Uncovering Innovativeness in Spanish Tourism Firms: The Role of Transformational Leadership, OCB, Firm Size, and Age

Abstract

Innovativeness in the tourism and hospitality sector is essential for competitiveness and survival. Leadership plays a key role in promoting (or hampering) firm innovativeness. This article intended to examine the role of transformational leadership (TL) and organization citizenship behavior (OCB) on Spanish tourism firms’ innovativeness (OI). It also investigated whether firm size and age moderate the relationship between TL, OI, and OCB. The cross-sectional survey method was used to collect data from 329 middle-level managers in Spanish tourism firms. The findings of the data revealed that TL and OCB have significant impacts on firm innovativeness; also, OCB mediates the relationship between TL and firm innovativeness. Firm size and age moderate the relationship between TL and firm innovativeness; also, firm size moderates the relationship between TL and OCB. It was found that large firms were more innovative than small ones; also, younger firms showed a higher level of innovativeness than old firms. Managerial and specific firm size and age implications were provided.

1. Introduction

Tourism and hospitality firms maneuver in an exceptionally competitive market characterized by continuous transformation [1]. In the tourism and hospitality industry, firm competitiveness depends on the level of innovativeness in terms of high quality and low cost production of their services, which meet or exceed customer need with a certain level of newness and sophistication [2]. Trends suggest that tourism as an industry can be attributed to immense innovativeness throughout history [3]. For instance, Disney Corporation’s magic idea that built the magical real-world counterparts to the fantasy lands depicted in Disney’s movies. The novel combination of movie and media-unified theme parks attract hundreds of thousands of locals and tourists around the world [4]. Raymond Alber Kroc of McDonald’s revolutionized the business of fast food to such an extreme that the conceptions developed are obliged as inspiration for the catering world [5]. The “Formule 1” concept of accommodation introduced by the “Accor Hotel chain” offers all essential and compulsory (such as accessibility, cleanliness, and comfortable beds) hotel standards at low prices, and represents a generic innovation [6].

Tourism destinations have also introduced far-reaching innovations to enhance tourists’ experience and let them feel the uniqueness [1,7]. Clydesdale [8] has identified a series of innovations that added value to customer experience, such as snowboard parks, tubes, snow biking, skiing, navigational games, dog sledding, and other accessories that help in the development of memorable experience. However, it has been claimed that innovation research has been applied to tourism and hospitality to a minimal extent, and the empirical test of said phenomenon is modest [1,2,3,9,10,11]. In line with this reasoning, we seek to study innovation in the tourism and hospitality sector by investigating the relationships between transformational leadership (TL), organization citizenship behavior (OCB), firm size, firm age, and the innovativeness of tourism firms.

Kent, Crotts [12] argued that TL “occurs when one or more persons engage with others in such a way that leader and followers raise one another to higher levels of motivation and morality.” TL style is defined as a leadership approach that causes a change in social systems, organizations, and individuals [13]. Bass [14] described TL as a mix of charisma, inspirational motivation, intellectual stimulation, and individualized consideration. Charisma arouses and inspires followers to achieve extraordinary goals [15,16]. Transformational leaders communicate a vision that inspires the followers to perform with creativity and achieve more than expected [17]. The inspirational motivation component of TL posits a leader as a role model that provides an emotional appeal to increase understanding and consciousness of shared goals among the followers [13]. The intellectual stimulation component of the TL motivates followers to think critically, find new solutions to old problems, and introduce new ideas for creativity [18,19]. Individual consideration focuses on followers’ individual needs, abilities, and inspirations [20]. TL inspire and stimulate followers to achieve more than expected and, in the process, develop their leadership capacity [21]. Thus, TL style has been deemed to foster better employee relationships, provide opportunities for creativity, and boost changes [17], which may lead to improved innovation performance. This is likely to happen in the tourism and hospitality industry, but no studies provide evidence in the same sense.

More in detail, TL may affect innovation through the improvement of OCB, which is the “individual discretionary behavior, not directly or explicitly recognized by the formal reward system, and that in the aggregate promotes the effective functioning of the organization” (Organ [22]. Notably, OCB increases firm efficiency by enhancing coworker productivity through virtue of altruism [23]; for instance, experienced workers voluntarily help newcomers to perform their duties in the best possible way. OCB enhances managerial productivity [24] by the quality of civic virtue (provide valuable suggestions and new ideas) and avoiding complaints and creating problems (courtesy and sportsmanship). Trends show that at the firm level, OCB enhances performance and is positively related to the quality and quantity of output [25]. Researchers suggest that OCB enhances team effectiveness [23]. Research trends show that high performing firms have a higher degree of OCB [26,27]. Extant research indicates that OCB has positive antecedents on individual-level performance, such as performance evaluations [28,29], rewards [30,31], and career advancement [31,32]. Summing up, OCB is good for teams, firms, as well as for individuals.

Finally, it is worth mentioning that TL may be more or less effective depending on the structural characteristics of firms, such as age and size. Indeed, these characteristics reflect a firm’s availability of resources and prior experiences, which may impact the influence of TL style on firm performance (e.g., innovation) and citizens’ behaviors [33,34].

All in all, the research questions of the study may be summarized as follows:

• Does TL affect firm innovativeness? How?
• Does OCB mediate the relationship between TL and firm innovativeness?
• Do firm size and age moderate the relationship between TL and firm innovativeness?
• Do firm size and age moderate the relationship between TL and OCB?

Hypotheses are developed, and we test them based on a sample of 329 Spanish tourism firms that have been willing to answer our provided questionnaire. Tourism firms are operating in a highly competitive market [1], where innovativeness is considered a key to business sustainability. The findings of this study not only expand the literature on the relationship between TL, OCB, and firm innovativeness (OI), but also inform tourism firms that the transformational leadership style has the capability of transforming firm innovativeness capacity. The present research also found that TL helps to enhance OCB, whereas OCB characteristics motivate employees to come up with creative ideas and cooperate with coworkers; hence, improving firm innovativeness and the business sustainability of tourism firms. Besides, this research reveals that firm size and age also play a vital role in tourism firms’ innovativeness. Thus, this research recommends that TL and OCB development in tourism firms leads to the firm’s innovativeness, which results in high quality, low production cost, and to meet or exceed customer need with creativity. The development of new products, services, and creative thinking is necessary for achieving sustainability. Through innovativeness, firms can build more sustainable products, processes, and practices that benefit the firm and society at large. Thus, the firm can innovate towards sustainability through disruptive transformation. This study recommends that the adoption of TL and OCB practices in tourism firms will be an initiative towards innovativeness and a drive towards sustainable outcomes.

2. Literature Review

2.1. Transformational Leadership (TL), Organization Citizenship Behavior (OCB), and Firm Innovativeness (OI)

Leadership is the ability to influence the competence and motivation of individuals and groups towards achieving specific goals [15,35]. Leadership is essential for the success and innovativeness of a firm [15]. Leaders energize, sustain, and direct specific work-related behaviors in their followers to introduce new ideas, work creatively, and innovate [35]. Trends suggests that leadership is the most determinant factor affecting the innovativeness of a firm. Leaders influence the innovativeness process through effecting organizational culture, structure, strategy, resources, or reward systems, or directly influence follower behaviors through motivation and a sense of shared identity [36].

