About the Author(s)

Desere Kokt Email symbol
Department of Business Management, Faculty of Management Sciences, Central University of Technology, Bloemfontein, South Africa

Bongani G. Mphirime symbol
Department of Business Management, Faculty of Management Sciences, Central University of Technology, Bloemfontein, South Africa


Kokt D. & Mphirime B.G., 2022, ‘Invigorating the hospitality industry: What is the impact of psychological contract and psychological capital on employee commitment?’, Acta Commercii 22(1), a981. https://doi.org/10.4102/ac.v22i1.981

Original Research

Invigorating the hospitality industry: What is the impact of psychological contract and psychological capital on employee commitment?

Desere Kokt, Bongani G. Mphirime

Received: 27 Sept. 2021; Accepted: 03 Mar. 2022; Published: 21 Oct. 2022

Copyright: © 2022. The Author(s). Licensee: AOSIS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Orientation: The coronavirus disease 2019 (COVID-19) pandemic has impacted all industries on a global scale. Specifically, the hospitality industry, being one of the largest industries in the world, has been affected by the decline in all forms of travel and tourism because of lockdown regulations instituted by governments.

Research purpose: In recovering from the devastating impact of COVID-19, it is imperative that the hospitality industry retains committed employees to revitalise and rebuild the industry.

Motivation for the study: The study reports on the impact of psychological contract and psychological capital on employee commitment within accommodation establishments.

Research design, approach and method: The study followed a quantitative research approach and a survey as data collection method. A structured questionnaire was administered to nine graded accommodation establishments in the two main economic hubs of the Free State province, namely Bloemfontein and Clarens. Data were analysed by partial least squares structural equation modelling (PLS-SEM).

Main findings: The results revealed that psychological contract has a statistically significant relationship with employee commitment. There was also a statistically significant relationship recorded between optimism and employee commitment, but no statistically significant relationships between hope, self-efficacy, resilience and employee commitment.

Practical/managerial implications: Rational contracts have the highest predictive power towards employee commitment. This emphasises the importance of developing and maintaining constructive relationships in accommodation establishments.

Contribution/value-add: The study was conducted during COVID-19, and thus, provides insight into the impact of psychological contract and psychological capital on employee commitment during the time of crisis and disruption.

Keywords: psychological contract; transactional contracts; rational contracts; psychological capital; employee commitment; social learning theory; hospitality industry; partial least squares structural equation modelling (PLS-SEM).


The tourism and hospitality industry is crucial in stimulating employment and growth opportunities in any country, especially in a developing country like South Africa. This industry consists of four inextricably linked segments: food and beverage (e.g. restaurants, bars and cafes), accommodation (e.g. hotels, motels and resorts), travel and tourism (e.g. transportation services and sightseeing), and recreation (e.g. river rafting and canoeing) (Asimah 2018).

The industry is highly volatile to both internal and external shocks, which can be caused by occurrences, such as natural disasters, global pandemics and terrorist attacks. This has been especially evident with the outbreak of the coronavirus disease 2019 (COVID-19) pandemic in the latter part of 2019 in China (WTTC 2020), resulting in a decline in tourist demands due to restrictions on mass mobility. Such severe lockdown measures instituted by governments globally to curb the spread of the virus have had a devastating impact on the tourism and hospitality industry (Khan et al. 2021).

Accommodation establishments play a crucial role in catering for tourist needs; hence, these establishments were the focus of this investigation. Having been critically affected by COVID-19, accommodation establishments need to bounce back and restore confidence in the hospitality industry. In this regard, the main objective of this study was to gauge the level of employee commitment in an industry that is highly labour-intensive and customer focused (Orido 2017). A demanding service industry such as the hospitality industry requires so-called emotional labour from employees. Emotional labour implies that employees need to continuously manage their feelings and expressions in performing their jobs (Biron & Van Veldhoven 2012). This, in turn, requires that both employees and employers be clear on their mutual expectations, and that employees maintain a positive emotional state. In considering these issues, as well as the psychological challenges associated with the COVID-19 pandemic, the study focused on the concepts of psychological contract and psychological capital.

