.01) were significant. This supported Hypotheses 2 and 4. However, the influences of Consultation (β = 0.114, p > 0.05) and Personal Appeals (β = −0.059, p > 0.05) were not significant. Thus, Hypotheses 3 and 5 were not supported. The influences of Exchange (β = −0.231, p < 0.01) and Pressure (β = −0.215, p < 0.01) were significant, while the influence of coalition (β = 0.052, p > 0.05) was not. The influence of Legitimating (β = 0.191, p < 0.01) was significant. However, Hypothesis 8 posited that legitimating would negatively influence job creativity. Thus, Hypotheses 6 and 9 were supported, while Hypotheses 7 and 8 were not.

The impact of job creativity was also assessed (Table 7). The degree to which job creativity explained job performance was detected at about 36.6% (Adjusted $R^2$ = 0.366). This regression model was significant (F-value = 105.446, p = 0.00). These results showed that the influence of job creativity (β = 0.608, p < 0.001) was significant. Therefore, Hypothesis 10 was supported.

4.4. Mediation Testing

The mediator variable was tested to investigate its effect on job creativity. This involved a three-step mediated regression analysis [63] and Sobel test (multiple regression analyses for influence tactics and job creativity were previously conducted (Table 6)). The results indicated that five of the independent variables (i.e., Inspirational Appeals, Ingratiation, Exchange, Legitimating, and Pressure) were significant. In the second step, multiple regression analyses were conducted on influence tactics and job performance (

Table 8. Results of the regression analysis for influence tactics → job performance.

	β	t-Value	p
1. Rational Persuasion	0.158	1.659	0.990
2. Inspirational Appeals	0.127	1.446	0.150
3. Consultation	0.078	0.840	0.402
4. Ingratiation	0.177	2.336 *	0.021
5. Personal Appeals	0.295	3.975 ***	0.000
6. Exchange	−0.177	−2.246 *	0.026
7. Coalition	0.041	0.462	0.645
8. Legitimating	0.011	0.132	0.895
9. Pressure	−0.062	−0.828	0.409
Adjusted $R^2$	0.357
F	12.177 ***

Notes: Independent Variable: Influence tactics. Dependent Variable: Job Performance. VIF < 10 in all cases. β = standardized β. * p < 0.05. *** p < 0.001.

).

Table 8 shows that the degree to which influence tactics explained job creativity was detected at about 35.7% (Adjusted $R^2$ = 0.357). This regression model was significant (F-value = 12.177, p = 0.00). The results showed that Ingratiation (β = 0.177, p < 0.05), Personal Appeals (β = 0.295, p < 0.01), and Exchange (β = −0.177, p < 0.05) were the only significant independent variables. Last, the third step investigated the impact of influence tactics and job creativity on job performance (

Table 9. Results of the regression analysis for influence tactics and job creativity → job performance.

	β	t-Value	p
1. Rational Persuasion	0.086	0.994	0.322
2. Inspirational Appeals	0.023	0.290	0.772
3. Consultation	0.026	0.309	0.758
4. Ingratiation	0.083	1.184	0.238
5. Personal Appeals	0.322	4.819 ***	0.000
6. Exchange	−0.071	−0.982	0.328
7. Coalition	0.017	0.214	0.831
8. Legitimating	−0.076	−0.978	0.329
9. Pressure	0.037	0.528	0.598
10. Job creativity	0.459	6.488	0.000
Adjusted $R^2$	0.481
F	17.787 ***

Notes: Independent Variable. Influence tactics, job creativity. Dependent Variable: Job Performance. VIF < 10 in all cases. β = standardized β. *** p < 0.001.

).

Table 9 shows that the degree to which influence tactics and job creativity explained job performance was detected at about 48.1% (Adjusted $R^2$ = 0.481). This regression model was significant (F-value = 17.787, p = 0.00). The results showed that the only significant independent variable was Personal Appeals (β = 0.322, p < 0.01). Job creativity was also significant (β = 0.459, p < 0.01). Thus, all three steps of the regression analyses revealed that influence tactics significantly affected job creativity, which had a higher influence on job performance than influence tactics. This supported Hypothesis 11. Hence, job creativity can mediate the effects of influence tactics on job performance. All results from influence tactics supported the hypothesis concerning mediation.