There are enormous theories of leadership; however, the most debated one is the TL theory. Burns [37] defined transformational leaders as one who “can lift followers from their petty preoccupations and rally around a common purpose to achieve things never thought possible.” The behavioral components of TL are categorized into four main components, namely, idealized (charismatic) influence, inspirational motivation, intellectual stimulation, and individualized consideration [38,39].

Idealized influence denotes the charismatic power of leaders that attract followers towards him/her by showing respect and trust to followers [40]. Besides, TL has high moral and ethical standards, and offers a vision, values, and wisdom to the followers, hence, engaging them on an emotional level. These sets of behaviors and actions make them a role model and deeply respected personalities for the followers. The idealized influence of transformational leadership motivates employees to develop confidence and pride for the organization [41]. Inspirational motivation encourages followers to perform beyond the expected level. TL provides ambitious future vision, motivates followers to perform challenging and high standard tasks, and emphasizes common organizational goals [42]. Intellectual stimulation means to inspire followers to think in an innovative way to solve the problems. Thus, in the presence of TL, employees become more creative, and take risks where it is required to solve organizational problems [43]. The individual consideration component of TL focuses on the individual needs of the followers, and listens to their concerns. Transformational leaders help their subordinates in career development and pay attention to the individual followers’ needs [44]. Thus, transformational leadership is a process that transforms and changes followers’ behavior toward an organization in term of ownership, sense of belonging, thinking innovatively, taking risks to solve the problems, motivation to perform challenging tasks, and working as a team to achieve common goals. Besides, TL is concerned with assessing followers’ needs, motivation, satisfaction, and respect. These elements form an exceptional form of influence that encourages followers to accomplish tasks innovatively and perform more than what is expected from them [43].

In the tourism and hospitality sector, the most valuable and precious assets of an organization are the employees who satisfy and retain customers [45]. Tourists/guests assess the service quality of a tourism organization by evaluating their employees’ behavior. A delighted tourist/guest always expects employees to perform extra-role behavior besides the routine duties such as OCB. These are the behaviors that are not in the job description and rewarded by the formal organization system; however, it boosts the organization’s effectiveness and functioning [46]. OCB is a set of multifaceted discretionary behaviors not related to job contents [47]. OCB behaviors can be categorized as affiliative and challenging OCB [48]. The affiliative dynamics of OCB promotes teamwork, group cohesion, sustaining the current working relationship, and engagements [49]. Additionally, Choi [50] suggests that affiliative OCB consists of helping behaviors, civic virtue, organizational loyalty, and sportsmanship spirit. However, challenging OCB includes all “voluntary act[s] of creativity and innovation designed to improve one’s task or the firm’s performance” [47,49]. The empirical findings suggest that affiliative OCB is related to organizational leadership, trust-building, and organizational justice [51].

Research has identified various elements that affect OCB; however, leadership is found to be the most influential. The trends suggest that supportive leadership behavior directly and indirectly influence OCB. The spirit of transformational leadership is to encourage followers to move beyond the expected or set goals [47]. TL has significant impacts on followers’ extra job performance and OCB [49]. Inspirational motivation and individual consideration attributes of TL push the followers to achieve individual as well as organizational goals, keeping in mind the ethical and moral implications of their actions on the overall organization [52]. Thus, the support and development dimensions of TL inject OCB in the followers’ behaviors. Transformational leaders support their followers in their work-related decisions, openness to experiment, new ideas, and creativity; also, the development behaviors include identification of suitable training and coaching for the followers to enhance their job-related abilities and skills to enrich their self-confidence in accepting challenging tasks [34]. The research trends suggest that effective leadership strongly influences OCB [53]. Humphrey [54] indicates that organizational identification is a common factor between TL and OCBs. An accumulated amount of research provides support that TL positively affects employees’ work attitudes [55], organization commitment [56], and organizational citizenship behaviors [57].

Tourism firms operate in a competitive world where innovativeness is a condition for firms’ survival [1]. The tourism industry touches all the spheres of life within a country and is functioning in a global village, which is becoming borderless due to socioeconomic, political, technological, and informational progressions and developments [58]. These megatrends have changed the nature of international tourism, and demand tourism firms for a new vision, innovativeness, and new attitudes that what can and must be done to remain competitive in the industry; also, to delight tourists and contribute to the society economically, socially, culturally, and environmentally [59]. Thus, tourism firms’ competitiveness is contingent on their innovativeness in achieving high-quality products and services at lower costs to meet the demands of potential customers [1].

Research trends reveal that transformational leadership plays a vital role in the innovativeness of a firm [33]. Vaccaro, Jansen [60] found that transformational leadership is the antecedent of firm innovativeness (OI). The intellectual stimulation component of TL focuses explicitly on employees’ creativity and innovativeness. Transformational leaders motivate followers to experiment, take risks, and think outside of the box continuously for performing tasks and innovations. Ford [61] suggests that firm creativity and innovativeness depend on the leadership and argued that leaders who have concerns about the effectiveness of the present system promote consideration for instigating change, creativity, and dynamic capabilities. Transformational leadership attributes such as coaching, training, group cohesion, knowledge sharing, psychological empowerment, supportive behavior, and emphasis on extra-role performance all contribute to firm innovativeness.

All in all, TL is a determinant of creativity and innovativeness [17]. Transformational leaders deliver a vision to the followers, support innovations, encourage and provide autonomy, value, and acknowledge employees’ efforts, and also motivate them to perform challenging tasks [62]. Additionally, individualized considerations encourage the followers to perform extra-role behavior because the leader evaluates, rewards, coaches, and provides training according to the followers’ performance [28,29]. Research tendencies recommend that TL has a direct relationship with altruism [63]. Miao and Kim [64] empirically proved that TL has a direct positive association with three types of OCB, i.e., altruism, conscientiousness, and civic virtue. TL encourages followers to connect their personal goals with broad organizational goals; hence, they identify their success with values and norms [41]. Thus, we posit the following hypotheses.

Hypothesis 1.

TL positively influence OCB.

Hypothesis 2.

TL positively influence OI.

2.2. Organization Citizenship Behavior (OCB) and Firm Innovativeness (OI)

OCB is getting more attention in the tourism and hospitality sector due to an encouraging impact on customer satisfaction. OCB in the tourism and hospitality sector is a prevalent and favorable performance that allows employees to assist coworkers in offering high-quality services, work for lengthy hours, meet tough goals, and be loyal with the organization [65]. Employees’ prosocial behavior and delivery of excellent services make a customer delight. Thus, OCB is a key to increase revenues and a source of competitive advantage in tourism sectors, as the interaction between employees and customers lodged is high [66].

Organ [22] initially identified seven components of OCB construct, however, later combined them into five, i.e., altruism—can be defined as volunteer actions such as helping coworkers; courtesy—providing useful information and consulting colleagues before taking any action; conscientiousness—respect for norms and values; sportsmanship—not complaining about small problems and showing citizenship behavior; and civic virtue—constructive involvement in the matters that affect the organization. Podsakoff, MacKenzie [47] developed seven dimensions of OCB, i.e., sportsmanship, helping behavior, civic virtue, organizational loyalty, self-development, corporate compliance, and individual initiative. The trends suggest that Organ [22] five dimensions scale is dominant in the literature.

