Learning from Failure: Building Resilience in Small- and Medium-Sized Tourism Enterprises, the Role of Servant Leadership and Transparent Communication

Abstract

Understanding how small- and medium-sized enterprises develop and foster resilience in their employees is critical to better adapt to and recover from challenges. Yet, how such a process is conducted is not well-understood in literature. Integrating the literature from the social exchange theory and the disaster resilience framework, this research examines the effects of servant leadership (SL) and transparent communication (TC) on employees’ capacity for resilience (learning from failure, hardiness, and optimism) and their adaptive performance during/post the COVID-19 crisis. A total of 880 employees in restaurants and travel agencies were surveyed. The results reveal that the effects of SL and TC on employees’ adaptive performance was fully mediated by employees’ capacity for resilience, specifically learning from failure.

1. Introduction

Within challenging times, resilient organizations adopt strategies and behaviors that enable them to face change and bounce back from adversities [1]. Organizations can achieve resilience if they have the suitable resources that enable their workforce to persevere and demonstrate well-adjusted behaviors [2,3]. Research suggests organizational resilience to be operationalized as a higher-level construct developed from various individual and organizational lower-order factors [4,5]. Particularly, a directional relationship has been proposed between resources/capabilities in general (economic, procedural, and/or social), employees’ capacity for resilience, and organizational demonstration of resilience [6]. Identifying such capabilities and their role in the resilience process is significant to scholars/practitioners tasked with modifying existing operations or developing new ones necessary to persist through hardships [7]. Yet, research examining the process perspective of organizational resilience is very limited [8], especially in the small- and medium-sized enterprises (SMEs) context, usually with limited access to critical resources [9], leaving a gap in the literature. Furthermore, this literature rarely explains how resilient individuals manifest themselves when disaster hits and how the resilience process occurs [4].

According to Chhatwani, Mishra, Varma, and Rai [10], the resiliency of small firms is very much reliant on the psychological resilience of employees. Resilient employees within/post challenging adversities display fighting spirit to influence unfavorable circumstances, cleverly use their experiences and skills to find solutions and help their organization to accurately evaluate the situation and fine-tune performance [5]. Although negative emotions addressed after feeling of failure in an organization/project can impede recovery [11], employees’ capacity for resilience (i.e., learning from failure, hardiness, and optimism) may rescue their jobs and obtain the resiliency for their organization [6]. Previous research tends to focus on the role of employees’ resilience in an organization’s survival, but its antecedents have not been fully explored. Besides individual efforts, social organizational factors such as positive supportive organizational policies and initiatives boost employees’ resilience [12,13].

Adaptive performance is an indicator of the resiliency of an organization [14] and is related to the ability to adjust ones’ behaviors, actions, or resources to address the changeable demands of the workplace environment [15]. Creatively solving problems, coping with uncertainties, and demonstrating cultural adaptability are some of the practices that an employee with high adaptive performance can carry out [16]. Supportive leadership behaviors and organizational climate have the potential to strongly influence adaptive performance [14,17]; however, evidence is scarce in the literature, specifically in the hospitality sector [14].

There are different ideas about the role of servant leadership (SL) in achieving organizational resilience. According to Yu, Wen, Smith, and Stokes [18], SL, which refers to leaders’ ability to work for the goals of their organization through satisfying the interests of their followers [19,20], may help establishing a positive climate that would lead to the resiliency of organizations. Followers are usually inspired by their servant leaders and therefore move away from self-serving to other-serving and engage in supportive work for their organization [21]. On the contrary, Andersen [22] states that the characteristics of a servant leader, such as prioritizing followers’ concerns and organizational concerns are secondary, might not be consistent with an organizational goal of adapting to challenges, specifically in the short-term. Similarly, Canavesi and Minelli [23] argue that SL may not be appropriate for organizations with fast-changing environments as decisions need to be made quickly with a fast top-down approach. Despite different perceptions of the impact of servant leaders on the resiliency of organizations, no research was found examining such a relationship [24].

Social network/connectedness is one of the most frequently suggested social capital in literature to influence organizational resilience [25,26,27]. It appears that positive internal communication such as transparent communication (TC) helps employees to be less anxious and frustrated, build trust, correctly evaluate the work situation, fine-tune their performance, and improve resilience. Communication and information sharing are exemplified in various successful resilient hospitality organizations in the COVID-19 crisis [28,29]; however, the research empirically investigating how TC influences the organizational resilience process can scarcely be found.

The aim of the following research is to examine the possible impact of SL and TC on the degree to which employees represent resilient behaviors (i.e., learning from failure, hardiness, and optimism). Second, the study tests whether and how employees’ resilience mediates/moderates the effect of SL and TC on the adaptive performance. Built on the social exchange theory (SET) [30], and the Disaster Resilience Framework for Hotels (DRFHs) [25], this study proposes a research model to investigate such relationships using data collected from SMEs in the tourism and hospitality industry (i.e., travel agencies and restaurants) post the COVID-19 crisis.

Our study addresses the need for an empirical investigation of the dynamic multiple dimension model of resilience in organizations [8,31], specifically in SMEs [10]. More importantly, it incorporates organizational capitals (i.e., SL and TC), psychological traits (i.e., employees’ resilience), and consequences of resilient attitude and behavior (i.e., adaptive performance), providing further support to the growing literature on the dynamic process of resilience. Furthermore, no empirical study has investigated the influence of SL and TC on an organizational resilience outcome such as adaptive performance simultaneously so far, particularly in a fast-changing context such as tourism and hospitality industry.

