Keywords

Introduction

Tourism activity has been the subject of debate in recent times due to its economic importance and the sustainability problems that this economic activity entails: CO2 emissions, excessive consumption and waste of water, energy, food and other resources due to practices and technologies unsustainable in the hospitality sectors (Bruns-Smith et al., 2015; Gössling et al., 2013; Hall, 2019; Koçak et al., 2020).

The debate is centered in the current underlying model of planning and growth (Hall, 2019; Higgins-Desbiolles et al., 2019; Sharpley, 2020) that has led to environmental degradation. Therefore, many companies face the inevitable pressure to adopt their business model based on the linear economy, to one based on the principles of the circular economy and to set economic and environmental goals.

The circular economy (CE) concept, which has attracted the attention of business and policy makers as a new approach to sustainability (Ellen MacArthur Foundation, 2015; European Commission, 2018), is supported by underlying restoration, regeneration, and re-use of resources principles. Viewed from a management perspective, the essence of a circular business model is to exploit business opportunities in such a way that a company can create value not only economically but also environmentally (Pichlak & Szromek, 2022).

Within tourism, the adoption of CE principles still needs further dissemination between scholars and practitioners (Manniche et al., 2021; Rodríguez-Antón & Alonso-Almeida, 2019). The progress towards a CE requires a significant transformation and many scholars emphasize the key role of green innovation in this regard (Sehnem et al., 2022; de Jesus & Mendonça, 2018).

In general, the innovations that are introduced in the tourism sector are fundamentally incremental (Lyons et al., 2007) and imply progressive modifications based on the reinforcement of existing knowledge and human interactions. These particularities about the nature of innovation in this sector suggest that the success in the formulation and implementation of green innovations depends to a large extent on human resource management and other people-driven factors. We propose that organizational culture plays a critical role in the successful implementation of circular business models and green innovations.

Advertising of green initiatives in the hospitality industry is abundant and growing but, nevertheless, there are few studies in this regard (Alonso-Almeida et al., 2016). Furthermore, evidence of the human side of these sustainability-oriented practices or their consequences is even more scarce with few exceptions (Sawe et al., 2021; Pham et al., 2023).

Therefore, to fill this gap in the literature on the opportunities of green innovation in the accommodation industry, we ask ourselves two questions: the first is whether green innovation allows hotel companies to improve their performance levels in economic and environmental terms; and the second, to what extent the existence of a robust organizational culture enhances the effect of green innovation on performance.

The remainder of this chapter is organized as follows. Section “Theory and Hypotheses” presents the theoretical background and hypotheses development, and then discusses the sample, data, and statistical procedures. Section “Data Analysis and Results” details the results of hypotheses testing, and the last section establishes the conclusions that are derived.

Theory and Hypotheses

Despite the multiplicity of terminologies (e.g. eco-innovation, sustainable innovation, environmental innovation, and others), there is a certain consensus in the literature towards the underlying meaning the concept, where all the definitions are usually focused on the improvements of environmental performance (Cai & Li, 2018). Green innovation in the accommodation industry refers to the development or modification of services, processes, organizational or marketing methods to contribute positively to the natural environment (intentionally or not) (Rennings, 2000). In fact, previous studies have considered that green innovation practices can positively and significantly affect the environmental performance of companies (Cai & Li, 2018; Asadi et al., 2020). In this sense, green innovation will improve and stimulate environmental performance because it allows adapting products and services to new sustainable demands, reducing emissions and the consumption of materials and energy, with a more efficient use of resources (Adegbile et al., 2017).

At once, one of the managers motivations for adopting green innovations is to help organizations attain a competitive advantage and achieve better economic performance (Font et al., 2017). Thanks to green innovation, it is possible to save on operating costs, improve the image of the company, comply with regulations and increase sales by serving new market segments (Quazi, 1999), in which they include consumers with a preference for sustainable products and more willing to pay a premium price for them. For these reasons, the effect of green innovation on economic performance has been studied in different research that have found a positive association between green innovation and performance.

The effect of green innovation in improving performance has also been the subject of analysis in the context of the tourism sector. Asadi et al. (2020) conducted research with a sample of 183 hotels in Malaysia and found that green innovation has a positive and significant influence not only on environmental performance, but also on economic performance. Accordingly, the following hypothesis is proposed:

  • H1: Green innovation affects corporate performance positively.