The study also gauged the impact of COVID-19 in the South African context, specifically in the two main economic hubs of the Free State province, namely Bloemfontein and Clarens. While Clarens offers numerous adventure and recreational tourism activities, the Free State is not a prime tourist destination as Bloemfontein is more focused on business travel (Marais 2004). For purposes of the study, graded accommodation establishments in these two hubs were targeted. Only graded accommodation establishments were considered as they need to adhere to the strict requirements of the Tourism Grading Council of South Africa (TGCSA 2020) to obtain grading.

Literature review

Theoretical framework

The study was underpinned by the social learning theory, which postulates that learning is a social phenomenon constituted in the ongoing social practice. The theory is premised on the human capacity to learn through the observation of and consequences attached to other people’s behaviour (Bandura 1971). According to Yamao and Sekiguchi (2015), behaviour is regulated not only by direct consequences of actions but also by vicarious reinforcement and self-reinforcement. They maintain that collective individual learning is the basis for social learning.

Employee commitment is the degree to which an employee identifies with the organisation together with their intentions to actively participate in advancing the organisation (Luthans & Youssef-Morgan 2017). Employee commitment thus involves a strong desire to remain a member of a particular organisation. Alansaari, Yusoff and Ismail (2019) reiterate that given the nature of the hospitality industry, there is an inherent reliance on people to fulfil the industry’s basic function (e.g. customer service and satisfaction), which supports the importance of cultivating a committed workforce. Research has confirmed pertinent challenges within the industry ranging from perceived poor wages (Bouzari & Karatepe 2017), limited opportunities for personal development (Lee & Chen 2013), job stress and burnout (Kokt & Ramarumo 2015), long working hours and a lack of job security (Bouzari & Karatepe 2017; Kokt & Ramarumo 2015; Wang, Wang & Xia 2019), and difficulties in attracting and retaining the right calibre of staff (Kandampully, Zhang & Bilgihan 2015).

High levels of employee commitment are indispensable for increasing the output and obtaining a sustainable competitive advantage (Ivanov, Webster & Seyyedi 2018). The study supports the conceptualisation of commitment through the three-component model of Meyer and Allen (1997). These authors postulate that commitment is experienced by employees based on three components, namely affective (based on emotional ties the employee develops with the organisation), normative (the perceived obligation towards the organisation, rooted in the norms of reciprocity) and continuance commitment (based on the perceived economic and social cost of leaving the organisation). According to this view, commitment is likely to establish a strong affective attachment to the organisation and heighten the sense of obligation to remain with the organisation (Meyer & Allen 1997). This conceptualisation of employee commitment is supported by the social learning theory as the mentioned behaviours are observed, and thus internalised, by other members of the organisation.

Psychological contract and psychological capital

The employment relationship is a complex interplay of expectations from both the employer and the employee (Dwesini 2019). This relationship encapsulates the entire spectrum within an employment contract, ranging from a strictly legal one to a purely psychological relationship (Kim, Karatepe & Lee 2018). Psychological contract can be defined in terms of the beliefs of employers and employees regarding the reciprocal obligations that exist between them (Anggraeni, Dwiatmadja & Yuniawan 2017). The development of the ‘psychological contract’ concepts can be traced back to the 1960s (Argyris 1960) when two types of psychological contracts were identified: transactional and rational contracts.

Transactional contracts are characterised by a short-term monetary scope. This entails clear expectations about aspects, such as fair compensation and the notion of reward and punishment (Alcover et al. 2017). Transactional contracts are materialistic in nature and may result in employees only working towards collecting their remuneration. Transactional contracts are also characterised by the limited involvement of parties and emphasise specific short-term monetary obligations. This type of contract provides tangible positive outcomes for both parties and has been linked to enhanced cohesion and organisational citizenship behaviour (Anggraeni et al. 2017).

Rational contracts, however, are associated with social exchange in which trust provides the basis for ongoing exchanges between the employee and the organisation. This engenders feelings of mutual obligation in which employees come to expect that they will be rewarded eventually for their hard work, loyalty and sacrifice. Rational contracts are thus characterised by socio-emotional elements, which involve the interpersonal relationships between employees as well as their social and personal development (Dwesini 2019).

