Organizational Cultures Determine Employee Innovation in Response to Seasonality: Regulatory Processes of Openness and Resistance

Abstract

The existing literature on tourism seasonality focuses on seasonality’s cause and impact but pays little attention to understand employees’ reactions to off-season markets. Drawing from approach-avoidance and regulatory focus theories, we examine the influence of three types of organizational cultures on employee innovative behavior. We also propose two regulatory processes that mediate those relationships: employee openness and resistance to change. Using multisource data from hotel employees and managers, our results indicate that employee openness positively mediates innovative and collaborative cultures’ relationships on employee innovation. In contrast, it negatively mediates the relationship between traditional culture and innovative behavior. On the other hand, employee resistance to change positively mediates the association between traditional culture and employee innovation, whereas it negatively mediates the relationships between innovative and collaborative cultures on employee innovation. We provide managerial implications and directions for future research in response to seasonality.

Keywords

tourism seasonality organizational culture innovative behavior openness resistance to change regulatory focus theory

Introduction

Seasonality is an inevitable issue in tourism and hospitality contexts. It determines the transitory and seasonal phenomena as the industry experiences overutilization and underutilization of resources resulting from seasonal variation (Senbeto & Hon, 2019). The seasonal changes in the market, in turn, influence the performance and productivity of tourism organizations. Currently, research on tourism seasonality has focused primarily on the causes and impacts of seasonal variation, using a one-size-fits-all approach (Koenig-Lewis & Bischoff, 2005). The causes of seasonality can be categorized into natural and institutional factors (Getz & Nilsson, 2004; Pegg et al., 2012; Turrion-Prats & Duro, 2017). Natural factors relate to climate and weather conditions, such as changes in temperature, rainfall, and sunlight that determine seasonal variations in tourist demand. On the other hand, institutional factors represent human activities and travel schedules that influence tourists’ seasonal flow and guests’ intention to visit a destination.

Prior studies have argued about the positive and negative influences of seasonality in tourism. Having fewer tourists in the off-season minimizes overcrowding and promotes a destination’s sustainability and surrounding facilities. However, from a commercial viewpoint, seasonality brings a plethora of challenges in terms of hotel occupancy, tourism receipts, and business activity and investment in general (Butler, 2001; Koenig-Lewis & Bischoff, 2005; Pegg et al., 2012). Although organizations adopt different strategies to offset seasonal market challenges, such as coping, combating, and capitulation (Getz & Nilsson, 2004), little is known about employees’ personal regulatory processes and their innovative behaviors, which have been significant, especially in their efforts to offset the seasonal shortage of demand (Senbeto & Hon, 2019). Without understanding individuals’ regulatory processes and how innovative behaviors will be increased or decreased, tourism organizations’ one-size-fits-all approach to the off-season is questionable. Organizations rely on their employees for innovative behaviors that will generate new and valuable ideas to form the foundation for new products, services, or processes (Amabile et al., 2004; Hon, 2012; Hon et al., 2013; Hon & Leung, 2011; Pizam, 2020; Senbeto & Hon, 2020). A such innovation and innovative behavior are crucial to offset the seasonal shortage of demand and gain a competitive advantage in the tourism market (Chen, 2011; Verreynne et al., 2019).

Moreover, organizational cultures can influence the interpretations of and reactions among employees who perform innovative behaviors in response to seasonality, but that relationship has received scant attention in the hospitality literature (Hon, 2012; Hon & Leung, 2011). However, an organization’s culture by itself cannot determine employees’ innovative behaviors, irrespective of the type and level of that culture, and employees’ regulatory processes play a vital role in the workers’ promotion or prevention foci for performing innovative behavior (Elliot, 2006; Higgins, 1997; Kim & Lee, 2013). Furthermore, researchers have repeatedly called for research to examine what kinds of organizational cultures promote employee innovative behaviour, and whether employees respond similarly or differently, in terms of creativity, to the same cultural influences (Hon & Leung, 2011; Zhou & George, 2001; Zhou & Shalley, 2008). Consequently, as a business strategy in response to the off-season in the hospitality industry, interest is growing for an examination of different types of organizational cultures and their effects on employee innovative behavior (Amabile et al., 2004; Hon et al., 2013; Hon & Lui, 2016; Senbeto & Chan, 2021).

By integrating the theories of approach-avoidance and regulatory focus, we arrive at several research objectives. First, we examine how different organizational cultures (i.e., innovative, collaborative, and traditional cultures) influence employees’ innovative behavior in response to the off-season. Second, we consider the role of employee openness as a generative regulatory process. We consider resistance to change as an avoidance or preventive regulatory process to understand the associations between different cultures and employee innovative behaviors. Third, this study contributes to understanding seasonality from a developing-country setting, as the existing studies have conducted in developed countries (Banki et al., 2016; Chen & Pearce, 2012; Koenig-Lewis & Bischoff, 2005).

Our contributions are threefold. First, we move beyond investigating the causes and impacts of seasonality. We identify employee innovative behavior as an important business strategy for hospitality firms to offset seasonal shortages of demand. Second, we examined the application of approach-avoidance and regulatory focus theories, via employee openness and resistance to change, to explain the relationships between different organizational cultures and employee innovative behavior. With that new understanding, we can answer hospitality managers’ questions about why some employees behave innovatively, and others tend to avoid innovation. Third, we go beyond the existing research, which has examined tourism seasonality in well-developed countries such as those in Europe and North America. Such gaps limit the generalizability and representativeness of the extant study on seasonality in tourism. Hence, this study further contributes to seasonality research and the hospitality and management literature in developing countries setting.