2. Theoretical Basis and Hypothesis

2.1. The DRFH and Social Exchange Theory

The DRFH proposes that hospitality businesses can reduce the risks of disasters if they possess a set of capitals/resources (social, human, natural, physical, and/or cultural) that enable fast recovery actions [25]. Limited available capitals can hinder preparation strategies and therefore require investment [27] According to DRFH, leadership and communication are considered significant contextual social capitals that promote and boost the capability of employees to cope proactively with adversities [25]. Employees’ capacity to adapt to new situations and proactively provide solutions is considered itself a human capital needed for resilience [25,26] This underscores the importance of conceptualizing organizational resilience as a dynamic process [31,32] in terms of inputs, functions, and outputs rather than as stable resources/capitals responsible for the organization’s ability to respond to adversity. Framing organizational resilience as a function of individual–organization exchanges would help in ensuring resilience preparedness for future turbulent events.

Social exchange theory (SET) provides an explanation for the individual–organization capital exchange relationship suggested to contribute to organizations’ resilience. SET posits that when an individual receives a service or resources from others, a feeling of a debt of gratitude to the partner emerges from that exchange [33]. To remove that feeling, he/she reciprocates. If the actors are satisfied with their returns, this interaction continues [34]. Research suggests that individuals who gain highly valued financial and/or socio-emotional resources through their work may choose to positively respond in return by devoting more of their skills, experience, and knowledge to their organization [33,35].

2.2. Servant Leadership (a Social Capital)

According to Greenleaf [19], servant leaders focus on answering and fulfilling the essentials, interests, and goals of the followers over self-serving. They usually have a set of characteristics that are conducive to such an approach (e.g., altruism, emotional intelligence, high-mindedness, prosocial behavior, and core self-assessment) [36]. Therefore, they guide their followers in the work environment through persuasion and conviction rather than direct power [20,37]. Such qualitative leader–employee relationship aims at the well-being and personal growth of the followers and the ongoing development and performance expectations of the organization [20,38]. These followers in turn perceive their servant leaders as exemplars and participate in effective behaviors/practices in the workplace [39]. A different interpretation of SL suggests that the protective behavior of servant leaders towards their followers may discourage them from proactively respond to crucial problems within their organization [23], affecting the overall organizational effectiveness [22]. In this research, we assess whether SL has potential to provide a suitable climate for resilience development in SMEs.

2.3. Transparent Communication (a Social Capital)

Regarding TC, it is considered a process that creates trust, credibility, and loyalty of stakeholders (i.e., employees) [40]. This process consists of three coordinated elements: disseminating deliberate substantial information in a way that enhances employees’ understanding [41]; encouraging employees to identify and acquire the information they seek [42]; and providing well-balanced and timely feedback of the activities and policies of an organization whether positive or negative [40]. According to Barret [43] and Neill et al. [44], internal TC can motivate employees’ support for organizational change. It accurately educates employees in the current organizational situation and what that means to them, aligns employees behind the organizational performance goals, encourages proactive performance, clarifies misunderstanding, and limits rumors [43]. These outcomes probably make employees believe in their control over the information needed for problem-solving [45] and motivate them to engage in positive practices to support their organization [44]. Therefore, TC is suggested to be a trigger for the resilience process in organizations, specifically when adversities occur.

2.4. Resilience of the Employees (a Human Capital)

Research argues that learning from failure [46,47], hardiness, and optimism [32], compose a fruitful construct of individual resilience. Learning from failure reflects employees’ capability to employ knowledge and skills gained from a failed experience (task/project/business) in real situations, fine-tune behavioral and cognitive practices, and find solutions to possible similar failures in the future [48]. Hardiness reflects an individual’s ability to control oneself when facing challenges and to fight hard to influence unfavorable circumstances [49]. Optimism, as the third dimension of resilience, reflects employees’ ability to have a positive outlook within difficult events, accurately evaluate the situation, and use error as a source of information to correct performance [31]. According to Kuntz et al. [13] and Nyaupane, et al. [50], in the organizational setting, resilient attitudes and behaviors of employees can be developed and sustained when a supporting system is in place. Prayag, et al. [51] reported that individual resilience solely cannot lead to organizational resilience unless appropriate managerial interventions are made.

2.5. Adaptive Performance (an Indicator of Business Resilience)

Adaptive performance, according to Pulakos et al. [52], involves practices such as handling crisis events, coping with uncertainties, and being adaptable whether interpersonally, culturally, or physically. It may occur at task, team, and/or organization level [53]. These levels determine the extent of the work role affected by the change and how individuals cope with and respond to it. For instance, changing activities to suit alternative processes reflects adaptivity at the task level; accepting and coping well with shifting responsibilities to facilitate new team structure refers to adaptivity at the team level; and information-gathering to adjust to an organizational restructure reflects adaptivity at the organizational level. The success of such practice is highly dependent on employees’ attitudes and behaviors, the correct interpretation of the environment, as well as the supportive climate of the organization [54].

2.6. Hypotheses

As DRFH contends, the social influence of leadership has a critical role in adjusting the behavior of the organizational members to adversities and enhancing their capabilities to overcome future challenges [25]. In an organization where SL is practiced efficiently, the leader particularly focuses on informing followers about their expected behavior and activities [20,36] through leader–employee communication and constructive interpersonal relationships [55]. Servant leaders know how to motivate and inspire their followers to improve performance and to find opportunities to achieve. They foster a work environment that activates their followers’ ability to develop and provide high quality of performance [56,57]. This corresponds to SET suggesting that followers who are being cared for probably reciprocate their leaders’ efforts with elevated levels of efforts [58].

