The role of leadership and organizational learning in fostering high performance of tourism firms in Vietnam

Abstract

This study extends prior work by developing a comprehensive framework examining how leadership and organizational learning facilitate the achievement of high performance in organizations. Following quantitative approach, this study used survey questionnaire to collect data from leaders in the tourism sector. SmartPLS was applied to perform PLS-SEM statistical techniques with 638 responses collected. The findings revealed that high performance of tourism firms was directly and indirectly affected by leadership traits, leadership competencies, complexity leadership and organizational learning. This study has a significant contribution to leadership, organizational learning, and organizational high performance literature by providing a comprehensive framework of the relationships among these phenomena. Significant implications for both theory and practice were provided.

Keywords:

• Organizational high performance
• leadership trait
• leadership competence
• complexity leadership
• organizational learning

PUBLIC INTEREST STATEMENT

Today’s global business environment has been characterized as competitive and complex due to speedy changes in social, economic, and technological aspects. These changes have urged many organizations to shift the foundation of strategy and competition from traditional method of relying on physical and financial resources to modern approach of using intellectual assets. This study aims to investigate the relationship between different leadership and organizational high performance, mediated by organizational learning within the context of tourism firms in Vietnam. The findings from this study can be used to offer powerful and scientifically proven recommendations for leaders and policy makers towards the achievement of organizational high performance of tourism firms.

1. Introduction

Today’s global business environment has been characterized as dynamic, competitive, complex, and multifaceted due to speedy changes in social, economic, and technological aspects. These changes have urged many organizations to shift the foundation of strategy and competition from traditional method of relying on physical and financial resources to monitor and maintain daily operations, to modern approach of using intellectual assets to create more values for customers and achieve superior performance (Kamukama et al., 2010). Furthermore, many organizations have been stalled to a near standstill due to the COVID-19 pandemic and the questions of whether they can survive after the demise of the crisis is still unknown (Bartik et al., 2020, Falk et al., 2021). Given the current situation, organizations are increasingly in search for various methods and business strategies to capitalize on their accessible resources and competencies to maintain operational efficiency during the crisis, capture opportunities within the marketplace, achieve superior performance, and remain competitive (Obeidat, 2016).

Earlier scholars stated that a firm’s resource-based view emphasizes achieving competitive advantage and superior long-term performance by utilizing the available resources such as knowledge, processes, and other capabilities (Barney, 1995; Wernerfelt, 1984). Added to this, Grant (1996) argued that a firm’s knowledge-based view highlights the use of the knowledge base of a firm as a strategic resource to augment sustainable performance and gain competitive advantage. In the workplace, organizational learning has been found to affect the success and survival of businesses (Weldy, 2009). As reported in past findings (Narsa, 2019; Oh, 2018; Zhou et al., 2015), organizational learning contributes to several organizational outcomes and thus firms need to promote learning and give it a great priority. Besides, leadership is a critical function of management in all businesses since strong leadership facilitates the alignment of people and resources to accomplish organizational goals and objectives (Northouse, 2018). In this regard, leaders then face many difficulties in dynamically integrating internal resources into superior performance and transforming their firms to adapt with the current complex and unusual situations of the COVID-19 pandemic. Many attempts have been made to answer the question of how leaders lead their organizations toward desirable outcomes during the crisis (Lamprinou et al., 2021; Lee et al., 2021; Ngoma et al., 2021).

However, although previous studies have examined the relationship between leadership and organizational outcomes, the findings are still inconsistent and inclusive towards simple methods (questionnaires) and replications of familiar leadership approaches (Yukl, 2013). The problem is exacerbated by the fact that there is no clear answer to the question of which aspects (traits, competencies, or behaviors) of leaders are important to organizational outcomes. In addition, while notable research has investigated the association between leadership and organizational learning on organizational high performance independently, yet previous researchers infrequently integrated them to make a more comprehensive framework. Moreover, these Western-developed phenomena were not tested in the context of Vietnam—a developing country in Asia.

To resolve these puzzles, this study aims to investigate the relationship between different leadership components and organizational high performance, mediated by organizational learning within the context of tourism firms in Vietnam. In this direction, our study fills the identified gaps in the literature and provides several contributions. First, this study extends the theoretical and empirical studies on the influences of leadership on organizational learning and organizational high performance by incorporating multiple leadership theories (trait theory, competence theory, complexity leadership theory) as predictors. Second, complexity leadership concerns a flexible type of leadership style that a leader aims at enabling their firms to thrive in the environment full of uncertainty and adapt to chaotic environments (Marion & Uhl-Bien, 2002). It should be especially relevant in the current crisis and turbulent business context due to the recent COVID-19 pandemic but has so far remained an understudied leadership approach (Tourish, 2019). The current research contributes to the leadership literature by examining complexity leadership—an emergent leadership approach and its implication towards organizational learning and organizational high performance. Third, there is significantly scarce research on how organizational learning affect the achievement of high performance in tourism enterprises. This study would enrich the organizational learning literature and provide further insights to the knowledge-based view by clarifying the role of organizational learning in engendering improved firm performance. Fourth, this study further examines whether organizational learning mediate the relationship between leadership and organizational high performance. This would help in offering further theoretical understanding of the mediating mechanism through which leadership influences organizational learning and ultimately result in superior performance of firms. Last but not least, the findings from this study can also be used to offer powerful and scientifically proven recommendations for leaders and policy makers towards the achievement of organizational high performance of tourism firms and the development of tourism industry in Vietnam.

2. Literature review and hypotheses development

2.1. Leadership

Leadership is defined as an influential process in which leaders empower their followers and facilitates the success of a group or an organization (Northouse, 2018; Yukl, 2013). Over decades, the evolution of this field is marked by the emergence of several leadership theories. Trait theory is the earliest theory on leadership, which assumes that effective leaders acquire specific innate personalities and attributes (Stogdill, 1948). Since studies on trait approach resulted in mixed results and skepticism due to the existence of various traits (Colbert et al., 2012), many attempts have been made to provide a unified personality framework, such as the five-factor model (Northouse, 2018). However, Bono et al. (2014) later argued that researchers should turn their attention to more traits that account for characteristics above and beyond the five-factor traits and are more relevant in the future business environment to advance the line of research on trait theory. To that end, Hiller and Beauchesne (2014) identified core self-evaluation, narcissism, need for achievement, and risk propensity as understudied traits that could provide a better conceptual explanation of leadership and how it predicts organizational-level outcomes such as strategy, culture, and performance. Recent literature showed that many researchers have expanded the domain of leaders’ personality and employed core self-evaluation and narcissism (Ding & Lin, 2020; Resick et al., 2009; Wang & Xu, 2019), as well as need for achievement and risk propensity (Luo et al., 2016; Marco & John, 2013; Tang & Tang, 2007; Yu & Chen, 2016) in their studies.