Theory and Hypothesis Development

Approach-Avoidance and Regulatory Focus Theories

The approach-avoidance motivation and the regulatory focus theory address human motivations, valence, stimuli, and behavioral decision-making processes. According to Elliot (2006), approach-avoidance motivation is

the energization of behavior by, or the direction of behavior toward a positive (approach motivation) stimuli (objects, events, possibilities), whereas avoidance motivation is defined as the energization of behavior by, or the direction of behavior away from, negative stimuli (objects, events, and possibilities). (p. 112)

Approach motivation represents the aspiration for positive stimuli or motives, while avoidance motivation represents negative stimuli or motives. The regulatory focus theory works closely with approach-avoidance motivation and elucidates how a person’s self-regulation is governed by positive or negative stimuli (Higgins, 1997, 1998). Regulatory foci can be categorized into promotion and prevention processes (Higgins, 1997). A promotion focus indicates the seeking of pleasure, development, and excitement, and the ideal self leads it, which is consistent with approach motivation. In contrast, a prevention focus pays attention to safety, protection, and obligations driven by the actual self and are compatible with avoidance motivation.

Studies have noted that approach-avoidance motivation being integrated with promotion and prevention foci strategies (Scholer & Higgins, 2008). Therefore, we integrate the two theories by combining an approach motivation with a promotion focus and an avoidance motivation with a prevention focus to provide a comprehensive understanding of the off-season market. Our combined theories imply that approach-promotion reveals individuals’ positive stimuli, and those stimuli lead to activation of further motive and action. Meanwhile, avoidance-prevention represents behavioral inhibitions that result in the prevention of losses and mistakes. We argue that employee innovative behavior in response to the off-season is sourced from an approach-promotion motivation or an avoidance-prevention motivation. Such motivation further determines how the employees’ psychological intentions arise—an interchange that is also influenced by the types of organizational culture the employees’ experience.

Organizations intentionally establish different cultures to drive employees’ motivation and behavior toward achieving organizational goals. Research has shown that innovative, collaborative, and traditional organizational cultures can influence employees creativity at workplace (Hon et al., 2014; Hon & Leung, 2011; Hon & Lui, 2016). Figure 1 presents a research model depicting the effects of the two regulatory mechanisms of employee openness and resistance to change, respectively, representing approach-promotion and avoidance-prevention regulatory processes, on the relationships between the three organizational cultures (innovative, collaborative, and traditional) and innovative behavior.

Figure 1

Proposed Model of Organizational Cultures and Employee Innovative Behavior in Response to Seasonality

The Regulatory Process of Employee Openness

Innovative culture and openness. An innovative culture is a business strategy that enables organizations to achieve success in product and service development and in exploring new markets and maintaining existing customers. In an environment with an innovative culture, employees are encouraged to experience new methods. The culture enables them to take risks and share different work approaches to change the status quo (Hon, 2012; Hon & Leung, 2011; Kofter, 2007). Thus, in an innovative cultural environment, employees tend to be more open to producing alternative marketing strategies to curb the off-season decline in demand. From the approach-avoidance and regulatory focus theories, employee openness, driven by approach motivation and promotion foci, is expected to lead to new ideas and unconventional working mechanisms. For example, Vaughn et al. (2008) found that people who were high in openness tended to follow promotion-related motives, while people who were low in openness tended to pursue prevention-related motives. Studies characterize openness as a person’s intellectual, cultural, imaginative, and creative mentality (Dollinger et al., 2004), and it paves the way for the individual’s eagerness for exploration and readiness to adapt to a new and changing environment (Makkonen et al., 2018; Woo et al., 2014).

Although employees do not create their cultural environment by themselves, they do have their individual positive or negative motives and responses toward their environment (Hon, 2012). According to the approach-avoidance motivation and regulatory focus theories, an innovative organizational culture encourages employees to work creatively and move beyond conventional practices. In response to the off-season, employees will think and act in novel ways and demonstrate new performance types to offset the seasonal variation. An innovative culture stimulates the employees who have a high degree of openness and a forward-thinking mindset to produce innovative actions. According to regulatory focus theory, that approach motivation, driven by an innovative culture, fosters employees with a high degree of openness, and their openness influences their subsequent promotion focus process, causing them to seek excitement and pleasure from developing more innovative behaviors. This approach motivation process enhances employees’ high levels of openness and leads them to adopt a promotion focus strategy in response to off-season markets. Thus, an innovative culture enhances employee innovative behavior via the employee openness regulatory process. We now have the following hypothesis:

Hypothesis 1₀: Openness does not mediate the relationship between an innovative organizational culture and employee innovative behavior in response to off-season challenges.

Hypothesis 1_a: Openness mediates the relationship between an innovative organizational culture and employee innovative behavior in response to off-season challenges.

Collaborative culture and openness. A collaborative organizational culture is also developed by organizations to drive employee innovative behavior. A collaborative culture encourages mutualism and coordination among people, and it allows employees in an organization to work together as a team to achieve common goals (Barczak et al., 2010; Hon & Leung, 2011). Research has asserted that the success of a collaborative organizational culture is leveraged by employees’ mutual interactions (Beyerlein et al., 2003; Nardi & Farrell, 2003), and their openness assists the organization’s endeavors in creating a supportive work culture. Thus, the employees’ openness propels an organization’s efforts to foster a collaborative work environment. Furthermore, studies found that attributes of employees’ openness are associated with positive outcomes, such as positive work attitudes, knowledge sharing (Cabrera et al., 2006), verbal intelligence (DeYoung et al., 2014), social responsibility (Bellou et al., 2018), cultural adaptation (Kenesei & Stier, 2017), and job burnout (Kim et al., 2007). Studies supported that collaborative culture positively related to employee’s knowledge sharing and service innovation (e.g., Hu et al., 2009; Hussain et al., 2016).