OI symbolizes organizational culture and climate that provide an environment and various supports for new ideas and product generation [67]. However, innovation is the outcome of OI in terms of new ideas, designs, methods, and products [68]. Lumpkin and Dess [69] suggest that “Innovativeness reflects the firm’s tendency to engage in and support new ideas, novelty experimentation and creative processes that may result in new products, services or technological processes.” Baer and Frese [70] suggest that OI consists of the organization’s activities that “produce visible and tangible innovative outcomes.” Wang and Ahmed [71] identified five areas of firm innovativeness, i.e., product innovation, market innovation, process innovation, behavior innovation, and strategic innovation. Additionally, suggesting that innovativeness is “an organization’s overall innovative capability to produce innovative outcomes.” Ruvio, Shoham [72] conceptualized firm innovativeness in five dimensions: Openness, risk-taking, creativity, future orientation, and proactiveness. The literature trends indicate that OI is a multidimensional construct that reflects an organizational culture and climate, which enables and facilitates idea generation, new product development, and promotes openness and creativity.

Chattalas, Koles [73] found that OCB supports innovations through readiness to help others, creating a friendly work atmosphere, and altruism for the firm and its members. Zhang, Wan [74] argued that OCB foster a high-quality organization and employee relationship. OCB motivates employees to dedicate themselves and contribute to the firm by introducing innovative ideas. Podsakoff and MacKenzie [23] reveal that OCB theoretically and practically improves organization effectiveness, as a high degree of OCB proactively involves employees in creative performance. Yan and Yan [75] indicate that the OCB “civic virtue” feature has a significant positive association with innovation in small businesses. Theoretical as well as empirical analyses suggest that OCB triggers a beneficial social climate that motivates employees to innovate [74]. Podsakoff, Whiting [76] claimed that OCB is positively associated with firm effectiveness, which supports the notion that OCB enhances firm innovativeness. Carmeli and Spreitzer [77] point out that OCB characteristics of altruism (helping others), courtesy (sharing knowledge), and civic virtue (constructive involvement) promote innovation and innovative culture in the firm. Xerri and Brunetto [78] believe that OCB, both at individual and firm level, leads to innovative behavior. Turnipseed and Turnipseed [79] indicate that the participatory paradigm of citizenship behavior has a positive influence on innovative ideas. Podsakoff, Whiting [76] argued that support for innovation is an antecedent of OCB.

The research on the relationship between OCB and OI is rare; however, OCB is a combination of such behaviors that help in the firm innovativeness. It can be derived from the literature that OCB boosts teamwork and encourages cooperation; besides, the civic virtue feature motivates employees to think constructively and innovatively. Hence, new ideas and information are shared within the organization to reduce costs and enhance the existing products and services to achieve organizational goals. Scholars believe that OCB improves team level innovations [80]. In tourism organizations, employees are in direct contact with customers/guests; he knows better how to solve the problems in due time with politeness. OCB represents the informal structure of an organization that shows its virtue of flexibility and openness, and Naqshbandi and Kaur [81] found that informal organization structure favors innovations. Organ [82] redefined OCB as “performance that supports the social and psychological environment in which task performance takes place.” Yu and Song [83] suggest that OCB, directly and indirectly, support innovations. Trends indicate the OI and OCB share common values such as openness of an organization to new ideas and change, which require individuals to be tolerant and respect other views and opinions. Thus, OCB, as a part of organization culture, develops a sense of pride in the organization members, and creates enthusiasm about what they are capable of doing to protect the organizational interest. OCB and OI both result in a positive organizational outcome [84].

Followers of transformational leaders feel a supportive climate for innovativeness and creative ideas. The individual consideration of TL provides encouragement and recognition to the followers, which serves as a reward for innovativeness [85]. Inspirational motivation encourages followers to generate new ideas and challenge the old method of work. The intellectual stimulation of TL enhances exploratory thinking and develops self-efficacy, which lead to higher creative performance [86]. TL increases psychological empowerment, which builds followers’ self-confidence and strengthens personal development [17]. TL followers are more likely to cooperate for a high contribution to the firm by supporting colleagues (altruism), provide creative ideas (civic virtue), obey firm rule regulations (conscientiousness), avoid corrupt practices (courtesy), and show tolerance to firm problems [87,88]. In addition, employees’ extra-role behavior is closely associated with firm effectiveness and efficiency [26,27]. Vigoda and Golembiewski [89] argued that OCB is necessary for the improvement of service quality and the creation of a healthy work environment. Hence, we posit the following hypotheses:

Hypothesis 3.

OCB positively influences OI.

Hypothesis 4.

OCB mediates between TL and OI.

2.3. The Moderating Role of Firm Size and Age

Literature trends suggest that the level of innovativeness is proportional to the firm size in the manufacturing industry [90]. Messeni Petruzzelli, Ardito [91] suggest that large firms have high capabilities to develop more valuable innovative solutions by using their experience and knowledge, whereas, the small firms can also innovate when their innovation is based on expertise and moderated by maturity. Research fosters that CEO TL has a direct impact on firm performance and innovativeness [92]; however, firm size indirectly contributes to the innovations [93]. Firm size has a significant positive influence on OI [94]. Hipp, Tether [95] analyzed empirical data of German service firms and found that the firm’s innovativeness increases with firm size. Jacob, Tintoré [96] examined the data of the tourism sector of the Balearic Islands, Spain, and found that large firms tend to innovate more than small companies. Their research suggests a massive difference between the number of innovations between small, medium, and large firms. Hipp, Tether [95] indicate that large firms have more lines of activity, finances, and human resources to innovate in a broader area. Cha, Kim [97] established a significant relationship between transformational leadership and inter-team collaboration and found that team size moderates the relationship.

The convincible moderating effect of firm size is drawn from the literature, indicating that firm size can act as a moderator in innovation research [98,99]. Khan, Rehman [93] found that firm size moderates the relationship between TL and OI, and argued that larger firms with sufficient resources could become more innovative than small firms. Little of the scholarship provides contradictory results and suggests that small firms are more engaged in innovation for survival [100]. To the best of our knowledge, the literature is silent about the moderating role of firm size between TL and OCB. However, based on the relationship between TL, OCB, and OI, it is assumed that firm size and age might moderate between TL and OCB. Concerning sub-sectors in tourism, Jacob, Tintoré [96] suggest that the accommodation and lodging sector is more innovative than leisure, recreation, and auxiliary services sectors. [90] found that Balearic hotel chain establishments in Mexico and the Dominican Republic indicate that hotels tend to be more innovative as the size increases. The trends advocate that large tourism firms’ economies of scale influence innovativeness probability. Sirilli and Evangelista [101] studied the relationship between a firm’s innovativeness and its size, both in the manufacturing and services sectors, and found that firm innovativeness behavior changes with size. Forés and Camisón [102] suggest that firm size indirectly influences innovation performance because it is associated with internal knowledge creation competences and absorptive capabilities. Orfila-Sintes and Mattsson [9] suggested that physical capacity, the number of beds, and room of the accommodation and hotel sector can prompt economies of scale, which guide the firms’ innovation decisions and its implementation. Thus, in tourism, facility size is a relevant variable in assessing the level of innovativeness of a firm. Chung and Kalnins [103] found that hotel size is positively related to the level of services and quality provided.