Competence theory adopts a leader-centered perspective to leadership and suggests that leaders acquire certain skills and competencies to make them effective (Northouse, 2018). Leadership competencies refer to a group of “essential skills, knowledge, and personal characteristics” (Lucia & Lepsinger, 1999, p. 1) that enable leaders to achieve superior performance and gain the results they expected (Spencer & Spencer, 1993). According to Amedu and Dulewicz (2018), three clusters of leadership competencies that contribute greatly to leadership effectiveness and performance of organizations in a variety of contexts are results orientation, cognitive competence, and interpersonal competence.

Behavioral theory focuses on the behaviors of leaders rather than their inherent personalities (Northouse, 2018). Among several leadership behaviors (e.g., task-oriented, people-oriented, participative, ethical, spiritual, etc.), researchers have increasingly paid attention to study transformational leadership over the past decades (Antonakis & House, 2002). According to Burns (1978), transformational leaders identify personal values and vision that guide others’ actions and initiate changes beneficial for the organizations. However, one limitation of transformational leadership lies in its failure to consider the organizational context and the advent of unpredictable leadership (Lord, 2008). Other scholars also stated that this approach overly relies on the leader-follower stereotype and thus failing to describe organizational learning processes (Gronn, 2002; Yukl, 1999).

Recognizing the limitations of transformational leadership and the abundance of existing empirical studies on the theory, future studies have turned the attention to more emerging conceptions of leadership such as complexity leadership (Yukl, 2013). According to Uhl-Bien and Arena (2017), complexity leadership refers to the structures, activities, and processes that enable organizations to thrive in the environment full of uncertainty. Hazy and Prottas (2018) stated that complexity leadership involves two leadership behaviors. The first dimension is generative leadership, which is how leaders bring new information about conflicting perspectives into the knowledge sharing and encourage involved agents to experiment and learn from these perspectives. The second dimension is administrative leadership, which is how leaders “help to promote clarity of action and accountability and would thus contribute to value potential realized through efficacy” (Hazy & Prottas, 2018, p. 328). Although complexity leadership is said to remediate the limitations of earlier leadership approaches in explaining learning processes (Marion & Uhl-Bien, 2002; Uhl-Bien et al., 2007), research on this leadership approach is limited due to the impact of overly heroic and popular leadership models (Tourish, 2019).

Since leadership research is inconclusive and biased towards simple methods and replications of familiar topics, Yukl (2013) encouraged researchers to use multiple leadership theories and multiple research methods to provide better understand of leadership and its influences. This study acknowledges the importance and relevance of leadership traits (core self-evaluation, narcissism, need for achievement, and risk propensity), leadership competencies (cognitive, interpersonal, and results orientation), and the newly emerged complexity leadership in predicting organizational learning and organizational high performance of firms operating in the current complex and ambiguous environment.

2.2. Organizational learning

Organizational learning is defined as a process of gaining new knowledge that consequently influences individual and organizational outcomes (Fiol & Lyles, 1985; Huber, 1991). March (1991) described organizational learning as the exploitation and exploration of knowledge. Huber (1991) then postulated that organizational learning involves the acquisition, distribution, interpretation, and storage of information from a variety of sources. In the same vein, Pérez López et al. (2005) proposed that organizational learning pointed to how knowledge is acquired, distributed, interpreted, and stored within the organizations. Knowledge management is considered to be closely related to organizational learning (Vera & Crossan, 2003). Most definitions of knowledge management include the creation, transference, application, and storage of knowledge (Alavi & Leidner, 2001; Nonaka & Takeuchi, 1995). According to Pun and Balkissoon (2011), the concepts of organizational learning and knowledge management are integrated. Other studies found that organizational learning is a part of knowledge management (Fteimi & Lehner, 2016; Serenko, 2013), or even being absorbed by knowledge management (Castaneda et al., 2018). In this study, organizational learning is the main focus and is defined as the learning processes that facilitate organizations to achieve their goals (Fiol & Lyles, 1985; Huber, 1991).

2.3. Organizational high performance

The performance of an organization is defined as its actual output compared to its desired goals (Kotlar et al., 2018). Peters and Waterman (1982) used a term called “high performance” to describe organizations that have a strong alignment between structure, leadership, culture, strategy, and employees’ capabilities. Following the seminal work of Peters and Waterman (1982), other scholars described high performance of an organization as how it effectively responses to the demand of the marketplace (Owen et al., 2001); or how it achieves better results than competitors over a longer period (De Waal, 2007). The importance of achieving organizational high performance has spurred the development of many approaches to accurately measure it. de Waal (2018a) reviewed existing literature on high performance measures and found that organizational high performance should be subjectively measured based on managerial perspectives, especially when “access to objective performance data is restricted or collection of the information is just not feasible” (p. 3). Based on the foregoing premises, in this study organizational high performance is defined as the achievement of satisfactory financial and non-financial results and is subjectively measured through the perception of leaders.

2.4. Hypotheses development

2.4.1. Leadership and organizational learning

Leaders play a significant role since they facilitate the collective improvement of organizational learning and decide strategies to respond to market demands. Matošková et al.’s (2018) study revealed strong significant positive relationships between leaders’ characteristics and knowledge sharing in firms operating in the Czech Republic. Zhang et al. (2018) argued that core self-evaluation affects knowledge sharing and creativity at organizations. Besides, extant literature proved that healthy narcissism or grandiose narcissism can improve organizational outcomes (Huang et al., 2019; Kim, 2018; Reina et al., 2014; Yoo, 2016). This appreciation makes it essential to consider the positive influences of leaders’ narcissistic personality on organizational learning. Need for achievement has long been found to positively relate to learning and speed of performance (Lowell, 1952). Risk propensity was found to be embedded in the concept of organizational learning capability with an assumption that organizational learning will be fostered when people take risks and accept mistakes (Alegre & Chiva, 2008; Onağ et al., 2014).

Amy’s (2008) study revealed that leaders exhibit a variety of characteristics and competencies, which enable them to become facilitators of organizational learning. Previous studies showed that emotional intelligence contributes to learning at organizations (Bettis-Outland & Guillory, 2018; Ghosh et al., 2012). Jain and Jeppe Jeppesen (2013) found a positive influence of leaders’ cognitive competences on the practices of managing knowledge in a thermal power generation firm. In addition, several studies have found that leaders’ social or interpersonal intelligence plays a vital role in leadership performance, knowledge acquisition, innovation, and creative performance (Kong, 2015; Siswanti et al., 2018). Kong (2015) stated that social competencies contribute to the analysis, utilization, and deployment of knowledge, which are beneficial for the organizations.