Limited research has explored how supportive leadership behaviors can influence employees with resilience-related personality features. According to Bartone [59] and Mazzetti et al. [49], hardiness in employees can be developed by leaders’ incentive behaviors that inspire them to re-evaluate undesirable events as worthy and identify the positive impacts of the threats. It is also suggested that, within adversities, leaders may foster their attitude of learning from failure and their ability to find novel approaches in solving problems [18]. This probably impacts their followers and fosters their attitude of learning from failure as well. Finally, Hsiao et al. [60] suggested that servant leaders who show ethical behavior and advocate fairness, listen to employees’ feedback, and consider their feelings significantly improve the state of optimism in their followers. Therefore, it is expected that organizations with SL have greater chances to enhance the resilience of their employees manifested in employees’ learning from failure, hardiness, and optimism. This prompts the following hypothesis (see Figure 1):

H1: 

SL is positively related to the resilience of employees (i.e., learning from failure, hardiness, and optimism).

The critical role of communication in achieving resiliency in organizations lies in its ability to provide stakeholders with the needed knowledge of the new turbulent situation and the necessary steps to adapt to or overcome it [25,61]. Little research has examined the impact of TC on employees’ attitudes and behaviors within adversities. For example, research reported that successful practice of TC in organizations helps encourage employees’ problem-focused control coping, reduce uncertainty [62] and enhance employees’ engagement [63]. TC also is found to lessen the adverse impact of employees’ emotional exhaustion in the employee–organization relationship and their advocative behavior [63]. Despite such a significant role, research that explains the influence of TC on individual’s resilience is quite fragmented and under-researched [64,65]. With this realization and as drawn in Figure 1, we hypothesize the following:

H2: 

TC is positively related to the resilience of employees (i.e., learning from failure, hardiness, and optimism).

According to Eva et al. [38], while servant leaders’ investment in their employees through emotional support and human resource practices might be considered an asset loss, it can be interpreted as an asset gain, as followers reciprocate by being more proactive, adaptive, and able to help servant leaders with their role. Little research has shown the link between SL and adaptive performance. For example, research has suggested SL behaviors help employees manage prolonged work stress and burnout feelings (a sub-facet of adaptive performance) [37]. Kaya and Karatepe [58] reported that servant leaders have a significant impact on their followers’ adaptive performance via work engagement. However, this result slightly contradicts the study of Newman, et al. [66] which found insignificant relation between SL and employees’ innovative behavior; a critical feature of adaptive performance. To examine the association between SL and adaptive performance, we hypothesized the following:

H3: 

SL is positively associated with employees’ adaptive performance.

Accountable, transparent, and timely internal communication can be considered a significant workplace coping enabler within change events [62]. Past studies have highlighted the value of the provision of information in promoting the appropriate coping efforts [67,68], such as adaptive performance. Through TC, employees have better access to resources and organizational support [67,69] which enable them to actively adapt to turbulent events [62]. On the contrary, the shortage of information probably leads to the lack of understanding of the stressful situation which increases employees’ feelings of uncertainty and uncontrollability and probably leads employees to not exert efforts in coping activities [43,63]. Therefore, we hypothesize the following:

H4: 

TC is positively associated with adaptive performance.

Park and Park’s [14] review study demonstrates that personality characteristics specifically, the Big Five personality dimensions is largely studied as antecedents of adaptive performance. Little research has tested the potential impact of other qualities on adaptive performance. For example, only two studies have investigated the relationship between hardiness and adaptability. One showed that hardiness is significantly related to adaptive performance [70]. The other study found an indirect relationship between hardiness and coping behavior through coping style, but not a direct one [71].

Regarding learning from failure, studies have lightly referred to its potential influence on adaptive performance. For example, research suggests that general cognitive ability [52,72], and individual and organizational experiential knowledge [73] are positively linked to adaptive performance. Optimism, on the other hand, is considered a constructive emotional characteristic that is linked to better adjustment to stressors [72], and problem-focused coping behavior [2,72]). Given the paucity of research examining the influence of employees’ resilience dimensions on adaptive performance, we hypothesize the following:

H5: 

The resilience of employees (i.e., learning from failure, hardiness, and optimism) is positively associated with adaptive performance.

SET was used as the basis for building the hypotheses concerning the mediating effect of employees’ resilience in the relationship between social capitals (i.e., SL and TC) and adaptive performance. SET proposes that individuals who receive highly valued social resources from their organization may reciprocate by devoting more of their emotional, cognitive, and physical resources to their organization [35]. Leaders who adopt the SL style focus on their followers’ development by creating an effective interrelationship with them. They share wisdom and consensus, rely on persuasion in discussions, delegate authority to their followers, and promote their growth [20]. Therefore, employees working in such a climate respect and admire their leader and organization and may reciprocate with higher levels of resilience and adaptive performance, specifically when adversities occur.

A climate with a TC is also critical for employees as it enables them to deal with workplace challenges and stress by acquiring the needed information, understanding the existing situation, voicing their concerns, and negotiating and opposing thoughts. Enabling employees to acquire timely credible information and effectively participating in decision-making leads to enriching employees’ work-life [74] and enhancing their coping capabilities rather than perceiving uncertainty and uncontrollability in the existing situation [62]. Therefore, employees who positively evaluate their organization climate as transparent and supportive are probably more engaged and dedicated to their job goals and reciprocate by proactively enhancing their resilience and accordingly their adaptive performance. Hence, we hypothesize the following:

H6: 

The resilience of employees (i.e., learning from failure, hardiness, and optimism) mediates the impact of SL on adaptive performance.