Openness and forward-thinking are characterized as curiosity and eagerness. Employees with high levels of openness are motivated to interact with others and are willing to share their workplace experiences. In accordance with approach-avoidance motivation and regulatory focus theory, approach motivation and promotion strategies raise employees’ intention to be open and ready for opportunities and exchange their experiences with coworkers. In the off-season period, a collaborative culture facilitates employees with high levels of openness and leads them to exhibit innovative actions. Such an approach motivation, driven by a collaborative culture, further enhances employees’ regulatory promotion focus and collaborates with others to generate more innovative behaviors. Hence, we expect that employee openness mediates the positive linkage between a collaborative culture and employee innovative behavior in response to the off-season. We propose the following hypothesis:

Hypothesis 2₀: Openness does not mediate the relationship between a collaborative organizational culture and employee innovative behavior in response to off-season challenges.

Hypothesis 2_a: Openness mediates the relationship between a collaborative organizational culture and employee innovative behavior in response to off-season challenges.

Traditional culture and openness. A traditional organizational culture is grounded in an established set of norms, customs, values, and traditions, to retain old practices and working procedures (Farh et al., 1997; Farh et al., 2007; Hon et al., 2014; Hon et al., 2015; Schwartz, 1992). A strict vertical chain of command, a rigid hierarchy, a high-power distance, and formalized rules and regulations are the main aspects of traditional culture. In such an environment, employees with high openness face challenges from conservatism, and the strict hierarchical structure influence their opportunity to be innovative. Research has suggested that traditional culture is negatively related to employee creativity (Hon et al., 2014; Hon et al., 2015; Hon & Leung, 2011). A traditional culture restrains employees from moving further and instead pushes them to follow conventional forms of performance. Consistently, studies have argued that the relationship between employee openness and traditional culture is negative (Gao & Shi, 2010; Ma et al., 2008).

Because a traditional culture attempts to pursue old practices and leaves less room for exploring new ideas and procedures, it works against any employees’ openness triggered by devotion and an eagerness to explore new working procedures. Furthermore, this incongruence between traditional culture and employee openness will decrease employees’ innovative behavior within organizations. According to approach-avoidance motivation and regulatory focus theory, a traditional culture hinders employees’ openness to working creatively because it triggers their avoidance motivation. In response, they will adopt a regulatory prevention strategy toward the off-season. To avoid individual losses and mistakes, that avoidance-prevention process will decrease employees’ willingness to perform innovative behaviors. Accordingly, we expect that employee openness negatively mediates the relationship between traditional culture and employee innovative behavior in response to the off-season.

Hypothesis 3₀: Openness does not mediate the relationship between a traditional organizational culture and employee innovative behavior in response to off-season challenges.

Hypothesis 3_a: Openness mediates the relationship between a traditional organizational culture and employee innovative behavior in response to off-season challenges.

The Regulatory Process of Employee Resistance to Change

Innovative culture and resistance. Resistance arises from psychological, situational, and dispositional traits that lead to individuals’ intentions to oppose change and progressive actions. In turn, those intentions obstruct employees from creating and implementing new ideas (Hon et al., 2014; Hon & Leung, 2011). An innovative organizational culture requires employees to explore new methods, even by taking risks at the workplace, and it counteracts employees’ resistance. It is clear that innovation is associated with change, creativity, and moving beyond traditional practices (Dobni, 2008), and it encourages employees’ intention to change the status quo. A study by Kauppila et al. (2010) supported the contention that salespersons became reluctant to sell new products due to their resistance to uncertain situations. Consistent with that, previous studies found that employee resistance to change related negatively to an innovative environment (Heidenreich & Kraemer, 2016; Madrid-Guijarro et al., 2009) and stemmed from risk aversion and resistive behavior (Kumar & Raghavendran, 2015; Lundy & Morin, 2013; Madrid-Guijarro et al., 2009).

Because resistance to change is irreconcilable with an innovative culture, organizations can face baffling and recalcitrant situations created by their employees’ resistance. In response to seasonality, employees may become resistive to utilizing new ways and alternative mechanisms. They may even lead them against mitigating the off-season market challenges by employing innovative selling methods or processes. Thus, these employees will not exhibit innovative behaviors to curb off-season market challenges. Drawing from approach-avoidance motivation and regulatory focus theory (Senbeto & Hon, 2019), we expect that employees with high resistance will be driven by avoidance motivation and adopt a prevention strategy in response to off-season markets. As a result, to avoid making errors and uncertainties, resistant employees will perform at low levels of innovative behavior. For such a situation, we examine the mediating role that employees’ resistance to change has on the linkage between an innovative culture and employees’ innovative behavior in response to the off-season. Consequently, we have the following hypothesis:

Hypothesis 4₀: Resistance does not mediate the relationship between an innovative organizational culture and employee innovative behavior in response to off-season challenges.

Hypothesis 4_a: Resistance mediates the relationship between an innovative organizational culture and employee innovative behavior in response to off-season challenges.