Developing a moral responsibility is considered to be an underlying motive for meeting relationship obligations, as opposed to accountability for only specific outcomes (Newman et al. 2018). Rational contracts are aimed at long-term job security, career development and personal support (Pate & Scullion 2018). These contracts are linked to civic virtue and trust (Jensen, Opland & Ryan 2010), as well as job satisfaction and intention to remain with the employer (Theron & Dodd 2011). For the sake of this study, the Psychological Contract Inventory of Rousseau (2000) was utilised to measure the construct.

Psychological capital pertains to personal strengths and positive qualities of individuals, all of which can lead to improved individual and organisational performance (Youssef 2004). Psychological capital is characterised by four elements: hope, resilience, self-efficacy and optimism. Hope is the combination of cognitive energy and creating pathways to reach one’s goals (Jung & Yoon 2015). This relates to goal-directed thinking that propels individuals towards desired outcomes. It also involves the willpower and energy needed to move towards reaching goals. Individuals with higher levels of hope are more likely to approach goals with positive feelings, incorporating a sense of challenge and anticipation of success. Individuals with lower levels of hope tend to focus more on deficiencies, negative feelings and thoughts of failure.

Luthans (2002) describes resilience as the positive psychological capital to rebound, or bounce back from adversities, uncertainties, conflicts, failures or even positive change and increased responsibility. Thus, resilience is the ability to constructively adapt in the face of adversity.

Self-efficacy refers to individuals’ conviction about their own cognitive abilities and self-motivation to successfully execute a specific task within a given context. Bouzari and Karatepe (2017) found that high levels of self-efficiency decrease the likelihood of failure when approaching a task, while Ronnie (2008) found that high levels of self-efficiency elicit a higher goal setting, self-motivation and perseverance. Luthans and Youssef-Morgan (2017) observed that individuals with high levels of self-efficiency display positive work experiences and higher levels of individual well-being.

Optimism is associated with positive attributes towards events, including positive emotions, motivation, realistic expectations and flexibility (Youssef 2004). Costa and Neves (2017) found that optimism within the workplace helps employees to constructively deal with feelings of being overwhelmed, while mitigating job stress and feelings of guilt and shame (Calvo & García 2020; Costa & Neves 2017; Luthans et al. 2005; Luthans & Youssef-Morgan 2017).

There is a dearth of research in the hospitality industry pertaining to the impact of psychological contract and psychological capital on employee commitment. This attests to the contributory value of this article.

Research methods and design
Research philosophy and design

The study was guided by the positivist epistemology as the researchers believe that social phenomena and their meaning exist separate from social actors. According to Saunders, Lewis and Thornhill (2012), the positivist researcher focuses on collecting measurable, quantifiable data in search of regularities and causal relationships. The study further employed a quantitative research approach and a descriptive research design, specifically a survey method to gather data from respondents.


Although the Free State province is not a main tourist destination, here there is still a need for economic growth and development in the province. The two main economic hubs of the Free State province namely Bloemfontein (which receive mostly business travellers) and Clarens (which caters for business and leisure tourists) were included in the study. The population of the study included employees working in graded accommodation establishments in Bloemfontein and Clarens during 2020. Only graded accommodation establishments were included in the study as they need to adhere to the strict criteria of the TGCSA to obtain grading. A list of all graded accommodation establishments are available on the TGCSA (2020) website. Although 20 establishments were initially part of the study, only nine participated in the study because of establishments either being closed or temporarily closed during 2020. Of the nine establishments, five were in Bloemfontein and four in Clarens. Prior to data collection, the main researcher requested the exact number of employees working at the various establishments. This amounted to around 150 employees, which constituted the population for the study. Ninety-two (92) questionnaires were completed and used for data analysis with a response rate of 61%.

Data collection

Data collection proved to be problematic because of pandemic-related lockdown restrictions. After obtaining written permission from the owners or managers of the various accommodation establishments, the main researcher personally administered hard copy questionnaires at the establishments. This allowed the researcher to obtain consent from the participants prior to data gathering. Simple random sampling was applied to target employees at various establishments. Simple random sampling implies that all employees have an equal chance of being selected for the study (Sekaran & Bougie 2016). As the main researcher visited all the participating establishments, a great deal of administrative and travelling arrangements were required. The data were captured using an Excel spreadsheet, and the main researcher meticulously captured every response. The data entries were checked by a statistician.