H7: 

The resilience of employees (i.e., learning from failure, hardiness, and optimism) mediates the impact of TC on adaptive performance.

3. Methodology

3.1. Measurement Development

All measures were developed based on the extensive literature review and pilot test. Liden, et al. [36] seven variables scale was employed to measure SL (a = 0.985). A sample variable included “My supervisor puts my top interests ahead of his/her own”. TC was measured by 16 items (a = 0.930) derived from Rawlins [40] and Men and Bowen [69]. The 16 variables construct three dimensions named participation (six variables), substantiality (six variables), and accountability (four variables). Adaptive performance was measured by three dimensions (a = 0.950) adopted from Griffin, et al. [53]. The adaptive performance scale covers individual task adaptability (three items), team task adaptability (three items), and organization adaptability (three items). Finally, hardiness (nine items) and optimism (nine items) were operationalized by employing the Connor_Davidson Resilience_Scale (CD-RISC) [75] (a = 0.918). Learning from failure was tested using seven items adopted from Shepherd et al. [48]. A sample variable included “I have developed my capability to make significant contributions to my job”. All employed measured were evaluated using a five-point Likert scale anchored by 1 (strongly disagree) and 5 (strongly agree). We pilot tested the questionnaire by some employees in restaurants and travel agencies (20), academics (8), and experts (13). Its readability, clarity, suitability, and comprehension were assured. In order to gain reliable information, the questionnaire explicitly assured anonymity and confidentiality.

A self-reporting instrument was employed; therefore, common_method_variance (CMV) can be a problem [76]. To avoid any potential issue of CMV, Harman’s single_factor analysis was carried out, the number of extracted factors constrained to one in SPSS exploratory factor analysis test (EFA) with no rotation method. One factor extracted and explained only for 29% of the variance, consequently, CMV is not a concern [77].

3.2. Participants and Process of Collecting Data

To gauge the hypotheses depicted in Figure 1, we randomly distributed a self-administrated questionnaire to full-time employees in SMEs (restaurants and travel agencies) in Egypt post the pandemic crisis. The sudden increase in the pandemic and the locking down of countries’ borders resulted in an immense economic hit for the entire industry in Egypt and worldwide. Essentially, the lockdown procedures, and travel prohibitions forced many hospitality businesses to apply workforce reduction and alter strategies and policies to cope with challenges. The panic and future uncertainties resulted in a tremendous effect on employees’ resilience and how they assess the resilience of their organization and hence they were selected as the questionnaire respondents.

A total of 300 restaurants (140) and travel agencies (160) were contacted during May and June 2021. The contact information was collected based on the Egyptian Hotel Guide (EHG), issued by the Tourism Authority in Egypt. To evade overrepresentation or underrepresentation of restaurants and travel agencies, four surveys were circulated to each category. The research team disseminated the questionnaire through two consecutive means: (1) by email forwarded to owners of SMEs, gently asking them to head the questionnaire to four employees, which returned only 50 questionnaires from restaurants (30) and travel agencies (20); and (2) by a drop-and-collect technique [78], in which 1200 questionnaires were disseminated personally by hand and then collected later. This method of data collection yielded 830 valid questionnaires. Thus, a total of 880 valid questionnaires were attained from the two steps process of data collection with a response rate of around 73%.

4. Results

4.1. Descriptive Statistics

Table 1. Respondents’ profile.

		N = 880	%
Type of business	Restaurant employees	500	57%
	Travel agent employees	380	43%
Gender	Male	620	70%
	Female	260	30%
Marital status	Married	619	70%
	Unmarried	261	30%
Age	<30 years	80	10%
	30 to 45 years	500	57%
	46 to 60 years	250	28%
	More than 60 years	50	5%
Education level	Less than secondary diploma	150	17%
	Secondary diploma	320	37%
	Bachelor’s degree	400	46%
Years in operation	Less than 5 years	317	36%
	6 to 15 years	313	35%
	Over 15 years	250	29%

displays the demographic characteristics of all respondents. Among the 880 respondents, 500 (57%) were restaurants employees, and 380 (43%) were travel agency employees. The majority were male (70%) and with spouses (70%). More than half of the people who responded to the survey (57%) were between the age of 30–45 years. Around 47% were university graduates. Regarding the length of employment, 317 respondents (about 36%) had been with their company for a period of less than 5 years at the survey time, while 313 (35%) had been working with their company for 6 to 15 years.

Table 2. Descriptive statistics.