Collaborative culture and resistance. A collaborative organizational culture is principally based on the employees and thereby represents bottom-up organizational mechanics and mutual interaction among employees in the workplace. By promoting best practices and learning, a collaborative culture intends primarily to promote the continuous sharing of ideas and cooperation. It facilitates an arena of relationships and community belonging among an organization’s members (Hon & Leung, 2011). However, employees’ resistance to change hinders a collaborative organizational culture because such resistance exhibits a low level of willingness to engage in a participatory work environment. Individuals who are high in resistance prefer to pursue routine tasks, and they show reluctance, keep old habits, and exhibit rigidity toward cognition and emotional reactions. Hence, employees’ resistance to change inhibits innovative behavior (Hon et al., 2014).

From approach-avoidance motivation and regulatory focus theory, employees’ resistance behavior stems from an avoidance reaction to cultural situations, and such employees focus strongly on self-control by executing on their supervisors’ trickle-down approaches and adopting a regulatory prevention strategy. Battistelli et al. (2013) asserted that job-related feedback compromises employees’ dispositional resistance toward change. Research has noted that resistance can hamper the cooperative environment in an organization and negatively affect employee creativity (Battistelli et al., 2013; Hon et al., 2014). Although it is believed that employees can develop innovative behavior through collaboration (Emden et al., 2006), motives of resistance may inhibit workers from such cooperation in knowledge sharing and skills exchange. In such a situation, resistance hinders the cooperative environment and impedes employees’ collaborative efforts to develop new market approaches during the low season. Thus, we predict the following.

Hypothesis 5₀: Resistance does not mediate the relationship between a collaborative organizational culture and employee innovative behavior, in response to off-season challenges.

Hypothesis 5_a: Resistance mediates the relationship between a collaborative organizational culture and employee innovative behavior, in response to off-season challenges.

Traditional culture and resistance. Unlike the cases with innovative and collaborative cultures, employee resistance reconciles with a traditional organizational culture because the traditional culture is grounded in a formalized work structure, and it promotes a safe and cautious attitude toward risks and uncertainties. According to Schwartz (1992), traditional culture is associated with values and norms that demonstrate commitment and respect and exhibit an inherited recognition of old beliefs and practices. A traditional culture exhibits a strict vertical chain of command, rigidity, and requirements of acceptance and commitment to superiors, leading employees to pursue existing rules and prescribed code of conduct (Hon et al., 2014; Hon & Lui, 2016). In a traditional culture, the organization’s overall structure adheres to rules, regulations, and terms and conditions adopted from the past. Employees in this cultural environment strive to protect the firm’s traditions and preserve conservatism, and they tend toward defensiveness and resistance to new ways of doing things (Farh et al., 1997; Leong & Chang, 2003). These organizations generally pursue a bureaucratic approach and a higher level of hierarchical structure and maintain coercive leadership, all of which are practices that dampen employees’ inspiration to generate and implement novel ideas.

A traditional culture prefers to keep old practices rather than emerging applications and working styles (Farh et al., 1997; Leong & Chang, 2003). Employees become anxious about facing innovation because they associate it with risks and uncertainties. According to approach-avoidance motivation and regulatory focus theory, employees are motivated by taking an avoidance approach against change, alteration, progress, and development. They adopt a regulatory prevention strategy in response to the off-season market. Employees’ resistive behaviors are closely related to the traditional culture, and workers favor past thinking and practices (Erwin & Garman, 2010). Such an avoidance-prevention approach discourages any generation and application of innovative behaviors. Consequently, we propose that a traditional culture relates to employee innovative behavior via a regulatory resistance process.

Hypothesis 6₀: Resistance does not mediate the relationship between a traditional organizational culture and employee innovative behavior in response to off-season challenges.

Hypothesis 6_a: Resistance mediates the relationship between a traditional organizational culture and employee innovative behavior in response to off-season challenges.

Research Methods

Sample and Data Collection Procedures

A research team led by the first author collected data from employees and managers in hotels located in four different regions in Ethiopia: Addis Ababa, Bahir Dar, Hawassa, and Debrezeit. These cities have been recognized as having promising potential for tourism and hospitality markets (Senbeto, 2019, 2020). The survey questions were translated from English to Amharic (an official language in Ethiopia), and then two bilingual language experts checked the consistency of the translations. Full-time employees were invited to answer questions about their organizational cultures, the extent of their openness, and their resistance regulatory foci. In contrast, managers were asked to respond to organizational cultures and their subordinates’ innovative behavior items.

Using convenience sampling, a pilot study was conducted first, with 40 employees and 10 managers, to evaluate all question items’ quality and readability. The research team first contacted human resource managers in each hotel to seek their voluntary participation in our study and explain the research to investigate human resource practices for research purposes. With HR managers’ help, a paper-based questionnaire was distributed to employees and their supervisors or managers during working hours. To further alleviate social desirability issues, the research team was away from the data collection sites, and respondents answered the questions independently. Finally, the research team returned to each firm to collect the questionnaires, which were put into sealed envelopes to ensure confidentiality and privacy. We distributed 570 questionnaires in total from 48 hotels that ranged from 3-star to 5-star ratings. After deleting the missing cases, we ended with 479 valid samples for subsequent analysis (a response rate of 84%).

Measures

The questionnaire included the six major constructs proposed in Figure 1. A 7-point Likert-type scale was adopted for the respondents’ answers, ranging from 1 (strongly disagree) to 7 (strongly agree). Supervisors rated the employees’ innovative behavior, while both the employees and the supervisors rated the three organizational cultures. An independent sample t test to detect whether there were different perceptions between the employees and supervisors’ responses.

Innovative culture. We used Zhou and George’s (2001) four-item scale to measure the innovative organizational culture. Sample items were “Our company recognizes employees who utilize new thinking in their marketing tasks” and “In our company, leaders respect our innovative efforts.” An independent sample t-test result confirmed no significant difference between the employees’ and supervisors’ ratings on the innovative culture (t = 0.24, p > .05). The Cronbach’s α for this scale was .89. Average variance extracted (AVE) and composite reliability are .67 and .89.