In addition to firm size, age is also a relevant structural factor at the firm level that influences the innovativeness of a firm Messeni Petruzzelli, Ardito [91]. Jacob and Groizard [90] found that new hotels are less innovative than older hotels. They established that the tendency to innovate per room increased as the age of the establishment increases. Hence, their results meet the theoretical expectation that “old is gold.” Firm age is an intangible asset as the firm gets old; it gets more experience and accumulates ownership advantages. Besides, the firm’s age influences the learning speed capabilities [91], recognization of knowledge value [104], and the capacity to take advantage of external knowledge resources [105].

The research on the relationship between a firm’s age and innovativeness is in a difference between scholars, as Chiaroni, Chiesa [106] suggest that older firms as compared to younger ones frequently fail to manage innovative activities due to change in the organization structure or technology. The economic perspective suggests that old firms are reluctant to accept new innovations for keeping the market stable; however, new firms always try to challenge the status quo by developing high impact innovations to draw new horizons in the market [107]. The organization’s inertia (organizational routines and organizational filters) perspective suggests that old firms are at a disadvantage as compared to the younger firms when they need to develop innovations based on new knowledge [91]. Whereas, organizational routines direct older firms to trust on established practices [108], and filters form a cognitive membrane that seizes corporate members to embrace innovative opportunities beyond the existing knowledge [7].

However, it is also a fact that older firms are more experienced, and their knowledge capabilities are much more mature than younger firms, hence, they develop more innovative services and products [109]. Older firms have more experienced human resources and long-lasting corporate memory that enhance their ability to evaluate the new knowledge to innovate and reduce the chances of misapplication [110]. The firm age and size are critical variables in organization studies, and an essential proxy to assess the organization process, knowledge management, innovativeness that change over time [105]. Thus, we considered firm size and age as a moderator for this study and posited the following hypothesis. Based on our hypotheses, we developed a conceptual model of this study, as given in Figure 1.

Hypothesis 5.

Firm size moderates the relationship between TL and OI.

Hypothesis 6.

Firm age moderates the relationship between TL and OI.

Hypothesis 7.

Firm size moderates the relationship between TL and OCB.

Hypothesis 8.

Firm age moderates the relationship between TL and OCB.

3. Methodology

The main aim of this study is to examine the mediating role of organizational citizenship behavior (OCB) between transformational leadership (TL) and firm innovativeness, and also investigate the moderating role of organization size and age between TL and OI.

3.1. Industry Setting

We chose Spanish tourism firms because Spain is one of the top ten tourism destinations in the world. Additionally, Spain has attracted 82.77 million tourists in 2018, 81.869 million in 2017, and 75.315 million in 2016 [111]. Spain has also moved to the second position in the world’s tourism ranking as the most popular tourist destination [112]. Spain’s organization SEGITTUR, a department for the Tourism Ministry, began to develop the concept of smart tourism destinations in 2012 and is helping turn Spain into a pioneer of sustainable tourism, and is the first to publish certification norms for identifying smart destinations [113]. The examples of smart tourist destinations in Spain are Gandia Valencia, Castelldefels, El Hierro, Haro, La Gomera, Playa de Palma, Badajoz, La Axarquía (Málaga), Jaca (Huesca), Las Palmas de Gran Canaria, Santiago de Compostela, and Villajoyosa.

3.2. Sample

This study applied a cross-sectional design for the collection of data. The stratified sample technique was used based on firm size [102,105]. The number of employees employed determined the size of the firm. Following the definition of the European Union [102] of small, medium, and large firms, the population of the firms were categorized into three groups (small < 50, medium < 250, and large ≥ 250 employees). A simple random sampling procedure was used. The firm population consists of tourism firms, tour operators, travel agencies, lodging and accommodation, restaurants, transport companies, recreational and leisure firms, attraction management firms, tourism destinations and management offices, and hotels.

The study population is comprised of middle management. The reason for choosing this specific group was their role as subordinates and leaders. The data were collected from different cities of Spain, such as Granada, Jaén, úbeda Tarifa, Baeza, Baleares, and Málaga. A total of 800 questionnaires were distributed face to face, through emails, and WhatsApp with a self-explanatory letter. The survey was conducted during July, August, and September 2019. All the respondents were assured about the privacy issues, and that data would be used only for research purposes. At the end of September 2019, we received a total of 329 complete questionnaires (a 41.12% response rate). Furthermore, care was taken to collect the data from each firm once. Approximately, there were 1,430,00 travel companies in Spain in 2019 [114], hence, our sample of 329 companies is around 0.23% of the whole market. The demographic features of the sample are given in

Table 1. Sample demographics.

Demographic	Frequency	Percentage
Gender
Male	183	55.6%
Female	146	44.4%
Education
Secondary	21	6.4%
Bachelor	56	17%
Master	141	42%
PhD	46	14%
Vocational training	65	19.8%
Firm Type
Government firms	114	34.7%
Semi government firms	62	18.8%
Private firms	153	46.5%
Firm Size
Small	122	37.08%
Large	207	62.92%
Firm Age
Young	110	33.43%
Average	116	35.26%
Old	103	31.31%

, showing that 55.6% of the respondents were male, and 44.4% were female. The majority of the respondents have a higher degree of education or received professional training. Besides, the maximum number of the respondents belonged to private owned firms followed by government and semi-government firms. The firm size shows that 62.92% of firms were large and 37.08% small; however, according to the defined criteria, none of the firms fall in the medium-size category. Table 1 provides some statistics about the sample.

3.3. Measurements

3.3.1. Transformational Leadership (TL)

The literature on leadership suggests that TL is the combination of charismatic influence [40], intellectual stimulation [43], inspirational motivation [42], and individual considerations [44]. Researchers have used multi-item TL measures with different scales [15]. This study adopted a nine-item measure of TL on a Likert scale (where 1 stands for strongly disagreed and 5 for strongly agreed). The scale was adopted from Hongdao, Bibi [15] study.

3.3.2. Organization Citizenship Behavior (OCB)

OCB is the desirable actions that an employee exercises to enhance the overall organization performance. Researchers have used multi-item OCB measures with diverse scales. This study adopted eight items scales from the existing literature [115,116,117]; however, care has been taken to include all the essential components of OCB, such as altruism (e.g., “I willingly give my time to help others with work problems”), courtesy (e.g., “I show genuine concern and courtesy toward coworkers, even under the most trying business or personal situations”), sportsmanship (e.g., “I assist others with their duties”), civic virtue (e.g., “I keep up with developments in the company”). The items were measured with a five-point Likert scale (where 1 stands for strongly disagreed and 5 for strongly agreed).