Measurement instrument

Data were collected using a structured questionnaire consisting of four sections. Section A measured the demographics (age, gender, race and position in the organisation). Section B, comprising 15 questions, captured responses related to psychological contract based on the Psychological Contract Inventory of Rousseau (2000). Section C, comprising 14 questions, measured employee commitment based on Meyer and Allen (1997), and Section D, comprising 15 questions, captured responses related to psychological capital based on the work of Luthans (2002). Questions were framed using a five-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree and 5 = strongly agree).

The questionnaire was piloted using 10 employees from graded accommodation establishments in Bloemfontein. These establishments were not included in the main data gathering. The pilot study showed that the questionnaire was clear, and no changes were made prior to administering the questionnaire in the main study.

Data analysis

Data were captured in Excel as advised by a statistician, and both descriptive and inferential statistics were employed to interpret the findings. Structural equation modelling, specifically partial least squares structural equation modelling (PLS-SEM), was applied to examine the relationships between the variables. Smart PLS version 3.0 was used to conduct the analysis.

Ethical considerations

Ethical clearance for the study was obtained from the Faculty Research and Innovation Committee for the Faculty of Management Sciences at the Central University of Technology, Free State, reference number: FRIC 09-02-2018. The following ethical considerations were adhered to and conveyed in the cover letter that accompanied the questionnaire. The employees who participated in the study were informed of the purpose of the study. Participation in the study was voluntary and explained as such. The questionnaire was anonymous, and respondents were ensured that their privacy would be maintained.


The following section provides an outline of the findings. The demographical composition of the respondents was as follows: most respondents (96%) were between the ages of 21 and 40 years, with 65% of respondents being female and 35% male. Ninety-seven per cent (97%) of respondents were of African descent. The most prevalent positions occupied by respondents (20%) were front of house staff (e.g. reception) and supervisory or managerial positions which accounted for 16% of the responses.

As all variables significantly deviated from a normal distribution, the use of the PLS-SEM was validated (Hair et al. 2017). Partial least squares structural equation modelling does not require data to be normally distributed and can be conducted on a small sample size (Bouckenooghe, De Clercq & Raja 2019). The minimum sample size should be equal to the larger of the following: (1) 10 times the largest number of formative indicators used to measure one construct, or (2) 10 times the largest number of structural paths directed at a particular construct in the structural model (Hair et al. 2017). In this study, the largest number of the structural paths directed at a construct was six (Figure 1), meaning that the minimum required sample size for a PLS-SEM analysis was 60. As the sample size for this study was greater than 90, it thus exceeded the minimum requirement.

FIGURE 1: Research model.

The following hypotheses were formulated:

H1: There is a statistically significant relationship between transactional contracts and employee commitment.

H2: There is a statistically significant relationship between rational contracts and employee commitment.

H3: There is a statistically significant relationship between self-efficacy and employee commitment.

H4: There is a statistically significant relationship between optimism and employee commitment.

H5: There is a statistically significant relationship between hope and employee commitment.

H6: There is a statistically significant relationship between resilience and employee commitment.

The PLS-SEM analysis was carried out in two stages, which included assessing both the outer and the inner model.

Assessing the outer model

According to Fornell and Larcker (1981), prior to testing for a significant relationship within the structural model, there must be an evaluation of the measurement tool. In this study, the reliability and validity of the measurement model were assessed using indicator reliability, convergent validity, internal consistent reliability and discriminant validity (Janadari, Subramaniam & Wei 2016). This is explained in the following subsection.

Indicator reliability

An indicator loading of > 0.5 indicates good indicator reliability (Hulland 1999). According to Hair et al. (2017), indicators with outer loadings between 0.40 and 0.70 should be considered for removal only if the deletion would lead to an increase in composite reliability (CR) and average variance extracted (AVE) above the suggested threshold value. Thus, in this study, indicators with loadings lower than 0.70 were removed from the measuring model only when the removal increased the CR and AVE values above the threshold of 0.7 for CR and 0.5 of AVE (Hair et al. 2017). (Table 1 displays the factor loadings.) The exceptions were cases in which there would be less than three indicators per construct. The following items were removed from the measurement model: HO_PSYCAP9, OE8, RC_PSYCAC3, SE_PSYCAP5, TC_PSYCAC2, OE12, RC_PSYCAC13, RE_PSYCAP4, TC_PSYCAC9, OE10, RC_PSYCAC11, TC_PSYCAC4, OE13, RC_PSYCAC5, OE2, OE9 and OE6.