Collaborative culture. We adopted a five-item scale developed by Podsakoff et al. (1997) to measure organizations’ collaborative culture. Sample items were “In our company, we support each other when another colleague fails in his/her marketing task during the off-season,” and “In our company, we share our marketing experience.” The results of an independent sample t test showed that there was no significant difference between the employees’ and supervisors’ responses on this construct (t = 0.19, p > .05). The Cronbach’s α for this scale was .91. AVE and composite reliability are .72 and .91.

Traditional culture. We used five items from Farh et al. (1997) to measure the traditional culture. Sample items were “We believe that managers’ decisions should be obeyed at all times,” and “We believe that to pursue a seniors’ track is the best way to avoid mistakes.” The results of an independent sample t test confirmed that there was no significant difference between employees’ and managers’ perceptions (t = 0.36, p >.05). The Cronbach’s α for this scale was .87. AVE and composite reliability are .63 and .87.

Employee openness. We used a six-item scale developed by Miller et al. (1994) to measure the extent of the employees’ openness. Sample items were “I look forward to the changes in my role that are brought by the implementation of work teams in response to the low season,” and “I perceive co-workers’ achievements as a positive implication to accomplishing my task.” The Cronbach’s α for this scale was .95. AVE and composite reliability are .71 and .95.

Employee resistance to change. We used a 15-item scale developed by Oreg (2006) to measure the extent of employee resistance to change. The scale was categorized into three dimensions: affective, behavioral, and cognitive resistance to change. The 15 questions drew from previous measures of dispositional resistance behavior used to gauge resistance to change (Oreg, 2003), and we modified some of the scales in accordance with the seasonality context. Sample items were “I feel stressed having to follow new marketing tactics during the low season” and “I presented my objections toward new ways of marketing strategies that I have to follow.” The fit indices for the three first-order factors and one second-order factor fell within an acceptable range (χ² = 183.30, df = 86, Tucker–Lewis index [TLI] = .97, comparative fit index [CFI] = .97, and root mean square error of approximation [RMSEA] = .049). Cronbach’s α for this scale was .96. AVE and composite reliability are .90 and .96.

Employee innovative behavior. We used a nine-item scale developed to measure employee innovative behavior. Employees’ supervisors were invited to answer questions about their subordinates’ innovative behavior. Sample items were “He/She works to generate a genuine solution to attracting guests during the low season,” and “He/She intends to generate original solutions for problems.” The Cronbach’s α for this scale was .91. AVE and composite reliability are .54 and .91.

Control variables. Previous studies have suggested that demographic variables and personality affect individuals’ innovative behaviors and their intentions to reject or accept change (Zhou & George, 2001; Zhou & Shalley, 2008). Thus, we controlled for age, gender, education, and organizational tenure. In addition, we controlled for the length of the employee-supervisor relationship (Van Dam et al., 2008). Last, we controlled for creative self-efficacy, because it is associated with innovative behavior.

Analytical strategy. We used the SPSS, structural equation modeling, and percentile bootstrapping analysis to test the data, and we applied Anderson and Gerbing’s (1988) two-step analytical strategy. We used confirmatory factor analysis to assess the measurement model. Based on our assessment of our model’s validity and reliability, we performed structural model analysis to examine the direct relationships among the constructs. Measurements and structural models results were evaluated based on fit indices (Byrne, 2016). Finally, we did a percentile bootstrapping analysis with 10,000 replications, for a 95% confidence interval (CI), to examine the mediating effects of employee openness and resistance to change on the relationships between organizational cultures and employee innovative behavior (Taylor et al., 2008).

Results

Descriptive Statistics

In our sample, 52.8% of the overall respondents were female, and 27.7% were from 18 to 25 years old, 59.7% were between 26 and 35, and the rest were 36 to 45 or older. The majority of the respondents had a college or university level education (82.7%), and the rest had either a postgraduate education or a secondary or high school level of schooling. In terms of jobs, 73.3% were from hotel sales and marketing, 18.3% were airport agents, and 8.4% were from guest relations services. Regarding organizational tenure, 64.1% of the employees had from 1 to 3 years of work experience with the organization, 14.4% had from 4 to 7 years, and the rest had worked for 8 to 10 years or longer.

Correlations

Table 1 presents the means, standard deviations, and correlations of all the constructs. As expected, employee openness was positively related to an innovative culture (r = .49, p < .01) and to a collaborative culture (r = .38, p < .01), and to employee innovative behavior (r = .47, p < .01), whereas openness was negatively related to a traditional culture (r = −.35, p < .01). Resistance to change was positively related to a traditional culture (r = .30, p < .01) but was negatively related to employee innovative behavior (r = −.34, p < .01), to a collaborative culture (r = −.23, p < .01), and to an innovative culture (r = −.28, p < .01). Employee innovative behavior was positively related to an innovative culture (r = .40, p < .01) and to a collaborative culture (r = .34, p < .01), but it was negatively related to a traditional culture (r = −.33, p < .01).