A Sobel test verified the above statements. That is, inspirational appeals → job creativity → job performance had an indirect effect (0.087, p < 0.05), while there was the indirect effect of ingratiation → job creativity → job performance was 0.088 (p < 0.05), exchange → job creativity → job performance had an indirect effect (−0.088, p < 0.01), and the indirect effect of legitimating → job creativity → job performance was 0.064 (p < 0.05). Pressure had a −0.068 indirect effect (p < 0.01).

5. Discussion

This study provided crucial insight into the necessary methods for developing job creativity and job performance among flight attendants by examining the relationships among influence tactics, job creativity, and job performance. Eleven hypotheses were formulated on the basis of the results of previous studies. A proposed theoretical framework was then formed. The model was examined according to data collected from 182 cabin crewmembers who worked for a Korean national carrier. According to one-way ANOVA analyses, in the age group and experience group, there was no difference between the groups (p > 0.05). The data analysis outcome indicated that five of the nine individual influence tactics (i.e., Inspirational Appeals, Ingratiation, Exchange, Legitimating, and Pressure) had significant effects on job creativity, which positively influenced job performance. More specifically, Inspirational Appeals, Ingratiation, and Legitimating positively influenced job creativity, while Exchange and Pressure had negative effects. Moreover, job creativity acted as a mediator between influence tactics and job performance. Hence, this study’s findings demonstrate causality among influence tactics, job creativity, and job performance.

Hypothesis 8 was not supported (i.e., Legitimating did not negatively influence job creativity, but, instead, had a positive influence). This is presumed to be related to a Korean airlines’ trait. A previous study indicated that flight attendants working for Korean airlines were engaged in a more vertical relationship involving managers and subordinates than among other international airline employees [64]. Hard influence tactics are usually affected by the legitimate power of the subject [39]. It is, thus, believed that cabin crews working for Korean carrier regard legitimating as a natural form of instruction.

This study’s results provided both theoretical and practical implications. Previous studies mainly classified influence tactics into categories, while some revealed correlations between influence tactics and other job activities [2,41,65]. However, it is necessary to examine the effects of leadership-enacted influence tactics on the various job activities performed by subordinates. This study examined the effects of each leader-influence tactic on job creativity among employees. Results indicated that certain influence tactics were effective in organizational situations. These findings are meaningful in that they support the previous studies and confirm that influence tactics influence job performance through job creativity in the Korean aviation industry. It contributed to clarify the effectiveness of influence tactics and expand the scope of research. In addition, theoretical implications were derived by studying the influence relationship between influence tactics and creativity, which was lacking in previous studies. This research also showed that job creativity acted as a mediator between influence tactics and job performance. This consequently revealed the specific effects of using influence tactics, which enhanced persuasiveness in practical terms. Those in managerial positions in the airline industry can select different influence tactics depending on the situation. Lastly, this study’s findings supported previous research revealing the effects of the influence tactics and the relationship between job creativity and job performance. In terms of a practical perspective, strong influence tactics such as pressures and exchanges, can help answer the practical demands of managers when they see that it hampers job creativity for employees. In other words, it has been confirmed that it is not positively affecting the employees to coercively order in vertical relations of the Korean airlines. Even if the strict hierarchy cannot be changed in a short period of time, lowering the elements of pressure and control in the on-the-job direction can improve the performance of employees.

This study had several limitations. First, there was a limit to clarifying the causal relationship due to its transversal design. Further research can be conducted using an experimental/longitudinal design to detect causal relationships. Second, few previous studies had directly explored the causality between influence tactics and job creativity. Hence, this study adopted concepts from previous research on meta-classification and creativity [26,37,38,41,42]. However, the individual impact tactics included in the meta-categories were somewhat different among scholars. Thus, the results of these studies were also inconsistent. Future studies will require a more rigorous verification of these meta-classifications.