TABLE 1: Factor loadings.

As shown in Table 1, most indicator loadings were above the 0.5 threshold value prescribed by Hulland (1999). The table also shows that the only indicators that did not meet the 0.5 threshold were OE5, OP_PSYCAP13, OP_PSYCAP7, RC_PSYCAC12, RE_PSYCAP11 and SE_PSYCAP15. In order to preserve content validity, these indicators were not removed (Hair et al. 2017).

Convergent validity

Convergent validity is the extent to which a measure correlates positively with alternative measures of the same construct (Bagozzi & Yi 1988; Hair et al. 2017). It was assessed using AVE greater than 0.5, as set out in Table 2 (Fornell & Larcker 1981; Janadari et al. 2016).

TABLE 2: Average variance extracted.

As presented in Table 2, the AVE values of all constructs were above the 0.5 threshold, except for hope and optimism.

Internal consistency reliability

Internal consistency reliability is assessed using the CR of a construct. Gefen, Straub and Boudreau (2000) stated that a CR greater than 0.7 indicates adequate internal consistency reliability. The CR values for the study are shown in Table 3.

TABLE 3: Measurement model: Composite reliability.

According to Table 3, the CR values of all constructs were above 0.70, except for hope and optimism.

Discriminant validity

Discriminant validity is the extent to which a construct is truly distinct from other constructs by empirical standards. Discriminant validity implies that a construct is unique and captures phenomena not represented by other constructs in the model (Hair et al. 2017). In this study, the Fornell and Larcker criterion was used to assess discriminant validity as it compares the square root of the AVE values with the latent variable correlations (Fornell & Larcker 1981). The square root of each construct’s AVE should be greater than its highest correlation with any other construct. The AVE values for each construct are displayed in Table 4.

TABLE 4: Discriminant validity.

As shown in Table 4, the square root of AVE for each latent variable was higher than any correlation with any other latent variable, indicating discriminant validity of the measurement model.

Assessing the inner (structural) model

The following procedure was followed in constructing the inner model: Step 1, assessing the significance and relevance of structural model relationships; Step 2, assessing level R2; and Step 3, assessing the effect size (f2), which are explained below.

Step 1: Assessing the significance and relevance of structural model relationships

The direct effects of all the hypothesised relationships were evaluated by bootstrapping analysis. Bootstrapping is a resampling technique that draws many subsamples from the original data and estimates models for each subsample (Hair et al. 2017). The results of the bootstrapping analysis are shown in Table 5.

TABLE 5: Path model results of partial least squares structural equation modelling.

As displayed in Table 5 it shows that a standardised beta and t-values were calculated by the bootstrapping procedure with a resample of 5000. The results show a statistically significant negative relationship between transactional contracts and employee commitment (β = −0.169, p < 0.048). H1 of the study was, therefore, supported.

A statistically significant positive relationship was observed between rational contracts and employee commitment (β = 0.654, p < 0.001), as indicated in Table 5. H2 of the study was thus also supported.

There was no statistically significant relationship between self-efficacy and employee commitment (β = −0.089, p = 0.573), and thus, H3 was rejected. However, there was a statistically significant positive relationship between optimism and employee commitment (β = 0.21, p < 0.025). H4 was, therefore, supported.

No statistically significant relationship was observed between hope and employee commitment (β = −0.057, p < 0.693); therefore, H5 was rejected. Finally, there was no statistically significant relationship between resilience and employee commitment (β = 0.137, p = 0.156); therefore, H6 was rejected.