Abbr.	Items	N	Min.	Max.	M	SD	Skewness	Kurtosis
TC (Participation); Rawlins [40], Men and Bowen [69].
TC_Partc_1	The firm requests feedback from employees like me on the information quality within the change.	880	1	5	3.61	0.835	−0.222	−0.037
TC_Partc_2	The firm involves employees like me to help define the information I need within the change.	880	1	5	3.58	0.811	−0.244	0.092
TC_Partc_3	The firm gives comprehensive information to employees like me within the change.	880	1	5	3.57	0.841	−0.344	0.222
TC_Partc_4	The firm facilitate finding the information employees like me need within the change.	880	1	5	3.58	0.836	−0.351	0.270
TC_Partc_5	The firm requests the viewpoints of employees like me before making decisions within the change.	880	1	5	3.56	0.830	−0.221	−0.036
TC_Partc_6	The firm takes the time with employees like me to understand who we are and what we need within the change.	880	1	5	3.57	0.849	−0.350	0.224
TC (Substantiality information); Rawlins [40], Men and Bowen [69].
TC_subsInfor_1	The firm delivers information in a timely manner to employees like me within the change.	880	1	5	3.31	1.038	−0.440	−0.317
TC_subsInfor_2	The firm delivers relevant information to employees like me within the change.	880	1	6	3.23	1.135	−0.358	−0.346
TC_subsInfor_3	The firm delivers complete information within the change.	880	1	5	3.12	1.178	−0.275	−0.685
TC_subsInfor_4	The firm delivers information that is not complicated for employees like me to comprehend within the change.	880	1	6	3.05	1.237	−0.234	−0.773
TC_subsInfor_5	The firm delivers precise information to employees like me within the change.	880	1	5	3.01	1.265	−0.243	−0.85
TC_subsInfor_6	The firm delivers reliable information within the change.	880	1	5	3.37	0.949	−0.118	−0.293
TC (Accountability); Rawlins [40], Men and Bowen [69].
TC_accontblty_1	The firm presents multiple perspectives of controversial matters within the change.	880	1	5	3.73	0.817	−0.922	1.208
TC_accontblty_2	The firm is disclosing information that might harm it within the change.	880	1	5	3.71	0.847	−0.916	0.896
TC_accontblty_3	The firm accepts criticism by employees like me within the change.	880	2	5	3.77	0.754	−0.663	0.396
TC_accontblty_4	The firm freely acknowledges when it has made flaws within the change.	880	1	5	3.74	0.826	−1.045	1.489
SL (Liden et al., 2014)
SL_1	My supervisor can determine if a work-related issue is going wrong.	880	1	5	3.79	1.282	−0.951	−0.146
SL_2	My supervisor makes my career growth a priority.	880	1	5	3.72	1.291	−0.87	−0.317
SL_3	I would ask help from my supervisor if I had a personal concern.	880	1	5	3.74	1.282	−0.894	−0.224
SL_4	My supervisor affirms the significance of giving back to the community.	880	1	5	3.74	1.290	−0.918	−0.217
SL_5	My supervisor puts my top interests ahead of his/her own.	880	1	5	3.71	1.298	−0.873	−0.305
SL_6	My supervisor allows me to handle hard situations in a way that I believe is best.	880	1	5	3.70	1.302	−0.850	−0.361
SL_7	My supervisor would NOT compromise moral values to achieve success.	880	1	5	3.70	1.299	−0.851	−0.359
Entrepreneurs’ resilience (Optimism); Connor and Davidson [75].
Optimisim1	Things occur for a reason.	880	1	5	3.41	1.003	−0.454	−0.422
Optimism2	I can deal with unpleasant emotions.	880	1	5	3.48	0.996	−0.833	0.143
Optimism3	I have to act on instinct.	880	1	5	3.20	1.115	−0.329	−0.895
Optimism4	I have a solid feeling of purpose.	880	1	5	3.38	1.067	−0.522	−0.641
Optimism5	I see the amusing side of things.	880	1	5	3.06	1.117	−0.213	−0.998
Optimism6	I tend to rebound after a hardship or illness.	880	1	5	3.51	1.087	−0.855	−0.018
Optimism7	Adapting to stress strengthens me.	880	1	5	3.18	1.161	−0.358	−0.926
Optimism8	I devote my best effort, no matter what.	880	1	5	3.22	1.116	−0.435	−0.814
Optimism9	Sometimes fate or God’s will can help.	880	1	5	3.25	1.079	−0.567	−0.628
Entrepreneurs’ resilience (Hardiness); Connor and Davidson [75].
Hardiness1	Under stress, I concentrate and think clearly.	880	2	5	4.31	0.8507	−0.998	0.023
Hardiness2	When issues seem hopeless, I do not quit.	880	1	5	4.29	0.8651	−1.003	0.128
Hardiness3	I can handle whatever comes my way.	880	2	5	4.28	0.872	−0.953	−0.096
Hardiness4	I can make uncommon or hard decisions.	880	2	5	4.32	0.874	−1.080	0.187
Hardiness5	I like to take the lead in problem-solving.	880	2	5	4.30	0.875	−1.022	0.076
Hardiness6	I believe I am a strong person.	880	2	5	4.28	0.900	−1.028	0.029
Hardiness7	I am not easily discouraged by failure.	880	2	5	4.29	0.882	−0.988	−0.029
Hardiness8	I like challenges.	880	2	5	4.28	0.896	−1.036	0.093
Hardiness9	I work to achieve my goals.	880	1	5	4.29	0.890	−1.030	0.120
Entrepreneurs’ resilience (Learning from Failure) Shepherd et al. [48]
LE_Fail_1	I have learned to better perform my duties.	880	1	5	4.06	1.156	−1.119-	0.428
LE_Fail_2	I can more effectively execute my tasks.	880	1	5	4.03	1.154	−1.076	0.354
LE_Fail_3	I have developed my capability to make significant contributions to my job.	880	1	5	4.01	1.157	−1.036	0.263
LE_Fail_4	I can “recognize” earlier the indications that a project is in trouble.	880	1	5	4.01	1.161	−1.034	0.239
LE_Fail_5	I now understand the mistakes we did that resulted in the project’s failure.	880	1	5	4.05	1.519	7.378	0.224
LE_Fail_6	I am more interested in helping others handle their failures.	880	1	5	3.99	1.169	−1.026	0.237
LE_Fail_7	I am a better tolerant person at work.	880	1	5	3.99	1.168	−1.020	0.231
Adaptive performance (Individual task adaptivity); Griffin et al. [53].
Indv_Tsk_Adpt_1	Coped well to changes in main duties.	880	1	5	3.72	1.256	−0.619	−0.740
Indv_Tsk_Adpt_2	Adapted to changes to the way you must do your main tasks.	880	1	5	3.69	1.263	−0.594	−0.763
Indv_Tsk_Adpt_3	Learned new capabilities to assist you cope with changes in your main tasks.	880	1	5	3.69	1.261	−0.588	−0.769
Adaptive performance (Team member adaptivity) Griffin et al. [53].
Tem_Memb_Adpt_1	handled effectively changes influencing your work unit (e.g., new members).	880	1	5	3.61	0.921	−0.722	0.612
Tem_Memb_Adpt_2	Learnt new capabilities or taken on new roles to adapt to changes in the way your unit operates.	880	1	5	3.66	0.875	−0.646	0.577
Tem_Memb_Adpt_3	Responded productively to changes in the way your team operates.	880	1	5	3.58	0.930	−0.686	0.280
Adaptive performance (Organization member adaptivity) Griffin et al. [53].
Org_Memb_Adpt_1	Responded flexibly to total changes in the firm (e.g., changes in management).	880	1	5	3.68	1.236	−0.532	−0.847
Org_Memb_Adpt_2	Adapted to changes in the way the firm operates.	880	1	5	3.66	1.223	−0.526	−0.814
Org_Memb_Adpt_3	Learnt capabilities or gained information that assisted in adjusting to overall changes in the firm.	880	1	5	3.64	1.226	−0.485	−0.860