3.3.3. Firm Innovativeness (OI)

Firm innovativeness is the firm capability to introduce new ideas, processes, and products. Trends suggest that researchers refer firm innovativeness to its openness, risk-taking, creativity, proactiveness, and future orientation (Ruvio, Shoham [72]. This study adopted an eight items measurement on five points Likert scale (where 1 stands for strongly disagreed and 5 for strongly agreed) from existing literature [72,118,119].

3.3.4. Firm Size

This study measures firm size by the number of persons employed by an organization. All those firms were considered small firms who have employed 50 ≤ employees, and those who employed 250 ≥ employees were considered large firms. Small firms were coded as “0” and large as “1”.

3.3.5. Firm Age

Firm age was measured in years; however, three different categories were developed, i.e., younger, average, and old. Whereas, younger was considered those who fall within the range of “1–20 years”, average “21–30 years”, and old “31 years and above”. Younger firms were coded as “1”, average as “2”, and old as “3”.

3.3.6. Estimation Procedure

The screening protocols such as missing, outliers, unengaged responses, and normality of the distribution were performed. We performed several methods for scale purification; (a) exploratory factor analysis [120], (b) confirmatory factor analysis [121], and (c) common method bias [122]. Various regression analyses have been performed to examine mediation and moderation analyses.

4. Results

4.1. Exploratory Factor Analysis (EFA)

First, an EFA was performed with fixed three factors; all those items whose communality values were less than 0.4 were excluded. In the next step, all the items which were high loadings on various factors were excluded. After deletion, five items (TL1, TL3, TL5, TL7, TL9) from TL measurement, three items (OCB1, OCB4, OCB6) from OCB measurement, and four items (OI2, OI4, OI7, OI8) from OI measurement, and we retained four items of TL, five items of OCB, and four items of OI scale. The KMO value (KMO = 0.798) is greater than 0.6, indicating sample adequacy, and all the individual KMO were found higher than 0.7, and Bartlett’s test of sphericity was χ² (78) = 1581.038 p = 0.00. Hence, KMO shows that sample size is suitable for factor analysis, and Bartlett’s test of sphericity indicates that the correlation structure is adequate for factor analysis. The Cronbach’s Alpha values for all three constructs were higher than 0.60, indicating the internal scale consistency. All three factors collectively explained 60.336 % of the variance. The detail of the exploratory factor analysis is provided in

Table 2. Exploratory factor analysis.

Items	Factor Loadings			Individual KMO	Variance Explained	Reliability
	TL	OCB	OI			Cronbach’s Alpha
TL2	0.920			0.890	24.144	0.904
TL4	0.920			0.815
TL6	0.884			0.788
TL8	0.794			0.825
OCB2		0.788		0.768	21.565	0.801
OCB3		0.752		0.802
OCB5		0.745		0.810
OCB7		0.602		0.764
OCB8		0.609		0.795
OI1			0.754	0.832	14.628	0.763
OI3			0.740	0.713
OI5			0.709	0.758
OI6			0.718	0.812

Note: Cutoff KMO = 0.6 and Cronbach’s Alpha cutoff = 0.7.

.

4.2. Confirmatory Factor Analysis (CFA)

We conducted a set of CFA to examine the construct validity and model fit. All the experiments were performed in AMOS 24. First, we performed a baseline CFA model (Model 1) comprised of all the main variables of the study, i.e., transformational leadership (TL), organization citizenship behavior (OCB), and firm innovativeness (OI). The estimated model fit indices for Model 1 are given in

Table 3. Model fit indices.

Model Fit Indices	Model 1	Model 2	Model 3
CMIN/df	1.050	8.374	10.398
P-value for model	0.370	0.000	0.000
CFI	0.998	0.691	0.600
TLI	0.997	0.624	0.520
GFI	0.970	0.637	0.699
AGFI	0.956	0.673	0.579
SRMR	0.016	0.070	0.080
RMESA	0.012	0.150	0.169
PCLOSE	0.999	0.000	0.000

Note: CMIN/df < 3 good, p-vale for model > 0.05, comparative fit index (CFI) > 0.95 great; 0.90 > traditional; 0.80 permissible, cutoff Tucker–Lewis index (TLI) > 0.95 good, cutoff goodness of fit index (GFI) > 0.95, cutoff, adjusted goodness of fit index (AGFI) > 0.80, cutoff standardized root mean square residual (SRMR) < 0.08, root mean square error of approximation (RMESA) < 0.05 good; 0.05–0.10 moderate; > 0.10 bad, p-value for test of close fit (PCLOSE) > 0.05.

. We also performed calculations for Model 2 and Model 3 to compare it with the proposed baseline model. Model 2 was a two-factor model, where TL and OCB were combined in a single factor. Besides, in Model 3, all TL, OCB, and OI were combined in an only factor to form a large factor. All three models were estimated based on the maximum likelihood method.

Table 3 suggests that all of the overall goodness-of-fit indices indicated that the baseline model with three-factor does fit the data well: χ²(61) = 64.045, p = 0.370, CMIN/df = 1.050, comparative fit index (CFI) = 0.998, Tucker–Lewis index (TLI) = 0.997, goodness of fit index (GFI) = 0.970, adjusted goodness of fit index = 0.956, standardized root mean square residual (SRMR) = 0.016, root mean square error of approximation (RMESA) = 0.012, and p-value for test of close fit (PCLOSE) = 0.999. The CFI value suggests that the variables are highly correlated as a result; our model is better than assuming they are uncorrelated. GFI and AGFI indicate the amount of variance and covariance explained by the total model. SRMR suggests that our model captures the data well, and it is highly fitted [123]. RMESA indicates that how much a model is a close fit in relation to the degree of freedom [124].

For validating the model measurements, we estimated the composite reliability (CR), average variance extracted (AVE), mean shared variance (MSV), and average shared variance (ASV). The detail of various validities and reliability are given in

Table 4. Composite reliability, convergent and discriminant validity of constructs.

Construct	CR	AVE	MSV	ASV	MaxR(H)	TL	OCB	OI
TL	0.908	0.715	0.0225	0.0121	0.927	0.845
OCB	0.789	0.529	0.0441	0.0333	0.806	0.627	0.727
OI	0.821	0.534	0.0441	0.0229	0.586	0.543	0.601	0.730

Note: cutoff composite reliability (CR) > 0.7, convergent validity (CV); average variance extracted (AVE) > 0.5 or CR > AVE, DV; square root of AVE > factor correlation or AVE > mean shared variance (MSV) or AVE > average shared variance (ASV).

. The values of CR for each construct is greater than 0.7, hence, indicating construct reliability. We have performed various checks for convergent validity (CV), as AVE > 0.5 for all the constructs; therefore, we have convergent validity; additionally, CR > AVE, which also indicates convergent validity (CV). We also performed various checks for discriminant validity (DV), as the square of AVE (bold diagonal) values were greater than any factor correlation, hence, indicating discriminant validity. Besides, the values of AVE > MSV and AVE > ASV; thus, both were indicating the discriminant validity.