In addition, through generative leadership, leaders encourage others to experiment and learn from varying viewpoint, which consequently generates new knowledge and promotes knowledge sharing within organizations (Arena & Uhl-Bien, 2016; Chowdhury, 2005; Hazy & Prottas, 2018). Džinić (2015) conducted a study in three Croatian city governments and found that administrative leadership has a significant positive relationship with organizational learning. Hence, the following hypotheses are proposed:

H1. Leaders’ perceptions of their leadership traits, including core self-evaluation (H1a), narcissism (H1b), need for achievement (H1c), and risk propensity (H1d) are associated with organizational learning.

H2. Leaders’ perceptions of their leadership competencies, including results-orientation (H2a), cognitive competence (H2b), and interpersonal competence (H2c) are associated with organizational learning.

H3. Leaders’ perceptions of their complexity leadership, including generative leadership (H3a) and administrative leadership (H3b) are associated with organizational learning.

2.4.2. Leadership and organizational high performance

An empirical study by Peterson et al. (2003) concluded that leaders’ characteristics ultimately affect firm performance. Using core self-evaluation scale developed by Judge and colleagues (2003), Simsek et al. (2010) found that the core self-evaluation of leaders has a connection with entrepreneurial orientation of organizations. Some researchers have pointed out that leaders’ grandiose narcissism has a positive impact on firm performance (Huang, 2019; Reina et al., 2014; Yoo, 2016). Kim (2018) conducted a study on 30 public institutions and found that personal characteristics of executives (narcissism) positively affects the performance of these firms. Need for achievement has also been acknowledged as a factor that positively affects organizational performance (Lee & Tsang, 2001). Relating risk propensity and firm performance, many studies suggested that leaders who are willing to take risks produced more desirable performance (Cain & Mckeon, 2012; Sidek & Zainol, 2011).

Earlier studies contended that leaders’ competencies positively affect the performance and success of organizations (McClelland, 1973; Pickett, 1998). In a study of the Fly Emirates Airline in the UAE, Bass and Steidlmeier (1999) found that leaders’ competencies play a vital role in the success of the airline firm. Sadler-Smith (2004) conducted research on small and medium-sized firms and noted a positive impact of leaders’ intuitive style on both financial and non-financial performance. Cuéllar-Molina et al.’s (2019) study contended that emotional intelligence contributes to high performance practices. Almatrooshi et al. (2016) conducted a systematical review on determinants of firm performance and suggested that leadership competencies (cognitive, emotional, and social intelligence) have positive effects on both employee and organizational performance. Amedu and Dulewicz (2018) investigated three core clusters of leadership competencies (interpersonal, cognitive, and result orientation) and found that these competencies positively affected firm performance.

Nienaber and Svensson (2013) made a conceptual analysis of complexity science and introduced a framework facilitating an understanding of leadership-performance relationship. Hazy and Uhl-Bien (2015) asserted that generative leadership is positively associated with organizational capabilities and later with firms’ performance and adaptability in a changing environment. Administrative leadership was found to help the organization “bring requisite resources, like raw materials, human resources, and financial capital into the organization” (Hazy & Prottas, 2018, p. 328). Therefore, it is hypothesized that:

H4. Leaders’ perceptions of their leadership traits, including core self-evaluation (H4a), narcissism (H4b), need for achievement (H4c), and risk propensity (H4d) are associated with organizational high performance.

H5. Leaders’ perceptions of their leadership competencies, including results-orientation (H5a), cognitive competence (H5b), and interpersonal competence (H5c) are associated with organizational high performance.

H6. Leaders’ perceptions of their complexity leadership, including generative leadership (H6a) and administrative leadership (H6b) are associated with organizational high performance.

2.4.3. Organizational learning and organizational high performance

Organizations should strengthen learning to achieve high performance and supersede their competitors (Garvin, 1993). God et al.’s (2012) meta-analysis of 33 empirical studies on organizational learning and firm performance revealed a positive relationship between learning and both financial and non-financial performance of firms. Yuliansyah et al. (2021) analyzed 157 survey responses from financial service firms and found that organizational learning has a positive influence on organizational performance. Their research findings are consistent with earlier studies (Ur Rehman et al., 2019; Valdez-Juárez et al., 2019; Waqas et al., 2019; Zhao et al., 2009). Zgrzywa-Ziemak and Walecka-Jankowska (2021) carried out an empirical examination of the relationship between organizational learning and sustainable performance of 694 Polish and Danish companies. The findings from their research have shown a positive, statistically significant relationship between the two phenomena. Another recent cross-sectional study of Soomro et al. (2021) also revealed that organizational learning has a positive and significant impact on organizational performance. Therefore, this study hypothesizes that:

H7. Organizational learning has a relationship with organizational high performance.

2.4.4. Organizational learning as a mediator

According to Bryant (2003), leaders create favorable conditions to develop organizational learning, which consequently enhance the performance of organizations. V. J. García-Morales et al.’s (2008) research in 164 pharmaceutical companies in Europe and America revealed leadership influence firm performance through the mediation of organizational learning. Noruzy et al. (2012) also found that leaders foster organizational learning, which in turn strengthen long-term performance of manufacturing firms. In a similar vein, Sayyadi (2019) stated that leaders play a vital role in the creation and management of knowledge within organizations, which are important elements to foster high performance. Other studies also pointed to the notion that organizational learning acts as a mediator in the relationship between leadership and organizational high performance (Mallén et al., 2015; Para-González et al., 2018; Ur Rehman et al., 2019). In the tourism context, studies that examine the relationships between different leadership approaches, organizational learning, and organizational high performance simultaneously have been found lacking. However, the findings discussed previously are important evidence that the impact of leaders on organizational high performance are mediated by organizational learning. Therefore, the following hypotheses are proposed:

H8. Organizational learning mediates the relationship between leadership traits, including core self-evaluation (H8a), narcissism (H8b), need for achievement (H8c), and risk propensity (H8d), and high performance.

H9. Organizational learning mediates the relationship between leadership competencies, including results-orientation (H9a), cognitive competence (H9b), and interpersonal competence (H9c), and high performance.

H10. Organizational learning mediates the relationship between complexity leadership, including generative leadership (H10a) and administrative leadership (H10b), and high performance.