shows some descriptive statistics as well. The maximum (Max.) and minimum (Min.) scores for the responses were 5 and 1 respectively. The mean (M) scores were between 3.01 and 4.32 and the values of standard deviation (SD) were between 0.811 and 1.302, divulging that our data are more scattered, and less spotted around the mean [79]. The skewness and kurtosis values (ad depicted in Table 2) showed no values higher than −2 or +2, providing a signal the data showed a normal distribution curve [80].

4.2. Findings from Confirmatory Factor Analysis Model (CFA)

First order CFA with maximum likelihood (ML) estimation procedure was carried out to evaluate the convergent and discriminant validity of the developed measures [81,82,83]. The employees’ capacity for resilience scale was subjected to the partial aggregation procedure proposed by Bagozzi and Heatherton [81] in which items were aggregated to create three indicators per factor named: hardiness, learning from failure, and optimism. Similarly, the 16 items measuring the three latent dimensions of TC (participation, substantiality, and accountability) were combined to build three indicators. Likewise, the nine items measuring the three dimensions of the adaptive performance scale were combined to create three variables.

Various goodness-of-fit (GoF) measures were used to evaluate the fit of measurement and structural models as suggested by Byrne [83], Hair et al. [83], and Kline [80], including normed chi-square, Comparative_Fit_Index (CFI), Tucker_Lewis_index (TLI), root mean_ square error approximation (RMSEA) and standardized root_mean squared (SRMR), Parsimony Comparative_Fit Index (PCFI) and Parsimony Normed_Fit Index (PNFI).

The CFA GoF output revealed a strong model fit (

Table 3. Scale validity.

Dimensions and Items	Loading	C_R	AVE	MSV	1	2	3	4
1-Employee resilience (a = 0.918)		0.921	0.795	0.223	0.892
Optimism	0.880
Hardiness	0.93
Learning from failure.	0.860
2-SL (a = 0.985)		0.985	0.903	0.204	0.262	0.950
SL1	0.953
SL2	0.956
SL3	0.972
SL4	0.945
SL5	0.948
SL6	0.938
SL7	0.940
3-TC (a = 0.930)		0.948	0.860	0.316	0.225	0.225	0.927
Participation	0.926
Substantiality information	0.853
Accountability	0.932
4-Adaptive performance (a = 0.950)		0.951	0.865	0.223	0.351	0.204	0.394	0.930
Individual task adaptivity	0.820
Team member adaptivity	0.800
Organization member adaptivity	0.760

Model fit: χ² (98, N = 880) = 360.542, p < 0.001, normed_χ² (3.679), RMSEA (0.033), SRMR (0.038), CFI (0.970), TLI (0.968), NFI (0.969), PCFI (0.819), and PNFI (0.813). C_R: composite reliability; AVE: average_variance extracted; MSV: maximum_shared value; diagonal_values: the square_root of AVE for each dimension; below diagonal values: intercorrelation between dimensions.

). Cronbach’s alpha values (previously explained) and composite reliability (C_R) were used to evaluate construct reliability. As shown in Table 3, the C_R findings for the four employed dimensions were as follows: SL (0.985), TC (0.948), adaptive performance (0.951), and employees’ capacity for resilience (0.921). All the values exceeded the suggested cut-off level of 0.70, suggesting strong internal consistency [84].

In addition, the convergent validity of the measurement scale was accomplished for two reasons: first, all the factor loadings (FLs) were significantly high and satisfactorily significant (Table 3). As presented in Table 3, all FL scores are between 0.853 and 0.972 and therefore exceeding the suggested threshold value of 0.50 [83]. Second, the average variance extracted (AVE) scores of all employed dimensions (SL, TC, adaptive performance, and employees’ capacity for resilience) were 0.903, 0.860, 0.865, and 0.795 respectively (Table 3). All the values were higher than 0.50, showing satisfactory convergent validity [83]. The maximum shared variance (MSV) values were also lower than the AVE values (see Table 1), which indicates good discriminant validity [83]. Discriminant validity was further validated because the values of the square_root of AVE for each dimension are higher than the values of intercorrelation between dimensions [80,82,83] (Table 3).