Table 1

Mean, Standard Deviations, and Correlations of Variables

Variable	M	SD	IC	TC	CC	OP	RES	EIB
1. Innovative culture	4.91	1.51	—
2. Traditional culture	2.96	1.36	−.47^**	—
3. Collaborative culture	4.93	1.47	.44^**	−.28^**	—
4. Openness	5.46	1.24	.49^**	−.35^**	.38^**	—
5. Resistance to change	2.44	1.22	–.28^**	.30^**	−.23^**	−.38^**	—
6. Employee innovative behavior	5.43	1.10	.40^**	−.33^**	.34^**	.47^**	−.34^**	—

Note: IC = innovative culture; TC = traditional culture; CC = collaborative culture; OP = openness; RES = resistance; EIB = employee innovative behavior.

Correlation is significant at the .01 level (two-tailed).

Measurement Model

The factor loadings for all the constructs including the second-order factors of employee resistance to change (affective, behavioral, and cognitive resistance) were higher than the cut-off point of 0.5 (Hair et al., 2010). Moreover, the t values were above the threshold of 1.96 with a 95% CI. The measurement model exhibits good fit indices (χ² = 1121.22, df = 881, p < .01, RMSEA = 0.024, goodness of fit index [GFI] = 0.903, TLI = 0.98, CFI = 0.98). To assess the discriminant validity, the proposed six-factor model was compared with the alternative models, which were a five-factor model and a one-factor model. The results indicate that the five-factor model resulted in an acceptable fit (χ² = 2238.93, df = 889, p < .01, RMSEA = 0.05, GFI = 0.79, TLI = 0.89, CFI = 0.9), but its chi-square, TLI, and GFI values were poorer than those from the proposed six-factor model. Finally, we tested the one-factor model by merging all the variables into a single grand latent factor. The results yielded a poorer fit (χ² = 10740.5, df = 899, p < .01, RMSEA = 0.15, GFI = 0.26, TLI = 0.28, CFI = 0.26). Results indicated that the proposed six-factor model achieved convergent validity with an AVE greater than 0.5 (Bagozzi & Yi, 1988), thereby indicating that the measurement items represented the intended constructs.

Tests of the mediating hypotheses. Figure 2 shows that both an innovative culture (β = .37, p < .01) and a collaborative culture (β = .18, p < .01) were positively related to employee openness, whereas a traditional culture was negatively related to employee openness (β = −.14, p < .01). Employee resistance to change was negatively related to an innovative culture (β = −.16, p < .05) and to a collaborative culture (β = −.12, p < .05), whereas it was positively related to a traditional culture (β =.19, p < .01). Employee innovative behavior was positively and significantly related to openness (β = .29, p < .01), and it was negatively and significantly related to resistance to change (β = −.16, p < .01). Table 2 reveals that the hypothesized model was better than the alternative models, because the χ² statistics indicate that the discrepancy between Model 3 (hypothesized) and Model 4 (an alternative) was not significant (χ² = 27, n.s.; Byrne, 2016). Table 2 also shows that the structural model received acceptable fit indices (χ² = 1150.33, p < .001, df = 881, RMSEA = 0.024, CFI = 0.98, GFI = 0.90, TLI = 0.98).

Figure 2

Proposed Model of Organizational Cultures and Employee Innovative Behavior in Response to Seasonality

Table 2

Summary of Model Fit Indices

Model Test	χ²	df	CFI	GFI	TLI	RMSEA
1. Independent model	14348.18	946
2. Measurement model	1121.22	881	.98	.90	.97	.024
3. Hypothesized model (Figure 1)	1150.33	881	.98	.90	.97	.025
4. Alternative model: additional direct paths from innovative, traditional, and collaborative cultures to employee innovative behavior	1177.11	885	.97	.89	.97	.027

Note: χ² values for the measurement and structural models are significant at p < .01. CFI = comparative fit index; GFI = goodness of fit index; TLI = Tucker–Lewis index; RMSEA = root mean square error of approximation; df = degrees of freedom.

To test the mediating effects, we performed percentile bootstrapping by utilizing a 10,000-replication bootstrap sample with a 95% CI to examine further the mediating effects of employee openness and resistance to change on the relationships between each of the three organizational cultures and employee innovative behavior (Taylor et al., 2008). Hayes’s (2013) procedures were followed to examine the CI for the lower and upper bounds, in order to assess whether the mediating effects of openness and resistance were significant. The results confirmed that openness had significant and positive mediating effects on the relationship between an innovative culture (indirect effect = .083, p < .05, 95% bias-corrected and accelerated CI [BCaCI; .040, .150]) and innovative behavior, and between a collaborative culture (indirect effect = .039, p < .05, 95% BCaCI [.016, .076]) and innovative behavior. Thus, Hypotheses 1 and 2 were supported, and the null Hypotheses 1₀ and 2₀ were rejected. In addition, openness negatively mediated the relationship between a traditional culture and employee innovative behavior (indirect effect = −.033, p < .05, 95% BCaCI [−.079, −.005]). Thus, Hypothesis 3 was also supported, and the null Hypothesis 3₀ was, therefore, rejected.

On the other hand, the results also supported that resistance to change had negative and significant mediating effects on the relationship between an innovative culture (indirect effect = −0.19, p < .05, 95% BCaCI [−.057, −.001]) and employee innovative behavior, and between a collaborative culture (indirect effect = − 0.14, p < 0.05, 95% BCaCI [−.044, −.001]) and innovative behavior. Thus, Hypotheses 4 and 5 were supported. The null Hypotheses 4₀ and 5₀ were, therefore, rejected. Finally, the results of bootstrap analysis also confirmed that employee resistance to change showed an inconsistent mediating effect (MacKinnon et al., 2007; Paulhus et al., 2004), in which adding resistance to change accelerated the negative impact of a traditional culture on innovative behavior (indirect effect = −.025, p < .05, 95% BCaCI [−.057, −.003]). Thus, the mutual negative influences of traditional culture and resistance to change further inhibited employee innovative behavior in response to the off-season. Hypothesis 6 was therefore supported. The Null Hypothesis 6₀ was rejected.