3. Methods

3.1. Survey instruments

As for leadership traits, core self-evaluation was measured based on the Core Self-Evaluation Scale (Henderson & Gardiner, 2019; Judge et al., 2003) and narcissism was measured based on the Narcissistic Personality Inventory (Ames et al., 2006; Raskin & Terry, 1988). Need for achievement and risk propensity measurement items were adopted from Sidek and Zainol (2011). The measurement scale of leadership competencies, including results orientation, cognitive and interpersonal competence was primarily adopted from Amedu (2016) and Amedu and Dulewicz (2018). Generative leadership and administrative leadership behaviors in complexity leadership were measured using the 10-item Complexity Leadership Interaction Modes developed by Hazy and Prottas (2018). Organizational learning was measured by five items adapted from V. García-Morales et al. (2012) and Jiménez-Jiménez and Sanz-Valle (2011). The measurement scale of organizational high performance was adopted from Arsezen-Otamis et al. (2015). In this study, all the constructs are reflective and are measured using a five-point Likert-type scale, ranging from 1—Strongly disagree to 5—Strongly agree. We also included age, tenure, experience in the industry, education, and gender as demographic data of the survey respondents. Before launching the survey, we conducted 10 pre-tests by interviewing five managers of tourism firms and five academics in the fields. The participants in the pre-tests were asked to help validate the questionnaire and evaluate if the survey questions were clearly understood.

3.2. Data collection and analysis

A randomly selected list of 1528 tourism firms in Vietnam, including tourist attractions, restaurants and bars, retailers for tourists, hotels and resorts, tourism event companies, travel agencies, and tourist transportation companies, were contacted via telephone, email, Zalo and Viber app. We delivered the questionnaires via mail and Google Forms to the leaders of these companies since they are reliable key informant and play a vital role in developing company policies, governing operating processes, and allocating resources (Jung et al., 2008). Finally, 638 questionnaires were fully completed and valid, representing a response rate of 42 percent. According to Hair et al. (2012), this sample is a good size for structural equation modeling analysis. Table 1 below illustrates the demographic characteristics of the sample in this study.

Table 1. Demographic characteristics of the sample (N = 638)

		Number	Percentage
Gender	Male	428	67.10
	Female	210	32.90
Age Group	< 31	135	21.20
	31–40	301	47.20
	41–50	153	24.00
	>50	49	7.70
Education level	College	113	17.70
	Bachelor	389	61.00
	Master	134	21.00
	Doctor	2	0.30
Company type	Restaurant/bar	138	21.60
	Tourist attraction	62	9.70
	Hotel/Resort	218	34.20
	Retailing system for tourists	54	8.50
	Transportation company	84	13.20
	Travel agency	45	7.10
	Event company	37	5.80

Smart-PLS software version 3.0 was used to process PLS-SEM for 638 cases. The non-parametric bootstrapping was measured with 1000 replications (Hair et al., 2013).

4. Results

4.1. Measurement model assessment

Composite Reliability (CR) is used to measure the internal consistency reliability. According to Hair et al. (2012), all the constructs with a minimum loading of 0.6 were accepted. In the current study, the factor loadings range from 0.684 to 0.825 (Table 2) so all scales are above 0.6 and each reliability items are appropriated. Table 2 also shows that the CR values of all the constructs range from 0.843 to 0.922. This is accepted with the rules of thumb for model evaluation by Hair et al. (2013) that the internal consistency reliability or composite reliability should be higher than 0.70 in exploratory research, and 0.60 to 0.70 is considered acceptable.

Table 2. Measurement model evaluation

Items	Factor Loadings	Cronbach’s Alpha	CR	(AVE)
Organizational High Performance (OHP)		0.848	0.884	0.523
OHP1 The profitability of the firm is satisfactory.	0.761
OHP2 The sales of the firm is satisfactory.	0.697
OHP3 The customers are satisfied with the firm.	0.713
OHP5 Relative to the similar firms, market share of the firm is good.	0.713
OHP7 We get the worth of our money, labor and time we spent for the firm.	0.739
OHP8 Our firm can find credits easily when needed.	0.721
Organizational Learning (OL)		0.783	0.852	0.535
OL1 The organization has acquired and shared much new and relevant knowledge that provided competitive advantage.	0.754
OL2 The organization’s members have acquired some critical capacities and skills that provided competitive advantage.	0.761
OL3 Organizational improvements have been influenced fundamentally by new knowledge entering the organization.	0.726
OL4 The organization is a learning organization.	0.701
OL5 Databases are always kept up-to-date.	0.714
Core Self-Evaluation (CSE)		0.768	0.843	0.518
CSE1 I am confident I get the success I deserve in life.	0.731
CSE5 I complete tasks successfully.	0.717
CSE7 Overall, I am satisfied with myself.	0.742
CSE9 I determine what will happen in my life.	0.687
CSE11 I am capable of coping with most of my problems.	0.721
Narcissism (NAR)		0.906	0.922	0.541
NAR1 I know that I am good because everybody keeps telling me so.	0.703
NAR2 I think I am a special person.	0.727
NAR3 I like having authority over people.	0.723
NAR4 I find it easy to manipulate people.	0.760
NAR5 I am apt to show off if I get the chance.	0.684
NAR6 I really like to be the center of attention.	0.755
NAR7 People always seem to recognize my authority.	0.753
NAR8 I can make anybody believe anything I want them to.	0.731
NAR9 I am more capable than other people.	0.761
NAR10 I am an extraordinary person.	0.758
Need for achievement (NFA)		0.796	0.860	0.551
NFA1 I do my best work when my job assignments are fairly difficult.	0.714
NFA3 I take moderate risks and stick my neck out to get ahead at work.	0.738
NFA5 At work, I set high standards for myself and others.	0.780
NFA7 I am highly motivated to succeed.	0.725
NFA9 I turn plans into action at work.	0.753
Risk propensity (RPR)		0.857	0.893	0.582
RPR1 With respect to my company, I believe that higher financial risks are worth taking for higher rewards.	0.761
RPR2 I accept occasional new product failures as being normal.	0.761
RPR3 In term of my business, I like to take big financial risks.	0.771
RPR4 I encourage the development of innovative marketing strategies, knowing well that some will fail.	0.728
RPR5 With respect to my business, I do not like to “play it safe”.	0.785
RPR6 I like to implement plans even though it is no evidence that it will work.	0.771
Cognitive Competence (COG)		0.892	0.912	0.537
COG1 I can produce a clear and consistent picture of the long-term future state and character of the organization in relation to its environment.	0.712
COG2 I am aware of the organization’s strengths and weaknesses and of the impact of the board’s decisions upon them.	0.738
COG3 I am aware of the stakeholder, market, technological and regulatory factors which determine the organization’s opportunities and threats.	0.704
COG4 I generate and recognize imaginative solutions and innovations.	0.748
COG5 I make sensible decisions or recommendations based on reasonable assumptions and factual information.	0.751
COG6 I show a readiness to take decisions, make judgments, take action and make commitments.	0.697
COG7 I identify problems, transforms and relates information from different sources and identifies possible or actual causes.	0.750
COG8 I probe the facts, challenge assumptions, identify the disadvantages of proposals, provide counter arguments and ensure discussions are penetrating.	0.779
COG9 I rise above the immediate problem or situation and see the wider issues and implications; relate disparate facts through an ability to perceive all relevant relationships.	0.713
Interpersonal Competence (INT)		0.860	0.899	0.641
INT1 I make a strong positive impression on first meeting, have authority and credibility, and establish rapport quickly.	0.808
INT2 I adopt a flexible (but not compliant) style when interacting with others.	0.798
INT3 I show an understanding of the feelings and needs of others, and a willingness to provide personal support or to take other actions as appropriate.	0.825
INT4 I inspire others to achieve goals by ensuring a clear understanding of what needs to be achieved; and by showing commitment, enthusiasm and support.	0.793
INT5 I persuade others to give their agreement and commitment. In face of conflict, I use personal influence to achieve compromise and agreement.	0.778
Results-Oriented Competence (ROR)		0.896	0.916	0.547
ROR1 I am alert and responsive to the need for change. I encourage new initiatives and the implementation of new policies, structures, and practices.	0.698
ROR2 I am assertive and forceful when dealing with others. I am ready to take charge of a situation.	0.719
ROR3 I show conspicuous levels of energy, vitality and output.	0.747
ROR5 I set high goals or standards of performance for self and for others, and am dissatisfied with average performance.	0.702
ROR6 I stay with a position or plan of action until the desired objective is achieved or is no longer reasonably attainable, irrespective of setbacks and obstacles.	0.718
ROR7 I identify those opportunities which will increase the organization’s business advantage; select and exploit those activities which will result in the largest returns.	0.776
ROR8 I allocate decision-making and other tasks appropriate subordinates to achieve desired goals. I organize all other resources efficiently and effectively.	0.795
ROR9 I effectively organize the activities of colleagues and subordinates to achieve desired goals. I organize all other resources efficiently and effectively.	0.772
ROR10 I establish priorities and take account of all relevant contingencies.	0.724
Administrative Leadership (ALM)		0.757	0.846	0.579
ALM2 I set objective metrics of success or failure.	0.733
ALM3 I quiet voices that distract from purpose.	0.801
ALM4 I ask people to invest more time and energy.	0.781
ALM5 I establish specific targets and deliverables.	0.726
Generative Leadership (GLM)		0.780	0.858	0.603
GLM1 I support differences of opinion.	0.762
GLM2 I provide resources and time to try new things.	0.819
GLM3 I encourage learning visits to other organizations.	0.773
GLM4 I encourage new approaches.	0.749