We performed a common method bias for examining how much variance a single factor explains. “Common method bias is the spurious variance associated with the measurement method” [15]. Harman’s single factor method was applied to examine how much of the portation of total variance was a single factor [15]. The results suggest that a single factor explained 26.125% of total variance explained, which is less than 50%, hence, revealed that the data did not suffer from common method bias. Finally, we extracted factors scores for conducting various regression analyses.

4.3. Hypotheses Testing and Regression Results

This study was examining the relationship between transformational leadership (TL) and firm innovativeness (OI) through organization citizenship behavior (OCB). OCB was used as a mediator; additionally, firm size and age were used as moderators between TL and OI. We used Andrew Hayes SSPS process macro [125] to test the mediation and moderation. The descriptive statistics and correlation between the variables are given in

Table 5. Descriptive statistics and correlations (N = 329).

Variables	Mean	SD	1	2	3	4	5	6
TL	3.618	0.438	1
OCB	3.278	0.461	0.627 *	1
OI	3.813	0.591	0.543 *	0.601 *	1
Age	1.978	0.805	0.004 **	−0.022	0.021 **	1
Firm Type	2.12	0.890	0.066	0.060	0.036	−0.666 *	1
Firm Size	0.629	0.484	0.056	0.025	0.502 *	0.720	0.120	1

Note: *, ** shows the significance level at 5% and 10%.

.

The correlation between the variables shows that there is a positive relationship between the variables (TL, OCB, OI) as expected; however, firm type and age are negatively correlated with each other. The correlation coefficients between the variables are less than 0.8; hence, we have no issue of multicollinearity. Researchers suggest that a correlation of less than 0.8 does not cause multicollinearity in regression analysis [126].

4.4. Mediation Analysis

Andrew F. Hayes’s process macro 3.1 in SPSS 23 was used to estimate the regression and mediation effects between TL, OCB, and OI. The regression results in

Table 6. Statistical results of mediation between TL, OCB, and OI.

					Bootstrapping
Paths	Coefficient	SE	t	Significance (p)	LLCI	ULCI
TL→OCB (a)	0.6290	0.0452	13.925	0.0000	0.5401	0.7178
OCB→OI (b)	0.4725	0.1049	4.5060	0.0000	0.2662	0.6788
TL→ OCB→ OI (c’)	0.2915	0.0881	2.6969	0.0074	0.0789	0.5042
TL→ OI (c)	0.5887	0.0881	6.6793	0.0000	0.4153	0.7621
Indirect effect	0.2972	0.0736			0.1647	0.4544
Moderation Model 1 (dependent OI)
Firm size	0.8363	0.0660	12.677	0.0000	0.7065	0.9661
Firm size x TL	0.5458	0.1428	3.8232	0.0002	0.2649	0.8266
Conditional Effects
Small firm size (0)	0.3981	0.1002	3.9737	0.0001	0.2010	0.5952
Large firm size (1)	0.9439	0.1017	9.2807	0.0000	0.7438	1.1440
Moderation Model 2 (dependent OI)
Firm Age	0.5066	0.2626	1.9290	0.0546	0.0734	0.9399
Firm Age x TL	−0.1367	0.0721	−1.8960	0.0589	−0.2557	−0.0178
Young	0.8592	0.0918	9.3617	0.0000	0.7078	1.0106
Average	0.7368	0.0624	11.802	0.0000	0.6338	0.8398
Old	0.6143	0.0878	6.9940	0.0000	0.4694	0.7592
Moderation Model 3 (dependent OCB)
Firm Size	−0.4986	0.3332	−1.4961	0.1356	−1.0483	0.0511
Firm size x TL	0.1689	0.0914	1.8474	0.0656	0.0181	0.3198
Small firm size (0)	0.5725	0.642	8.9210	0.0000	0.4666	0.6783
Large firm size (1)	0.7414	0.0651	11.381	0.0000	0.6339	0.8489
Moderation Model 4 (dependent OCB)
Firm Age	0.2578	0.2120	1.2159	0.2249	−0.0920	0.6076
Firm Age x TL	−0.0718	0.0587	−1.2232	0.2221	−0.1687	0.0250

were well inclined with our proposed hypotheses. The results suggested a significant positive relationship between TL and OCB (path a) with b = 0.6290, p = 0.0000 and an overall model fit F (1, 327) = 193.89, p = 0.0000 and R² = 0.3722, hence, providing support to H1. The results further suggested a significant positive relationship between OCB and OI (path b) with b = 0.4725, p = 0.0000 and an overall model fit F (2, 326) = 33.77, p = 0.0000 and R² = 0.1716, hence, supporting H3. The direct effect of TL on OI (c’) was significant b = 0.2915, p = 0.0000 with an overall model fit F (2, 326) = 33.77, p = 0.0000 and R² = 0.1716, hence, support hypothesis H2. The total direct effect of TL on OI (path c) is significant with b = 0.5887, p = 0.0000 and with an overall model fit F (1, 327) = 44.61, p = 0.0000, R² = 0.1201. The indirect effect was tested by using bootstrap estimation with 5000 samples and 95% confidence interval by implementing process macro 3.1, and the results suggested a significant coefficient of indirect effects with b = 0.2972 [95%, CI = 0.1638, 0.4447], hence, providing support to H4. The path diagram of the results is presented in Figure 2. The path diagram was developed through AMOS 24. The path diagram replicated the results of Andrew F. Hayes, and hence, suggested the robustness of our results, where e1 and e2 represent error terms, suggesting unexplained variance in the dependent variables.

4.5. Moderation Analysis

Four moderation models were performed through Andrew F. Hayes process macro 3.1 by choosing model 1 to examine the moderating role of firm size and age between TL and OI; also, the moderating effects of firm size and age between TL and OCB. The results are shown in Table 6. The interaction of firm size and TL was found significant with b = 0.5458, p = 0.0002 and confidence interval (95%, 0.2649, 0.8266), with an overall model fit F (3, 325) = 81.99, p = 0.000 and R² = 0.4308. The conditional effects of the predictor at a different level of the moderator (0= small firms, 1= large firms) suggested significant results. At a low level of moderation [conditional effect = 0.3981, t = 3.9737, 95%, CI (0.2010, 0.5952), p = 0.0001]. At a high level of moderation [conditional effect = 0.9439, t = 9.2807, 95%, CI (0.7438, 1.1440), p = 0.0000]. The results suggested that firm size is a positive moderator between TL and OI, hence, supporting H5. The interaction plots in Figure 3 were drawn one standard deviation below and one standard deviation above the mean to verify to what extent the interactions support hypothesis H5. Figure 3 suggested that both at small and large level firm size moderate the relationship between TL and IO; however, the moderated effects of firm size are high in large size firms.

The second moderation was performed for examining the moderating effects of firm age between TL and OI. The results in Table 6 suggested a significant interaction between firm age and TL with b = −0.1367, p = 0.0589 and confidence interval (90%, −0.2557, −0.0178) with an overall model fit F (3, 325) = 47.132, p = 0.0000 and R² = 0.3032, hence, supporting hypothesis H6. For detailed conditional effects, please see Table 6. The interaction plots in Figure 4 were drawn one standard deviation below and above the mean. Figure 4 suggested that young firms’ innovativeness increased with a higher level of TL than old firms. The data labels indicated that a high level of TL is more helpful in firm innovativeness in larger firms than younger firms. We checked the moderation for model 2 and 3 at 95%; however, we failed to extract significant moderation relationships, and thus increased the confidence interval to 90% and found significant moderation results for model 2 and 3. In social sciences, a 90% confidence interval is acceptable [127]. The confidence interval just shows how confident the authors are about the results of the study. The confidence interval is a conventional choice, and one is free to select a different number [128].