4.3. Structural Equation Modeling (SEM)

This research used a confirmatory approach, in which a theoretical conceptual model was developed based on extensive literature review, and then observed data were collected to analyze if it matched the previously defined theoretical conceptual model [85]. The theoretical (structural) model is rejected or approved in this procedure depending on whether it meets a model fit criterion. As shown in

Table 4. Result of a structural model.

	Hypotheses			Beta (β)	C-R (T-Value)	R2	Hypotheses Results
H1	SL	→	Employee Resilience	0.43 ***	7.588		Supported
H2	TC	→	Employee Resilience	0.39 ***	6.362		Supported
H3	SL	→	Adaptative Performance	0.27 ***	3.461		Supported
H4	TC	→	Adaptative Performance	0.25 ***	3.160		Supported
H5	Employee Resilience	→	Adaptative Performance	0.52 ***	9.999		Supported
H6	SL → Employee Resilience → Adaptative Performance			Path 1: β = 0.43 *** Path 2: β = 0.52 ***	Path 1: t-value = 7.588 Path 2: t-value = 9.999		Supported
H7	TC → Employee Resilience → Adaptative Performance			Path 1: β = 0.39 *** Path 2: β = 0.52 ***	Path 1: t-value = 3.160 Path 2: t-value = 9.999		Supported
Employee Resilience						0.34
Adaptative Performance						0.41

Model fit: (χ² (99, N = 880) = 430.848, p < 0.001, normed_χ² = 4.352, RMSEA (0.045), SRMR (0.033), CFI (0.956), TLI (0.952), NFI (0.969), PCFI (0.731) and PNFI (0.727). ***: significant level < 0.001.

, the structural model fitted the data well, according to the SEM results: χ² (99, N = 880) = 430.848, p < 0.001, (Normed χ²) = 4.35, (SRMR = 0.033, RMSEA = 0.045, CFI = 0.956, NFI = 0.969, and TLI = 0.952, PCFI = 0.731, and PNFI = 0.727). The study hypotheses were tested after obtaining adequate model fit criteria. A research hypothesis is pictured in Figure 2 by each path in the structural model between the latent variables.

This study suggested five direct hypotheses. The first hypothesis that tests the impact of SL on the resilience of employees (H1) is supported (T-value = 7.588, p < 0.001), with a highly significant path coefficient of 0.43 demonstrating that the two variables have a positive direct relationship. Similarly, the SEM results show that the impact of TC on the resilience of employees (H2) is positive and significant (T-value = 6.362, p < 0.001), with a path coefficient of 0.39, thus hypothesis two (H2) is supported. Likewise, the third hypothesis investigated the impact of SL on adaptive performance, the SEM results showed a positive significant (T-value = 3.461, p < 0.001) relationship between the two variables with a path coeffective of 0.27 supporting hypothesis three (H3). The impact of TC on adaptive performance was found to be positive and significant (T-value = 3.160, p < 0.001) with a path coeffective of 0.25 supporting hypothesis four (H4).

Finally, as shown in Table 4, the impact of the resilience of employees on adaptive performance is positive and significant (T-value = 9.999, p < 0.001) and showed a high path coeffective of 0.52, hence supporting hypothesis five (H5).

The SEM results also provide signals that the resilience of employees partially mediates the link between SL, TC, and adaptive performance, as direct and indirect relationships were [86]. These results support H6 and H7. The mediation effects (H6 and H7) are further supported by investigating the direct and indirect effects in AMOS output [87]. The direct positive significant relationship between SL and adaptive performance increased from (β = 0.27, p > 0.001) to a total effect of 0.37 with p > 0.001. Similarly, the direct positive significant relationship between TC and adaptive performance increased from (β = 0.25, p > 0.001) to a total effect of 0.34 with p > 0.001. The previous SEM results further support the partially mediation effect of the resilience of employees in the relationship between SL, TC, and adaptive performance.

All the paths’ explanatory power (R2) explains 41% of the variance in adaptive performance (R2 = 0.41) as an endogenous latent variable, and 34% of the variance in the resilience of employees (R2 = 0.34), as displayed in Table 4.

5. Conclusions

On the basis of the DRFH and SET, this research developed and tested a model in which SL and TC affect the resilience of SMEs within/post adversities. Results of a self-administrated survey targeting employees in SMEs in Egypt demonstrated that, post-COVID-19, SL and TC can influence how employees cope with and respond to challenges- specifically their learning from failure and have a significant positive impact on their adaptive performance. Such a leadership style along with internal communication practices can effectively foster employees’ capacity for resilience and influence their abilities and willingness to engage in adaptive performance to meet the changing organizational needs. This study enriches the research with theoretical contributions to the SMEs literature in addition to important practical implications for managers.

5.1. Theoretical Contributions

The current investigation provides additional insights regarding the mechanism of the dynamic process of resilience in the workplace. First, this study reports the findings concerning the influence of social capitals in organizations, as manifested by SL and TC, on employees’ capacity for resilience. The present research also links social organizational capitals to adaptive performance as an indicator of business continuity through employees’ capacity of resilience. Exploring how resilience in organizations is developed and how it influences workplace outcomes is significant because such a process is in the primary phases of investigation [8,88,89,90], specifically in the SMEs context [9].