Step 2: Assessing the level R2

R2 measures the proportion of variance in a latent endogenous construct that is explained by other exogenous constructs expressed as a percentage (Chin 1988). Exogenous constructs are dependent constructs in at least one equation, although they may be independent variables in other equations in the system. In this study, the R2 value of employee commitment was 0.56. This means that a combination of transactional contracts, rational contracts and optimism explains 56% of the variance in the employee commitment construct. Cohen (1988) states that R2 values of ≥ 0.12 indicate a low-effect size, values between 0.13 and 0.25 indicate a medium-effect size, and values of ≥ 0.26 indicate a high-effect size. Thus, the results reveal that a combination of transactional contracts, rational contracts and optimism have a high predictive power towards employee commitment.

Step 3: Assessing the effect size (f2)

The effect size of a construct evaluates whether the omitted construct has a substantive impact on the endogenous construct, which is also known as the effect size of the exogenous latent variable. Cohen (1988) provided the following guidelines for effect size: 0.02 ≤ f2 < 0.15: weak effect, 0.15 ≤ f2 < 0.35: moderate effect, and f2 > 0.35: strong effect.

In the study, both transactional contracts (0.045) and optimism (0.082) had a weak effect; in other words, they did not play an important role in the prediction of employee commitment. However, the rational contracts (0.619) had a strong effect, meaning that it played a crucial role in the prediction of employee commitment. Figure 2 displays the PLS-SEM model.

FIGURE 2: The partial least squares structural equation modelling model showing the impact of psychological contract and psychological capital on employee commitment.

The relationships between the variables examined in this study were discussed, as shown in Figure 2. Psychological contract was measured using two contracts, namely transactional, and rational contracts. The findings revealed a statistically significant negative relationship between transactional contracts and employee commitment (−0.169, p = 0.048), while a positive statistical relationship was found between rational contracts and employee commitment (0.654, p = 0.000). Related to psychological capital, a positive statistical relationship was observed between optimism and employee commitment (0.210, p = 0.021). Finally, no statistical relationship was found between resilience and employee commitment (0.137, p = 0.154), hope and employee commitment (−0.057, p = 0.695), and self-efficacy and employee commitment (−0.089, p = 0.572).

Discussion and recommendations

As this is a novel study for the hospitality industry, the findings provide particular insights that will be explained below. The findings of this study confirm a negative statistically significant relationship between transactional contracts and employee commitment (Table 5). This implies that when transactional contracts breach increases, employee commitment decreases and vice versa (Brown, Thomas & Bosselman 2015; Penfold & Ronnie 2015; Wöcke & Sutherland 2008; Zhou 2014). The findings also show a significant positive relationship between rational contracts and employee commitment (Table 5). Rational contracts are associated with social exchange and the interaction between employees and the organisation.

It is recommended, therefore, that accommodation establishments instil a sense of collegiality amongst employees by stimulating good interpersonal relationships. Collegiality and conducive interpersonal relationships can create a sense of belonging amongst employees, which can, in turn, impact positively on employee commitment. This can also contribute to the socio-normative relationships of employees that relate to the unwritten rules for acceptable behaviour in the organisational context. This is important, as it enables employees to comply with the expectations of the organisation. Furthermore, hospitality establishments need to communicate their expectations clearly. This is especially important given the complex and dynamic nature of the hospitality industry. It is thus suggested that more emphasis be placed on employee orientation programmes at the commencement of the employment relationship. Establishments should also craft clear and unambiguous job roles and responsibilities for employees.

The study found no statistically significant relationship between self-efficacy and employee commitment (Table 5). Self-efficacy reflects the judgement of an individual’s ability to accomplish a certain level of performance (Yamao & Sekiguchi 2015). Previous research (see Kim et al. 2018; Luthans et al. 2006; Yildiz 2018) confirms that self-efficacy can increase the level of work engagement.

The study confirmed a statistically significant relationship between optimism and employee commitment (Table 5). Optimism relates to employees experiencing a positive outlook, including displaying positive emotions and being motivated when they contemplate the future. According to Luthans and Youssef-Morgan (2017), employees with high levels of optimism are generally more energetic, enthusiastic and engrossed in their work, which implies that they are more engaged and committed to both the organisation and their individual goals. This supports the research of Kong et al. (2018) and Wardani and Anwar (2019) who found that optimism positively affects employees’ commitment, and those with high levels of psychological capital show greater levels of organisational commitment, which generally results in an improved organisational performance.