Moderation models 3 and 4 were conducted to examine the moderating effects of firm size, age, and TL on OCB. The results of model 3 suggest that the interaction of firm size and TL was found significant with b = 0.1689, p = 0.0656 and confidence interval (90%, 0.0181, 0.3198), with an overall model fit F (3, 325) = 70.38, p = 0.0000 and R² = 0.3938. The conditional effects of predictor at a different level of the moderator (0 = small firms, 1 = large firms) suggested significant results. At a low level of moderation [conditional effect = 0.5725, t = 8.9210, 90%, CI (0.4666, 0.6783), p = 0.0000]. At a high level of moderation [conditional effect = 0.7414, t = 11.3806, 90%, CI (0.6339, 0.8489), p = 0.0000]. The results suggested that firm size is a positive moderator between TL and OCB; hence, supporting H7. The interaction plots in Figure 5 were drawn one standard deviation below and one standard deviation above the mean to verify to what extent the interactions support hypothesis H7. Figure 3 suggested that both small and large level firm size moderate the relationship between TL and OCB; however, the moderated effects of firm size are high in large size firms.

The results of model 4 suggest that the interaction of firm age and TL was found non-significant with b = −0.0718, p = 0.2221 and confidence interval (90%, −0.1687, 0.0250), with an overall model fit F (3, 325) = 65.032, p = 0.0000 and R² = 0.3751. The results suggested that firm age is not a significant moderator between TL and OCB; hence, rejecting H8. The interaction plots in Figure 6 were drawn one standard deviation below and one standard deviation above the mean to verify that firm age does not play a significant role between TL and OCB.

5. Discussion and Conclusions

This study investigated the essential mechanism that explains how transformational leadership (TL) enhances firm innovativeness through the development of OCB in tourism and hospitality firms. This study represents the first attempt to investigate, (a) the mediation role of OCB in the relationship between TL and OI, (b) the moderating role of firm size in the relationship between TL and OI, TL, and OCB, and (c) the moderating role of firm age in the relationship between TL and OI, TL, and OCB. The findings of this study suggest that TL is a significant contributor to OI in the Spanish tourism firm. The results confirm our predictions regarding the effect of TL in predicting OCB and OI. The findings support the notion that TL influences firm innovativeness. The results suggest that TL directly explains 58.87% variation in firm innovativeness. The findings further indicate that OCB directly influences firm innovativeness by 47.25%. This study implies that TL through OCB explains firm innovativeness by 29.15%. The overall findings reveal that TL style enhances firm innovativeness, and the development of OCB in employees enrich this relationship. The interaction of TL and firm size indicate that firm size moderates the relationship between TL and firm innovativeness (OI) by 54.58%; in addition, large firms are more innovative than the small firms. The study demonstrates that firm age moderates the relationship between TL and OI by −13.67%, suggesting that old firms are less innovative than younger firms. The interaction of TL with firm size and age reveals that firm size moderates the relationship between TL and OCB by 16.89%; however, firm age does not moderate the relationship between TL and OCB.

5.1. Theoretical Implications

The critical contribution of this study to the existing literature is our attempt to bring TL, OCB, OI, firm size, and firm age into a single theoretical framework. Although, there are many studies on the role of leadership concerning innovative work behavior, firm performance, creativity, team innovation, and innovative climate [17,33,77,129,130], little attention has been paid to the firm overall innovativeness [3,72,131]. This study, for the first time, attempts the mediating role of OCB between TL and OI. This study provides empirical support to the leader-member exchange theory (LXM) and social exchange theory (SET). The social exchange theory suggests that employees who receive motivation and support from leadership are showing a high tendency toward creativity and productive activities for the firm [73]. Lee [132] found that leadership shows influence on firm innovativeness through LXM. This study also provides support to social information processing theory in an organizational setup by focusing on the support of TL for OCB, when employees receive help from the leadership and colleagues, they try to develop cooperative behavior and engage in creative work [133]. Our study contributes to the prior literature on the role of TL as a prominent leadership style contributing to firm innovativeness [72,119], creativity, OCB [47], performance [134], and innovation [85,94]. Additionally, this study provides support to the outcomes of OCB that have been identified as helpful in firm innovativeness [23,63,76]. This study goes beyond the previous studies by providing the empirical evidence that TL is conducive to OCB and firm innovativeness in the tourism and hospitality sector. This study reflects Gumusluoglu and Ilsev [17], who suggest that TL has a positive association with firm innovativeness. Additionally, we provide a mechanism for Jacob, Tintoré [96], who argued that innovation is a potential common phenomenon in Spanish tourism firms, particularly in the accommodation and lodging sector. Transformational leaders motivate followers to think creatively and find a solution to the problem in an outbox manner, and also support followers in their decisions, provide a future vision, motivate employees to perform high standard and challenging tasks, welcome new ideas, take care of individual needs (such as career development, training) and build self-confidence consideration [38,39].

Jacob and Groizard [90] suggested that the Balearics hotel chain in Spain and Latin American destinations should focus on the employees’ qualifications and training to keep pace with rapid innovation. This study also confirmed the findings of Li, Sajjad [42], who suggested that transformational leadership has a positive impact on the innovative behavior of employees. In addition, firm innovativeness is a continuous activity, not episodic, which has snowball effects over time; for instance, Martin [135] demonstrated that the creative use of the Internet in the tourism and hospitality firms provided an interactive interface between tourists and tourism suppliers. Thus, our study suggests that those employees who perceive high TL activities in the firms are highly motivated towards firm innovativeness. Jung, Wu [94] found that CEO transformational leadership has a direct positive influence on the firm’s innovativeness. Hence, it is concluded that firms who are high in TL would more probably tend to a higher level of firm innovativeness.

The empirical findings of this study suggested that TL has a positive influence on OCB. Podsakoff, MacKenzie [47] argued that the true spirit of transformational leadership is to influence the followers to go beyond expectations. This study confirms the findings of López-Domínguez, Enache [49], who suggested that TL has an essential impact on employee extra-role behavior and OCB. TL, through individual considerations (such as supportive and developmental leadership), motivates followers towards change-oriented citizenship behavior. Thus, the net effect on TL on the individual is to include proprieties among their needs, ambition for the achievement, and to perform extra-role activities to achieve self and organizational goals. Rafferty and Griffin [34] argued that TL shows several behaviors that enhance OCB, such as identification of training and coaching of the followers to encourage them to improve their job-related abilities and skills to build their confidence in undertaking a wide range of proactive tasks. Hence, the findings of this study about the relationship between TL and OCB are well in line with the literature.