CR: Composite Reliability; AVE: Average Variance Extracted

We evaluate the validity of items by testing convergent validity through the average variance extracted (AVE) to see if this value is higher than 0.50 or not (Hair et al., 2011). The results of AVE values show in Table 2 range from 0.518 to 0.641, which are higher than the indexes suggesting by Hair et al. (2011). Therefore, the convergent validity is confirmed.

As for discriminant validity, Hair et al. (2011) suggested that “an indicator’s loadings should be higher than all of its cross loadings”. According to Fornell and Larcker (1981), “the square root of AVE of each latent variable should be greater than the correlations among the latent variables”, and it can be used to establish discriminant validity. For example, the latent variable INT’s AVE is 0.641 so the square root of AVE of INT became 0.801. This value was greater than the correlations among the latent variables in the Colum of INT (NAR: 0.532, NFA: 0.571, OHP: 0.565, etc.). Furthermore, the square root of AVE of INT also bigger than the correlation values in the row of INT (GLM: 0.575, CSE: 0.606, COG: 0.735). Other the latent variables were well established the discriminant validity (Table 3).

Table 3. Discriminant validity (Formell and Lacker’s criterion)

	Mean	SD.	CSE	NAR	NFA	RPR	COG	INT	ROR	ALM	GLM	OL	OHP
CSE	3.770	1.056	0.720
NAR	3.821	1.046	0.679	0.736
NFA	4.051	0.905	0.672	0.587	0.742
RPR	3.918	1.045	0.535	0.700	0.585	0.763
COG	4.260	0.751	0.698	0.534	0.662	0.488	0.733
INT	4.271	0.780	0.606	0.532	0.571	0.457	0.735	0.801
ROR	4.321	0.737	0.681	0.519	0.660	0.430	0.832	0.758	0.740
ALM	4.343	0.721	0.557	0.460	0.556	0.375	0.684	0.625	0.717	0.761
GLM	4.225	0.785	0.524	0.381	0.530	0.335	0.708	0.575	0.693	0.631	0.776
OL	4.267	0.746	0.573	0.489	0.616	0.462	0.710	0.617	0.682	0.620	0.625	0.732
OHP	4.211	0.831	0.629	0.534	0.542	0.442	0.601	0.565	0.639	0.541	0.449	0.612	0.723

Bold values represent the square root of AVEs

According to Henseler et al. (2015), the heterotrait-monotrait ratio of the correlations (HTMT) is considered better than Fornell-Larcker criterion. Table 4 below presents the HTMT ratio for discriminant validity in this study. The choice of the HTMT threshold values, either a conservative benchmark of 0.85, a more liberal cut-off value of 0.9, or even higher at 0.95 (Franke & Sarstedt, 2019; Henseler et al., 2015; Voorhees et al., 2016) should “be made against the background of how conservative the researcher wants to be in assessing discriminant validity and how confident (s)he is regarding the uniqueness of the constructs” (Roemer et al., 2021, p. 2640). In this study, all HTMT ratio values were below the 0.9 threshold, except for the HTMT ratio of ROR and COR (HTMT ratio value = 0.931). Although this ratio was a little bit higher than the 0.9 threshold, it can be acceptable.