Second, no empirical investigation was found of the impact of SL on employees’ capacity for resilience [24], despite being highly recommended especially for the tourism and hospitality business [57,88]. Our research tested the linkage between the SL and the resilient capacities of employees (i.e., hardiness, learning from failure, and optimism) in SMEs post-COVID-19. The result suggests that servant leaders who exhibit positive behaviors and responses during adversities and focus on meeting their followers’ needs, particularly the psychological ones, can improve the resilience level of their followers, specifically learning from failure. It seems that an organization with SL enables its employees to learn how to relieve stress, accept imperfection, and address problems accompanying shocking events. The positive attitude and behavior of such leaders broaden their followers’ thinking, motivate them to take the right path in the face of challenges, open up possible practices of how to respond to harsh conditions, and improve their state of optimism. The result reported here is not only concordant with the DRFH [25], but also receives support from empirical research proposing the significant impact of supportive leadership on the psychological capacities of employees [49,59,91].

Third, no empirical research has examined the relationship between the internal TC and resilience of organizations. This is surprising because TC has been noted to be a critical predictor of organizational resilience when confronting either planned or unplanned change [3,62]. Consistent with the DRFH [25], our study offers empirical evidence to the role of TC in developing and fostering employees’ capacity for resilience during adversities. Keeping employees on track about the existing situation of the organization and its influence on the current and future strategies fosters a positive atmosphere in the workplace where employees can participate in the decision-making process, leading them to accept challenges with confidence and optimism and better reach potential solutions.

Fourth, the results that the resilience of employees fully mediates the effects of social capital on employees’ adaptive performance suggest that employees who experience SL and TC within their organization demonstrate a high capacity for resilience and therefore display flexibility and adaptability to change despite uncertainty. As argued above, servant leaders as well as internal TC motivate employees to take on and put in the needed effort to thrive during harsh conditions and foster positive workplace outcomes [92,93,94]. It seems that servant leaders’ behaviors (e.g., placing the needs of their followers first, and offering them the support that goes beyond the formal employment relationship) in addition to providing employees with timely TC, trigger employees’ capacity for resilience within adversities [92]. In such a workplace climate, employees reciprocate by demonstrating a positive adaptive performance that matches the harsh situation.

Moreover, the findings provide a convincing case for the links among social organizational capitals, employees’ capacity for resilience, and employees’ adaptive performance as an indicator of business continuity. This research formulates theoretical and empirical reasoning for the importance of combining different disciplinary insights to develop the knowledge of organizational resilience. Based on the DRFH and SET, the proposed model, as reported above, maps out the capabilities of the organization (i.e., SL, TC, and the resilience of employees) in face of adversities and harsh events. Future studies can use such a framework to uncover the relationship between other organizational capabilities and the demonstration of resilience in organizations.

5.2. Practical Contributions

The results of this research may help SMEs managers in several ways. Firstly, top management can use SL to develop and enhance positive employees’ psychological characteristics and behaviors. Servant leaders should empower their followers, provide them the opportunity for promotion and growth, demonstrate compassion towards them, protect their interests, and delegate them authority [20]. Effective practice of SL should pave the way for developing employees’ capacity for resilience, enabling them to better adapt to organizational challenges, particularly when adversities occur [95,96]. In doing so, managers and supervisors should join training programs that teach how to practice SL, for example, by using case studies. This is crucial because servant leaders should build one-on-one relationships with their followers who have different personalities, goals, and ambitions and work under changing circumstances. Using case studies would help potential and current leaders to successfully deal with their followers, respond to their concerns, and take corrective actions when necessary.

Secondly, this research also offers implications for managers in using internal communication in influencing the resilience of employees and adaptation to organizational challenges. Managers/supervisors should provide employees with credible information about the harsh conditions the organization going through. Organizations should also motivate employees to voice their concerns and join the decision-making process by expressing their thoughts and negotiating opinions. Such communicative practices would enable employees to correctly understand the existing situation, and proactively respond to it specifically in times characterized by uncertainty and uncontrollability [43]. Therefore, management should organize communication training to teach supervisors at all levels how to practice transparency when interacting with employees. Supervisors through these programs should learn how to communicate openly, ensure a flow of timely reliable substantial information, involve employees in decision-making, and provide regular updates and feedback. By doing so, employees would better believe in their control on unfavorable circumstances, cleverly use the available resources to find suitable solutions, and have updated information and feedback to enhance their performance.

Finally, management should periodically evaluate the level of employees’ capacity for resilience in their organization. It is important to ensure that SL and TC efforts truly promote the resilience capacities of employees and enhance their adaption to challenges. The results of these evaluations would help fine-tune the practices of SL and internal communication in the organization.

5.3. Limitation and Future Research

This research has some limitations, as well as crucial findings and contributions to the resilience of SMEs. First, we developed and empirically examined a research model on the influence of SL and TC on employees’ capacity for resilience and adaptive performance (i.e., business continuity indicator), the impact of employees’ capacity for resilience on adaptive performance, and the underlying mechanism linking all these variables to organizational resilience. Only employees of SMEs in Egypt were considered for the study; thus, caution should be taken into consideration when generalizing the results for large companies or for top managerial level. Multi-group analysis can be conducted to investigate the impact of enterprise type on the research hypothesis. Second, our research examined only one business continuity indicator: employees’ adaptive performance. This provides a chance to extend this research by examining the relationships among SL, TC, and employees’ capacity for resilience on other factors, such as creativity and marketing indicators. Finally, this research employed a cross-sectional sampling analysis. Thus, despite the possibility of inferring causal effects between the study latent factors, they cannot be identified with certainty. The researchers thus may propose a longitudinal framework methodology to verify the current research’s potential causal relationships.