In addition, the findings suggested a significant positive relationship between OCB and OI. The literature on the relationship between OCB and OI is rare. OCB is the employees’ constructive behaviors that influence organizational performance. Barnard [136] referred to OCB as “the willingness to cooperate,” and Katz and Kahn [137] named it as “innovative and spontaneous behaviors” [138]. Researchers also identified the individual initiative as one of the OCB components [47] that involves the engagement of an employee in task-related volunteer behavior that falls far beyond his/her duties [139]. Thus, in a sense, the roots of every organization’s citizenship behavior can be traced back to firm innovativeness. These pieces of literature provide theoretical support to our findings that OCB has a significant positive relationship with OI. Besides, OCB’s significant relation with TL and OI also offers strong support to our result that OCB mediates between TL and OI. Thus, it is suggested that tourism and hospitality firms high in TL and OCB tend towards higher firm innovativeness than those who are low in TL and OCB.

Moreover, the findings of this study suggest that firm size and age significantly moderate the relationship between TL and OI, TL, and OCB. Hipp, Tether [95] surveyed German service firms and found that the tendency to innovate increased with firm size. They further suggested that “this relationship is simply a reflection of the fact that larger firms tend to have more lines of activity and therefore, more areas in which to innovate.” Jacob, Tintoré [96] conducted a study of the tourism sector of the Balearic Islands, Spain and found that large firm tends to innovate more than small firms. Jacob and Groizard [90] found that Balearic hotel firms in Mexico and the Dominican Republic indicated that “hotels tend to be more innovative as size increases as measured by the number of hotel rooms. Large hotels showed higher innovation per room than small hotels.” These studies did not discuss the mechanism of how and why firm size matters, and besides, they used a simple percentage and did not offer any sophisticated methodology. Hjalager [2] suggested that large tourism firms are the center for innovation in tourism. Jacob and Groizard [90] suggested that besides the size, firm age also influences the firm level of innovativeness. Petruzzelli, Ardito [91] indicated that firm age is a determinant of firm innovative performance.

5.2. Managerial Implications

The findings of the present study demonstrated a significant relationship between TL, OCB, and OI in Spanish tourism and hospitality firms. This research offers several managerial implications to tourism and hospitality firms in general and specific in terms of firm size and age. First, the managers in Spanish tourism and hospitality firms should develop TL skills for ensuring firm innovativeness. The findings of the present study suggest that employees are inspired by leadership behavior in terms of individual considerations, future vision orientation, openness to new ideas, creativity, and supportive and developmental behavior that subsequently leads to firm innovativeness. Second, managers should focus on building organization citizenship behavior (as it leads to firm innovativeness) in the employees by providing proper training, coaching, organizing workshops, and seminars. Respect should be paid to the ideas and information shared by the employees; supportive leadership behavior is a key to OCB. A high level of attention should be paid to employees’ individual needs, which makes them satisfied with the job and inspires them to be committed and loyal to the organization. In addition, managers should focus more on the development of the civic virtue component of OCB for increasing innovativeness. Managers can use OCB as a tool for rewards, performance evaluation, and promotion; hence, it will help motivate employees to perform more than what is expected. It will also help in the creation of more ideas for innovations.

5.3. Firm Size and Age Implications

The interaction effects of firm size and TL suggested a positive impact on OI both in small and large firms; however, it was found that despite their flexibility, small-size firms are less likely to be innovative than large size firms. Small firms might face financial constrains in adopting innovations or might face challenges in the implementation due to a limited workforce. Tourism is a network-based industry; thus, it is suggested small size firms should take advantage of their regional network or suppliers; for instance, small size firms can form a partnership for sharing knowledge or develop a joint research and development collaboration for joint innovations. Besides, they can jointly hire tourism consultancy firms for developing new products, innovative processes, and improvement of quality. Small size firms can also use supplier networks, marketing channels, and customer feedback; for instance, a travel agency can use supplier knowledge and marketing channels to get knowledge about the market trends and opportunities available for innovations.

To gain knowledge about mega-industry trends, small size firms can purchase annually published information from national and international organizations. For instance, Simon-Kucher & Partners consultancy offers travel, tourism, and leisure published information. It also helps in product designing, pricing, Internet interface building, marketing strategy, and developing customer loyalty schemes. The mentioned implications are suitable for small size firms because of the knowledge gained from the external environment to innovative performance is easy because of their less complex structure. Besides, the internal and external flow of communication is freer in small firms than large-size ones; thus, it can easily identify the various dimensions of dissemination and, finally, the application components of new knowledge.

The large size firms have more resources and capabilities that allow them to extend their existing pool of knowledge. Managers in large firms should devote more effort and time to accumulate knowledge that prolongs the continuity of innovation arising from the consolidated researcher lines. However, the literature suggests that large firms have significant coordination and communication costs, less flexible organization structure, are slow to react, have less autonomy, and multi-layers organizational hierarchy often pose a threat to rejection of new ideas. Hence, it is suggested that large firms should use the available diverse human and capital resources for scientific and technological knowledge creation. Besides, to overcome the problems of complex organization structure, new business models should be developed that offer flexibility and adaptability to deal with changes in the external environment and stimulate knowledge creation. Large firms are advised to invest in the development of practices that promote coordination and communication between different parts of the organization and agents in the external environment; this would help in the establishment of a more flexible and organic organizational structure.

The interaction effects of firm age and TL suggested a positive impact on OI both in younger and older firms; however, it is found that despite their knowledge and experience, old firms have less firm innovativeness. Older firms have more experience, expertise, resources, and strong value networks, but less flexible organization structure; besides, younger firms have a flexible organization structure and are eager to innovate with a limited amount of expertise, value networks, and resources. The merits and demerits of both types of firms offer opportunities for collaborative innovation partnerships. Younger firms have strong competencies in focused areas that make them attractive for collaboration with older firms. Thus, it is advised that younger and older firms should form a network of alliances to joint innovations with complementary roles in the value chain, and such a kind of network would benefit both types of firms and open new business opportunities. Older firms should create technology platforms and recruit younger firms to develop products for these platforms, where older firms provide extensive technical and non-technical information, co-marketing opportunities, subsidies research, and development costs, and younger firms work on process and product design. Besides, younger firms who are the active users of new technologies may develop enhancements for these technologies that improve the capability and quality.

5.4. Limitations and Future Research

This study is based on a cross-sectional survey, which is the main limitation. Second, we did not use a set of control variables, such as the data of the study is collected from various cities of Spain, and the demographic factor may influence the respondent response. Third, the respondents were chosen from middle-level management to represent the firm; there is a risk of single-source bias. Fourth, we focused on a single industry; the results may not be representative of other sectors; hence, the results should be interpreted with caution. Fifth, we used a common method bias; the similarity of the method may inflate the observed relationships between the dependent and independent variables. In addition, we were unable to collect the data from medium-size firms. The scholars are suggested to use OCB various constructs such as altruism, civic virtue, courtesy, conscientiousness, and sportsmanship between the relationship of TL and firm innovativeness to identify the most influencing constructs. Further, it is suggested that a longitudinal survey should be conducted for comparison of samples at different times. Demographic variables should be used as a control to see whether they have any significant effects on the relationship.