Tourism organizations are forced to continually reformulate their practices and processes as a consequence of the instability in which they carry out their activity (Nieves & Quintana, 2018). In this context, the employees are who promote and implement innovation (Lee & Hyun, 2016) since their direct interaction with the environment provides them with knowledge to identify areas that need improvement and can provide solutions to the problems of their company, their customers, and their environment (Karlsson & Skålén, 2015).

Organizational culture (OC) is defined as a set of beliefs and values shared by members of the same organization that influences the behavior of the company and its members as if they were unwritten rules (Cameron & Quinn, 1999). Consequently, OC is a powerful weapon that can be useful to promote creativity, risk taking, orientation towards results and the commitment of members to their company, reinforcing the organization’s capacity to achieve its innovative goals due to the greater understanding of these by its members and their commitment to them. In other words, OC is inextricably linked to how individuals interact and behave (Luthra et al., 2017), so having a culture that encourages employees to develop new ways of working that promote innovation and circularity is a factor that can determine the survival of a company (Heyes et al., 2018).

OC was discussed by the scholars in numerous contexts considering certain issues related to the role of culture in the success of green innovation. In tourism sector, González-Rodríguez et al. (2019) have shown that the type of culture predominant in hotels determines the achievement in the implementation of sustainability innovations. In this line, the study by Cantele and Zardini (2018) shows that the impact of green innovation practices performance is conditioned by the organizational commitment of employees.

Therefore, it can be considered that a strong OC, in terms of employee commitment and innovation orientation, can enhance the relationship between green innovation and performance achieved, allowing us to formulate hypothesis 2:

  • H2: Robust organizational culture positively moderates the relationship between green innovation and corporate performance.

Research Methodology

To test the proposed relationships, we focus our research on tourism firms and, specifically, the population under study is made up of those tourist accommodation establishments in Spain (hotels, hostels, aparthotels and holiday complexes) that appear in the ‘Alimarket’ database. This pre-selection has been restricted by selecting those accommodations that are located exclusively in coastal municipalities because the innovations are characterized by responding to a specific business and market model, making it difficult to compare innovation between different competitive contexts and models, for instance between sun and beach tourism and urban tourism.

The rationale behind the choice of tourism as the target sector is based on its position as one of the main economic drivers at an international level, aspect that is justified by its contribution to global economy: in 2019 tourism contributed to 10.4% of world GDP and 10.6% of employment (Hosteltur, 2021). At the same time, from an environmental perspective, despite its dependence on the natural conditions of the tourist destination, the tourism sector and coastal tourism activity has traditionally been linked to negative externalities, such as the phenomenon of overtourism and specific problems such as landscape pollution (Gelbman, 2021). This dual reality of the tourism sector, in which economic and environmental pressures of the activity must be reconciled, make it an ideal context for our research.

Primary data obtained through a self-made questionnaire based on validated scales have been used. For its preparation, a detailed review of the literature and a pre-test were carried out with two professional experts and the executive directors of four companies.

In the final questionnaire used, items for measuring green innovation, organizational culture and corporate performance were included. Items were measured with 7-point Likert-scales where 1 meant strong disagreement and 7 meant strong agreement. Green innovation (GINN) is a first-order reflective construct that was measured with three items, based on the work of ** countries. International Journal of Hospitality Management, 92, 102699." href="#ref-CR31" id="ref-link-section-d337514e726">2021). Regarding the dependent variable corporate performance (PERF), a second-order reflective construct has been created, made up of one-dimensional constructs and made up of reflective items. The scales used for economic and environmental performance, of eight and five items, respectively, was adapted from Úbeda-García et al. (2021).

For data collection, an online version of the questionnaire (QualtricsXM software was used) was distributed among the CEOs of the hotel accommodations from September 2021 to January 2022.

Data Analysis and Results

In the current research, the authors’ efforts have been directed to a specific model which is able to investigate the causal relationship between GINN and PERF and moderator role of OC. The relationships proposed in the model are tested using the Structural Equation Modeling (SEM) method based on analysis of variance: Partial Least Squares (PLS). For data treatment, Smart PLS 3 (version 3.3.9) was used.