Discussion and Conclusions

Theoretical Implications

Coping with market inadequacy during off-season periods (Banki et al., 2016) and attempting to develop new markets and sustain existing ones are primary concerns for tourism and hotel enterprises. Studies have examined the push and pull factors that generate high- and low-seasonal demands for tourism products and services (see Amelung et al., 2007; Koenig-Lewis & Bischoff, 2005; Senbeto & Hon, 2019). However, several issues related to how tourism organizations can cope with seasonality still poses thought-provoking questions in the hospitality industry (Goulding et al., 2005; Koenig-Lewis & Bischoff, 2010). Moreover, existing tourism seasonality studies have mainly focused on aggregate demand and supply from the Western perspective, but economic and climatic variations are different in non-Western societies. Thus, a comprehensive seasonality study to understand the theoretical and practical gaps associated with seasonality features in tourism from non-Western perspectives is necessary (T. Chen & Pearce, 2012; Koenig-Lewis & Bischoff, 2005). To fill this gap, the current study incorporated approach-avoidance motivation theory and regulatory focus theory to examine the influence of organizational cultures on employee innovative behavior in response to the off-season.

Previous studies have paid considerable attention to macro-level aspects of seasonality. However, little attention is paid to the microlevel, like individual employees’ perspectives in response to seasonality (Goulding et al., 2005). The present study investigates two underlying regulatory mechanisms—employee openness as an approach-promotion focus and resistance to change as an avoidance-prevention focus—on the relationships between the three primary types of organizational cultures and employee innovative behavior in response to the off-season in hospitality industry. Furthermore, tourism researchers (Liu & Wall, 2006) have emphasized that inadequate attention has been given to human resource development in the tourism industry, especially in developing countries. Other studies have supported the concept that seasonality in tourism is less known in the context of developing countries (e.g., Banki et al., 2016; Koenig-Lewis & Bischoff, 2005; T. Chen & Pearce, 2012). We know that organizations in developing countries in places such as Africa rely strongly on employee innovative behavior to help them develop their hospitality markets and improve their service quality to offset seasonal shortages of demand. Thus, our study responds to the call for conducting seasonality research in developing-country settings.

Furthermore, the existing seasonality research has mainly focused on qualitative or case-based studies, with a limited understanding of theoretical and conceptual development (see T. Chen & Pearce, 2012; Koenig-Lewis & Bischoff, 2005). Our research model expands that understanding by using approach-avoidance motivation theory and regulatory focus theory to infer testable hypotheses on the relationships of organizational cultures and employee innovative behavior in response to seasonality. We also provide answers to help solve the parallel questions of when do hotels’ different cultures influence employee innovative behaviors in response to seasonality, and why do some employees perform innovative behavior, as a generative response, whereas others avoid it, as a resistance response. Our findings show that organizational cultures, which firms intentionally establish to achieve their business goals, can cause employees to be stimulated by approach or avoidance motivation and adopt either a promotion focus strategy or a prevention focus strategy toward their culture. These regulatory focus mechanisms can further promote or prevent employee innovative behavior in response to the off-season. Hence, this study offers mutual benefits to the hotel, tourism, marketing, and management fields to help them deal with seasonal market variation in a non-Western developing country setting.

Practical Implications

The present study offers practical implications to the literature on seasonality, especially in the hospitality and tourism industries. First, this study’s findings have implications for human resources, hotel management practices, and marketing strategies in a developing country, Ethiopia. Our results indicated those potential employees’ inclinations for and compatibility with a hotel’s organizational culture is important to know at the time of job recruitment and selection for human resource managers and tourism practitioners. For example, employees who exhibit openness are compatible with innovative and collaborative organizational cultures because they are more willing to develop, collaborate, and exchange ideas with others. In contrast, employees who resist change do not do well in an innovative culture and are comfortable with a traditional cultural environment. Thus, measuring potential employees’ attitudes and developing an understanding of their personal needs and psychological behaviors is an important task for managers and practitioners during employee recruitment and selection, as well as during worker training and development processes, in order to assess and capitalize on the compatibility between the organization’s business plan and employees’ acceptance levels.

Second, tourism organizations should be aware that the three different types of organizational cultures are not equally effective in fostering innovative behaviors in employees. When employees possess a high level of openness, they react positively to innovative and collaborative organizational cultures driven by an approach and promotion focus that will enhance innovative behavior. On the contrary, when employees have a high degree of resistance, they react most positively to traditional organizational culture and have a strong motivation toward an avoidance and prevention focus, leading them to perform at a low level of innovative behavior. This implication is particularly relevant to multinational hospitality firms that operate in different countries and have employees with varying regulatory foci.

Third, with the effect of seasonality and its consequent off-season market-related challenges, marketers need to consider strategies that assist them in managing seasonal variation, and they are wise to identify guests’ and tourists’ seasonal variation patterns. Also, marketers could view the current research framework and apply our findings in their business strategy to manage seasonal variation and identify international tourists’ and hotel guests’ seasonal variation. Concerning this, the results show that innovative, collaborative, and open environments have a higher possibility for marketing activities such as promotions, advertisement, and publicity to address off-season market challenges. Concerning that endeavor, this study suggests that innovative and collaborative organizational cultures and an open environment have a high proclivity for marketing activities, such as promotions, advertisement, and publicity, to address off-season market challenges. This study can provide input for policy makers in creating plans and business strategies to address seasonality from micro and macro perspectives.