The findings indicated no statistically significant relationship between hope and employee commitment (Table 5). Hope explains a positive motivational state that incorporates the energy and motivation for individuals to attain success. According to Luthans et al. (2005), individuals with high levels of hope show greater levels of commitment. Once individuals have higher levels of hope, they display a sense of duty and responsibility towards the organisation (Luthans et al. 2005).

The findings confirmed no statistically significant relationship between resilience and employee commitment (Table 5). Resilience relates to the ability to recover from setbacks – it can also be described as being tough and being able to bounce back from setbacks. Stajkovic and Luthans (1998) and Robyn and Mitonga-Monga (2017) found that resilience can increase work engagement, loyalty and intention to stay with an organisation. This usually results in employees being able to actively participate in problem solving within the work environment.

An important factor to consider is the ability of owners or managers to manage the social and economic impact of major disruption on employees (such as the case with COVID-19) as this can affect future employee commitment (Ocen, Kasekende & Angundaru 2017). As a result, the higher the impact on employees’ social or economic circumstances, the higher the degree of association with the organisation. Once an individual feels a sense of loyalty to an organisation, he or she is bound to defend the organisation (Alansaari et al. 2019; Zareie & Navimipour 2016).

The findings confirmed a correlation between optimism and employee commitment (Table 5). As such, it would be prudent for management in accommodation establishments to ensure that employee levels of optimism are maintained by focusing on the achievement of employees and what employees get right in terms of their job responsibilities. This will enable employees to approach difficult tasks with greater energy and confidence. Employees are also likely to experience a sense of support in dealing with every-day challenges. It is imperative that structures are in place for coaching, mentoring and support.

Other recommendations emanating from the findings are that owners or managers should endeavour to inculcate a sense of belonging towards the organisation by creating a psychologically safe space for employees within accommodation establishments. This can be done by ensuring that employees are made aware of the establishment’s vision, mission, goals and challenges. This should instil a sense of hope amongst employees that the establishment is open and honest and cares for their well-being.

In order to enhance the self-efficacy of employees, more emphasis should be placed on training, development and wellness programmes, especially for smaller accommodation establishments. This is likely to increase self-efficacy and resilience, thus helping employees to enhance and develop their personal goals in line with those of the organisation. Furthermore, in order to enhance resilience, greater emphasis should be placed on employee well-being. Employees need to develop the necessary personal competencies to manage workplace challenges, such as communication and inter-personal skills, problem solving, and conflict management.


The study had prominent limitations because of the restrictions imposed to curb the COVID-19 pandemic. As alluded to before, accommodation establishments were either closed or temporarily closed, and many were not prepared to participate in the study. To reach the employees from the various establishments, the main researcher had to travel to the establishments to gather the data, which was time-consuming and laborious.


The main objective of this study was to investigate the impact of psychological contract and psychological capital on the commitment of hospitality employees. The findings of this study revealed a negative yet statistically significant relationship between transactional contracts and employee commitment, on the one hand, and a statistically significant positive relationship between rational contracts and employee commitment, on the other hand. These findings solidify the importance of the psychological contract in managing employee commitment. Thus, any significant breach of the psychological contract could have a negative effect on employee commitment.

Related to the psychological capital constructs, only optimism had a statistically significantly positive relationship with employee commitment. A possible reason for this may be the uncertainties regarding COVID-19 and its devastating impact on hospitality establishments. Owners or managers have an important role to play in enhancing self-efficacy, hope and resilience in their establishments.

Apart from being volatile to external shocks and disasters, the hospitality industry presents a uniquely complex working environment. Employees are expected to work long hours in an often hectic and demanding workplace. It is therefore suggested that further research needs to explore the psychological wellness and resilience of hospitality employees, and devise ways in which employees can be supported.


The authors would like to extend their gratitude to the Central University of Technology, Free State for the research grant to complete the study.

Competing interests

The authors declare that they have no personal or financial relationships that may have inappropriately influenced them in writing this article.

Authors’ contributions

B.M. constructed the first draft of the article and collected the data. D.K. refined the article and interpreted the research findings.

Funding information

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Data availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request.


The opinions conveyed in the current study do not represent the position of the funding institution but are interpretations exclusive to the concerned authors.


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