Table 4. Discriminant validity-heterotrait-monotrait ratio

	OHP	OL	CSE	NAR	NFA	RPR	COG	INT	ROR	ALM	GLM
OHP
OL	0.740
CSE	0.774	0.732
NAR	0.595	0.568	0.806
NFA	0.654	0.775	0.862	0.683
RPR	0.509	0.559	0.658	0.798	0.701
COG	0.683	0.847	0.843	0.586	0.783	0.551
INT	0.657	0.751	0.745	0.596	0.688	0.526	0.837
ROR	0.724	0.813	0.818	0.567	0.780	0.484	0.931	0.863
ALM	0.667	0.804	0.721	0.539	0.712	0.452	0.830	0.771	0.871
GLM	0.541	0.797	0.669	0.443	0.667	0.401	0.846	0.698	0.828	0.825

4.2. Structural model assessment

We use variance inflation factor (VIF) to check the existence of multicollinearity. According to Hair et al. (2011), the acceptable criterion for each indicator of VIF value should be smaller than 5. The results of the collinearity statistics in our study show that the VIF values range from 1.390 to 4.633, in which outer VIF values are from 1.390 to 2.505 and inner VIF values are from 2.201 to 4.633. This indicates that multicollinearity is not a problem in our data.

The predictive power of structural model is examined, and the measurement model results are satisfactory. In this study, the coefficient of determination (R2) is 0.532 for OHP. This indicated that the nine latent variables (CSE, NAR, NFA, RPR, ROR, COG, INT, GLM, ALM) moderately explain 53.2% of the variance in OHP. Besides, the coefficient of determination (R2) is 0.589 for OL, which indicates that 9 latent variables (CSE, NAR, NFA, RPR, ROR, COG, INT, GLM, ALM) moderately explain 58.9% of the variance in OL. According to Hair et al. (2011), if the Stone-Gesser’s values (Q2) is bigger than zero, the exogenous constructs are predictive relevance for the endogenous construct. In this study, Q2 value is 0.269 for the average cross-validated redundancy of OHP, and 0.305 for OL.

In this study, we use bootstrapping procedure with 1000 replications at the 97.5% confidence intervals. The critical t-values for a two-tailed test are larger than 1.96 and this value is acceptable (significance level = 5%, p < 0.05) (Hair et al., 2013). Table 5 depicts the results of structural model.

Table 5. Path coefficients and hypothesis testing

Hypotheses	Relationship	Path coefficients (β)	T-Values	P- Values	Decision
H1a	CSE → OL	−0.012	0.222	0.825	Rejected
H1b	NAR → OL	0.023	0.588	0.557	Rejected
H1c	NFA → OL	0.153	3.248	0.001	Supported
H1d	RPR → OL	0.072	1.959	0.050	Supported
H2a	ROR → OL	0.080	1.195	0.232	Rejected
H2b	COG → OL	0.239	3.891	0.000	Supported
H2c	INT → OL	0.082	1.724	0.085	Rejected
H3a	GLM → OL	0.164	2.913	0.004	Supported
H3b	ALM → OL	0.128	2.576	0.010	Supported
H4a	CSE → OHP	0.245	4.751	0.000	Supported
H4b	NAR → OHP	0.100	1.982	0.048	Supported
H4c	NFA → OHP	−0.011	0.178	0.858	Rejected
H4d	RPR → OHP	0.019	0.392	0.695	Rejected
H5a	ROR → OHP	0.252	3.439	0.001	Supported
H5b	COG → OHP	−0.027	0.398	0.691	Rejected
H5c	INT → OHP	0.043	0.844	0.399	Rejected
H6a	GLM → OHP	−0.112	2.250	0.025	Supported
H6b	ALM → OHP	0.075	1.461	0.144	Rejected
H7	OL → OHP	0.267	3.164	0.002	Supported
H8a	CSE → OL → OHP	−0.003	0.211	0.833	Rejected
H8b	NAR → OL → OHP	0.006	0.575	0.565	Rejected
H8c	NFA → OL → OHP	0.041	2.234	0.026	Supported
H8d	RPR → OL → OHP	0.019	1.721	0.086	Rejected
H9a	ROR → OL → OHP	0.021	1.105	0.269	Rejected
H9b	COG → OL → OHP	0.064	2.327	0.020	Supported
H9c	INT → OL → OHP	0.022	1.480	0.139	Rejected
H10a	GLM → OL → OHP	0.044	2.409	0.016	Supported
H10b	ALM → OL → OHP	0.034	1.720	0.086	Rejected

Hypothesis 1 is tested and the results show that two factors NFA (β = 0.153, T = 3.248, P = 0.001 < 0.05) and RPR (β = 0.072, T = 1.959, P = 0.050 < 0.05) are positively associated with OL at 99% and 95% confidence level. Therefore, hypotheses H1c and H1d are supported. Two factors CSE and NAR are not positively associated with OL and have no significant differences; therefore, hypothesis H1a and H1b are rejected. Hypothesis 2 is tested and the results show that only COG (β = 0.239, T = 3.891, P = 0.000 < 0.05) is positively associated with OL at 99% and confidence level. Therefore, hypothesis H2b is supported. Two factors ROR and INT are not positively associated with OL and have no significant statistics; therefore, hypotheses H2a and H2c are rejected. Hypothesis 3 is tested and the results show that all the path coefficients are statistically significant. GLM (β = 0.164, T = 2.913, P = 0.004 < 0.05) and ALM (β = 0.128, T = 2.576, P = 0.010 < 0.05) are positively associated with OL at 99% confidence level. Hypotheses H3a and H3b are fully supported.

Hypothesis 4 is tested and the results show that only CSE (β = 0.245, T = 4.751, P = 0.000 < 0.05) and NAR (β = 0.100, T = 1.982, P = 0.048 < 0.05) are positively associated with OHP at 95% and 99% confidence level. Therefore, hypotheses H4a and H4b are supported. Two factors NFA and RPR are not positively associated with OHP and have no significant statistics; therefore, hypotheses H4c and H4d are rejected. Hypothesis 5 is tested and the results show that only ROR (β = 0.252, T = 3.439, P = 0.001 < 0.05) is positively associated with OHP at 99% confidence level. Therefore, hypothesis H5a is supported. Two factors COG and INT are not positively associated with OHP and have no significant statistics; therefore, hypotheses H5b and H5c are rejected. Hypothesis 6 is tested and the results show that only GLM (β = −0.112, T = 2.250, P = 0.025 < 0.05) is negatively associated with OHP at 97.5% confidence level. Therefore, hypothesis H6a is supported. The factor ALM is not significantly associated with OHP; therefore, hypothesis H6b is rejected.

Hypothesis 7 is tested and the results show that the path coefficient is statistically significant. OL (β = 0.267, T = 3.164, P = 0.002 < 0.05) is positively associated with OHP at 99% confidence level. Therefore, hypothesis H7 is fully supported.