Fourth, tourism managers need to support their employees to address the off-season market through high proclivity for marketing activities and customer satisfaction in time of off-season. For example, Alananzeh et al. (2015) found that high seasonality has several consequences on hotel employees regarding miscommunication, deviance, negative relationship, and conflict with coworkers during work hours. Innovative behavior helps employees understand and predict the extent of seasonal variation and showed readiness to assist the organization’s effort to curb off-season. In response to seasonality, employee innovative behavior helps them be aware of changing customer demand, building up psychological remedies, and confronting several working mechanisms. In such a vein, examples of employee innovative behavior in response to off-season includes familiarization with marketing mechanisms, addressing nonpeak season market demand, suggesting and facilitating alternative ways to ensure organizations’ objectives.

Furthermore, in combating resistance, managers need to communicate their proposed marketing mechanisms in considering employees’ awareness and organizations’ characteristics and past performance. In addition, it is preferable to support employees endeavor to express their thoughts by enhancing collaborative work environment in which employees could share their feelings and thoughts. Most important, to cope with employees’ resistance behavior, managers need to understand when change is compulsory to impede off-season market challenges by understanding a performance gap that deteriorates response to challenges like seasonality. Fostering collaborative work culture can be a better strategy to minimize resistance and uphold openness by enhancing interaction among coworkers, reward, promotional strategy, and appreciation of motivation, idea generation, and application. Motivating employees and creating a comfortable atmosphere to express what they think is a better means to encourage inspiration as it helps curb seasonality.

Last, based on our findings, prospective investors who may want to develop new markets in other cultural settings, first by guiding them in investigating the effects of seasonality on their upcoming hotel business, and second by providing specific information related to seasonality that can be helpful during preparation and actualization of hotel investment in developing countries and in different cultural settings.

Limitations and Directions for Future Research

This study had several limitations. Although it adopted multisource samples for our survey, obtained from both employees and managers, the research design was cross-sectional and therefore may not be able to solve the causality issue. Also, this study adopted a nonprobability sampling method to collect the data. We suggest that future studies examine the evolutionary relationships and developmental patterns among organizational cultures, employees’ regulatory processes, and employee innovative behavior, in the context of seasonality. Future research is also needed to replicate our findings using a probability sampling method and different cultural settings and other developing countries. We recommend that similar studies be conducted within segments of tourism organizations, such as with travel agents or tour operations and destination management organizations, to validate this study’s finding in tourism and hospitality contexts. For example, additional empirical studies are necessary to assess respondents’ roles in managing seasonality in different market destinations and tourism organizations in developing countries.

Moreover, to ensure our findings’ generalizability, we first suggest further exploration of different aspects of innovation, such as in various markets, services, products, processes, and technologies. For example, a future study using a holistic approach toward innovation with regard to seasonality is necessary. Second, we recommend field experiments to examine other mediating effects, such as the effects of efficacy (Michael et al., 2011), leadership (Pieterse et al., 2010), and supervisory or organizational support, on the relationship between organizational cultures and employee innovative behavior. Finally, we believe that future studies should combine a qualitative approach and on-site observation methods to explore seasonality’s macrolevel perspectives, using data from senior managers, tourists, and/or customers. Mixed research methods should provide another direction for seasonality research combined with constructivism and positivism, or postpositivism.

In summary, although seasonality is not a new topic in the tourism literature, it has been discussed from a one-size-fits-all approach. Unfortunately, that approach has many limitations in terms of conceptual and theoretical development, especially relating to how tourism organizations can solve the off-season issues in a competitive market. Drawing on approach-avoidance motivation theory and regulatory focus theory, this study examines the influence that the three primary types of organizational culture—innovative, collaborative, and traditional cultures—exert on employee innovative behavior via the regulatory mechanisms of employee openness and resistance to change. Our findings indicate that high levels of employee openness in conjunction with innovative and collaborative cultures foster innovative behavior and accelerate positive reactions to curb off-season problems. In contrast, employees’ resistance to change, in conjunction with a traditional culture associated with avoidance motives and prevention strategies, causes them to perform at a low level of innovative behavior in response to off-season challenges. Our empirical findings contribute to the industry’s knowledge about tourism seasonality and hospitality management in the context of developing countries.

Conclusion

In summary, considering the issue of managing seasonality in hospitality and the necessity of innovative behavior, this study examines the impact of innovative, collaborative, and traditional organizational culture on employee innovative behavior. We emphasize the importance of understanding regulatory focus propositions such as promotion and prevention approaches in addressing employee’s openness and resistance to change in response to seasonality. We answer a critical question concerning the type of organizational culture, personal, and psychological characteristics suggested to respond to seasonality in hospitality.

Footnotes

Acknowledgements

The authors would like to thank the Institute of International Business and Governance, established with the substantial support of a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (UGC/IDS16/17), for its support.

Authors’ Note:

ORCID iDs

Dagnachew L. Senbeto

Alice H. Y. Hon

Rob Law

Dagnachew L. Senbeto (e-mail: dsenbeto@ouhk.edu.hk) is a research assistant professor at the Lee Shau Kee School of Business and Administration at the Open University of Hong Kong, Kowloon, Hong Kong. Alice H. Y. Hon (e-mail: alice.hon@polyu.edu.hk) currently works at the School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Kowloon, Hong Kong, SAR. Rob Law, PhD (e-mail: rob.law@polyu.edu.hk), is a professor of technology management in the School of Hotel and Tourism Management at The Hong Kong Polytechnic University, Kowloon, Hong Kong, SAR.

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