Hypothesis 8 is tested and the results show that OL mediates the relationship between NFA and OHP (β = 0.041, T = 2.234, P = 0.026 < 0.05). Therefore, hypothesis H8c is supported. There is no statistically significant indirect relationship between CSE, NAR, RPR and OHP through the mediation of OL. Therefore, hypotheses H8a, H8b, and H8c are rejected. Hypothesis 9 is tested and the results show that OL mediates the relationship between COG and OHP (β = 0.064, T = 2.327, P = 0.020 < 0.05). Therefore, hypothesis H9b is supported. There is no statistically significant indirect relationship between ROR, INT and OHP through the mediation of OL. Therefore, hypotheses H9a and H9c are rejected. Hypothesis 10 is tested and the results show that OL mediates the relationship between GLM and OHP (β = 0.044, T = 2.409, P = 0.016 < 0.05). Therefore, hypothesis H10a is supported. There is no statistically significant indirect relationship between ALM and OHP through the mediation of OL. Therefore, hypothesis H10b is rejected.

The results for the direct effects of the structural model are shown in Figure 1.

Figure 1. PLS-SEM results.

5. Discussion

The examination of the 10 hypotheses has brought forward several key issues. First, the results partially confirm the significant effects of different leadership traits, competencies, and behaviors on organizational learning. Out of the four leadership traits and four competencies, only need for achievement (H1c), risk propensity (H1d), and cognitive competence (H2b) exert significant positive effects on organizational learning; therefore, offering further evidence for previous studies (Jain & Jeppe Jeppesen, 2013; Lowell, 1952; Onağ et al., 2014). On the contrary, core self-evaluation (H1a), narcissism (H1b), results orientation (H2a), and interpersonal competence (H2c) do not have significant direct effects on organizational learning. These results contrasting the conclusions drawn by earlier research which supported the presumed relationships (Bettis-Outland & Guillory, 2018; Siswanti et al., 2018; Zhang et al., 2018). One plausible reason could be that leaders who score high in these domains tend to be overconfident in every dimension of their work and just focus on building relationships, which, in turn, leads them to satisfy with the status quo and underestimate learning initiatives. Besides, although earlier studies have tangentially implied that generative and administrative leadership relates to knowledge acquisition (Hazy & Prottas, 2018; Džinić, 2015), our study is an early attempt to understand how these leadership behaviors help organizations achieve better organizational learning using the lens of the complexity leadership theory (H3a, H3b). The explanation for this finding can be due to strong Confucianism culture in Vietnam, which encourages learning and sees it as a tool to help people explore their instinctive potentials and achieve higher performance (Viengkham et al., 2018).

Second, the results offer insightful discussion on how the leaders’ traits, competencies, and behaviors affect organizational high performance. The results of this study support our contention that leaders’ core self-evaluation (H4a), narcissism (H4b), and results-orientation (H5a) are important antecedents to firms’ superior performance. This finding is consistent with earlier literature in the fields (Simsek et al., 2010; Kim, 2018). Some hypotheses (H4c, H4d, H5b and H5c) are not supported by the data although earlier works have helped in proposing these associations (Almatrooshi et al., 2016; Cain & Mckeon, 2012; Lee & Tsang, 2001). It appears that within the context of this research leaders who have high levels of need for achievement, risk propensity, cognitive competence, and interpersonal skills do not contribute to the performance of their organizations. This, in turn, provides new insights toward the extension of existing theoretical relationships and adds to the current debates from similarly published studies. Furthermore, previous studies have identified generative and administrative leadership as the behaviors related to firm performance (Hazy & Prottas, 2018; Hazy & Uhl-Bien, 2015; Nienaber & Svensson, 2013). In our study, the results are opposite to what earlier studies have discussed since generative leadership (H6a) was found to negatively relate to organizational performance and administrative leadership (H6b) was found to have no connection with organizational high performance. It seems that leaders within the context of this research rely on much on their personalities and competencies rather than their behaviors to lead their firms towards superior performance. Besides, tourism leaders perceived that the application of new ideas and forgiveness of mistakes could create problems in the performance of their organizations. This finding therefore reflects the contemporary nature of tourism sector, which requires accuracy and consistency in daily operation and delivery of services (Solakis et al., 2022). These findings open doors for future researchers to investigate how such leadership behaviors could be applied to foster high performance and calls for using complexity leadership theory to better explain for leadership effectiveness and organizational outcomes.

Third, although the leadership-related findings of this research are consistent with earlier studies, our work extends previous literature by investigating the role of organizational learning. The findings show a significant relationship between the organizational learning and the organizational high performance, which is consistent with previous studies (Yuliansyah et al., 2021; Soomro et al., 2021; God et al., 2012). As evidenced by the results, organizational learning acts as a prerequisite for organizational high performance of tourism firms in Vietnam, which contributes to tourism literature and supports the contention that these Western-developed phenomena can be applied in the context of developing economies in Asia.

Finally, results for mediating role of organizational learning represent that this factor is believed to mediate the impact need for achievement (H8c), cognitive competence (H9b), and generative leadership (H10a) have on organizational high performance. The findings confirm that the resource-based view theory and knowledge-based view concept can be used to examine and validate the relationship between these domains in the tourism industry. More precisely, this study concurs with earlier works proposing that organizational learning is a crucial mediator in firm’s superior performance (V. J. García-Morales et al., 2008; Sayyadi, 2019). The results also extend the previous findings by reporting how organizational learning mediates the relationship between leaders’ traits, competencies, behaviors, and firm performance, in the context of tourism firms in Vietnam—a developing country in Asia. Furthermore, this study provides one of the first mediation investigations of the theory that organizational learning is important in firm’s high performance to derive the best results from leaders with need for achievement, cognitive competence, and generative leadership behaviors.

6. Conclusion

This study aims to examine how leadership, organizational learning, and organizational high performance affect one another. The research findings revealed positive relationships between leadership factors (need for achievement, risk propensity, cognitive competence, generative behavior, and administrative behavior) and organizational learning. Besides, core self-evaluation, narcissism, result-oriented competence, and generative behavior of leaders have been found to affect organizational high performance. The study also proved that organizational learning is still an effective predictor of firm performance. Moreover, the mediating role of organizational learning found in this study enriches the content of resource-based view theory and knowledge-based view concept by revealing one of the mechanisms through which leadership affects organizational high performance. In addition, this study provides some culture-specific insights about how the findings reflect the contemporary nature of tourism sector and strong Confucianism culture in Vietnam.

6.1. Theoretical implications

This study has several theoretical contributions. First, existing studies on leadership and organizational outcomes seem to fit the metaphor of “the blind men and the elephant” with each research merely touching on a single leadership theory. Our study extends leadership literature by combining traits, competencies, and complexity leadership theories and demonstrating that leaders’ characteristics and behaviors not only influence organizational learning, but also organizational high performance. Besides, despite decades of research and thousands of publications on leadership, the field has not yet arrived at a definitive knowledge about a comprehensive leadership profile of leaders in organizations. We hope that the findings in this study contribute another small piece to this large puzzle and provide a glimpse into the “black box” of leadership effectiveness.

Second, by integrating the concepts of leadership, organizational learning, and organizational high performance, this study develops an overarching and unique conceptual indicating the mediating role of organizational learning. In this regard, previous studies were looking at the relationship between leadership and organizational learning, organizational learning and organizational high performance, leadership and organizational high performance. Contrariwise, this study presents a combined and more comprehensive theoretical framework which examines how each variable affects one another.

Third, the current study contributes to the existent knowledge through its highlights on the role of organizational learning in stimulating organizational high performance and in positively mediating the relationship between leadership and organizational high performance. Furthermore, the present study presents an analysis of these domains in the context of tourism firms in Vietnam. Previous literature on the same concepts has focused on Western countries and well-developed knowledge economies (Amedu & Dulewicz, 2018; Matošková et al., 2018; Sayyadi, 2019; Soomro et al., 2021; Zgrzywa-Ziemak & Walecka-Jankowska, 2021), and thus, neglected developing countries and transitioning economies such as Vietnam. The findings into how tourism firms in Vietnam foster high performance through leadership and organizational learning represent a first step to establishing comparisons between regions and industries, which are potential research areas in the future.

6.2. Managerial implications

The current study makes several practical contributions. First, the results from this study can be used by practitioners, business owners, and human resources managers engaged in the field of recruitment and leadership development. In particular, the findings revealed two potential clusters of personality traits and competencies including: (1) need for achievement, risk propensity, and cognitive competence that are significantly related to organizational learning, and (2) core self-evaluation, narcissism, and result-orientation that are significantly related to organizational high performance. These are personalities and competencies that leaders bring with them to work so that they can foster organizational learning and superior firm performance. Human resources managers can use these clusters of personality traits and competencies as a reference in selecting and training senior executives or potential leaders. The description of these traits can also be used in a survey as a pre-hiring or preliminary assessment to identify the presence of effective leadership personalities among potential applicants. Furthermore, human resource department in tourism firms should develop comprehensive training programs for their leaders to acquire and develop a skillset including cognitive and results orientation competences.

Second, the results suggest that both generative and administrative leadership behaviors are important for leaders to foster organizational learning. Ideally, leaders in tourism firms should be able to demonstrate both leadership behaviors since such behavioral flexibility is essential for leadership effectiveness. In tourism firms, if a leader is inclined toward only generative leadership behavior, another leader should focus on administrative leadership behavior to ensure effective implementation of organizational learning. In this regard, business owners and human resource department should nurture a working environment that values and rewards such behaviors. Added to this, tourism firms can train their leaders and managerial employees and encouraging them to exhibit complexity leadership behaviors through development programs combined with mentoring practices and a culture that reinforces such behaviors. For example, administrative leaders are trained to set specific goals, evaluation criteria, and expected deliverables at work. They also need to learn some influencing tactics that can be used in empowering employees to invest more time and energy to work. On the other hand, generative leaders will support and provide necessary resources for field trips and experiential learning programs, as well as the implementation of innovative ideas at work. Moreover, further training programs could be provided to help leaders be aware of the external environment and flexibly adjust their leadership behaviors (generative, administrative, or the combination of the two behaviors) to better fit changing contingencies and the prevailing environment faced by their organizations such as the COVID-19 pandemic.

Third, organizations cannot solely rely on leaders to foster high performance; therefore, other factors such as organizational learning must be in place. Business owners can work with human resource department to develop an organizational learning department within their firms. This department is responsible for collecting, assembling, and distributing employees’ suggestions and new approaches on work performance so that these ideas are heard and considered for implementation continuously. Tourism firms can also assign this department to identify and implement necessary techniques and facilities to acquire and transfer knowledge (e.g., field trips, workshops, conferences, best practices sharing sessions, etc.) among different fields of activities. Moreover, the organizational learning department needs to strengthen communication and collaboration between departments in the organization and between the organization and its external partners so that they are integrated towards learning. The outcomes of organizational learning, for example, internal knowledge resources and databases, should be stored and kept up to date for future use. Added to this, in the current turbulent and uncertain environment during COVID-19 pandemic, business owners and managerial executives must also identify optimal strategies to successfully cultivate a favorable learning environment and foster a shared culture between organizational members. For example, leaders in tourism firms should focus efforts on initiatives that can result in the creation new knowledge (e.g., research and development activities, creative solutions competition, annual innovative ideas rewards) and in activities dedicated to disseminating and utilizing knowledge (e.g., application of new technologies in learning, group projects, meetings, etc.). Contents and criteria related to knowledge creation, sharing, application and storage should be included in the annual review and annual performance appraisal as act as a requirement for recognitions, rewards, and promotions.

6.3. Limitations and areas for future research

This study has several limitations. The first limitation is the use of a subjective measure for organizational high performance. Though this approach is not ideal, this is one of the most pragmatic constraints in doing research in Vietnam now due to the lack of valid and reliable sources of performance data for the variety of firms in our sample. Added to this, the leaders participating in this study might exhibit a self-serving bias and thus reducing the variance in performance across the tourism organizations. Future studies are encouraged to include other performance indicators to evaluate the leadership approaches and influences of leaders, for example, assessments from employees, customers, and the community. Finally, our research was conducted in a context where leaders seem to have great latitude for discretion due to cultural aspects. Future studies could explore the moderating or mediating effects of culture on the relationship between leadership and organizational outcomes.

Correction

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number NCUD.05-2019.70.

Notes on contributors

Ngoc Khuong Mai

Ngoc Khuong Mai is a lecturer and researcher of School of Business of the International University, Vietnam National University, Ho Chi Minh City, Vietnam. He has bachelor’s degree in Tourism and Hospitality Management, Master of Science degree in Leisure, Tourism and Environment at Wageningen University, the Netherlands, and PhD degree in Development Management at School of Public Administration of the National Institute of Development Administration (NIDA), Bangkok, Thailand.

Thanh Tung Do

Thanh Tung Do is a PhD Candidate at School of Business of the International University, Vietnam National University, Ho Chi Minh City, Vietnam (IU-VNU). He has bachelor’s degree in International Business at IU-VNU, Master of Science degree in Leadership at Northeastern University, Boston, USA. His research interests include leadership, organizational learning, and high performance organization.