The analysis of results is divided into two stages, following the theoretical recommendations, as it is a higher-order model of the hierarchical component approach (Lohmoller, 1989). In the first stage, the first-order results are analyzed, verifying that the first-order measurement model meets all theoretical requirements regarding reliability and construct validity. In addition, an assessment of the global first-order model has been carried out in which measures of approximate model fit have been applied (Henseler, 2017). This proves that the first-order global model has an adequate overall fit.

Once the criteria have been checked in the first-order stage and, to avoid repeating tables for the evaluation of the first- and second-order measurement model, the results obtained in the second-order model, that is, the advanced model that includes the theoretical hypotheses under study, are detailed in this research.

The evaluation of the PLS-SEM models focuses initially on the measurement models for each of the constructs. The aim is to assess the reliability and validity of the indicators of each construct. It is observed that the assessments of the measurement model improve with the creation of the second-order model.

To study the internal consistency, we analyzed three indicators of quality: Cronbach’s α, rho_A, and composite reliability. To evaluate the convergent validity, we tested the average variance extracted (AVE), which shows that a group of indicators represent a single underlying construct (Henseler, 2017). See Table 9.1.

Table 9.1 Internal consistency reliability and convergent validity
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Finally, we evaluate the existence of discriminant validity to find to what extent a certain construct differs from the others. To do this, by applying the Fornell-Lacker criterion and the HTMT Inference criterion, we can verify that we have a good level of discriminant validity for the measurement model. In this sense, it has been verified by applying Fornell-Lacker and HTMT criterion that all the values are below 0.85 (strict threshold proposed by Kline, 2011). Likewise, the HTMT Inference criterion is met, according to which the value 0.9 is not within the 95% CI (Gold et al., 2001).

After testing the reliability and the validity of the constructs, we analyzed the structural model. First, we checked for any problems related with collinearity, due to the need to avoid multicollinearity between the antecedent variables of each endogenous construct. Then we analyzed the path coefficients, the R2 values and the effect sizes (f2).

According to Hair et al. (2019), there are indications of collinearity when the variance inflation factor (VIF) is greater than 3. None of the VIF values obtained in this study are above the maximum value (Table 9.2).

Table 9.2 Multicollinearity assessment—VIF values
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After checking for collinearity, we evaluated the relevance of the relationships in the model. To this end we employed the PLS-SEM algorithm. To test whether the path coefficients are significant, we used bootstrap**. This technique allows us to test whether the hypothesized relationships are significantly different from 0 by analyzing the t statistic. Table 9.3 shows the significance levels for each relationship through their p values and their bootstrap confidence intervals.

Table 9.3 Path coefficients (direct and moderation effects)
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The positive relationships proposed in Hypothesis 1 [GINN→PERF; β = 0.599; p < 0.000] are significant and have the proposed sign. We can confirm that green innovation has positive effects on corporate performance (that includes environmental and economic dimensions).

Additionally, the study assessed the moderating role of culture on the relationship between green innovation and performance. Without the inclusion of the moderating effect, the R-Sq value for PER was 0.482. This shows that 48.2% change in PERF is accounted by GINN. With the inclusion of the interaction term, the R-Sq increased to 0.518. This supposes an increase of 3.6% in variance explained in the dependent variable (PERF).

Further, significance of moderating effect was analyzed, the results revealed a positive and significant moderating impact of OC on the relationship between GINN and PERF (β = 0.094, p < 0.05), supporting H2. This implies that with an increase in role culture, the relationship between GINN and PERF is strengthened. Further, slope analysis is presented to better understand the nature of the moderating effects. As shown in Fig. 9.1, the line is much steeper for High OC, this implying that at High Level of OC, the impact of green innovation on performance is much stronger in comparison with Low OC.

Fig. 9.1
A 3-line graph titled moderator effect plots PERF versus GINN and has some following estimated values. The lines Cult negative 1 S D, Cult mean, and Cult positive 1 S D plot an increasing trend with Cult negative at the bottom and cult positive at the top order.

Moderating effect

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F-Square effect size was 0.018 and according to Cohen (1988) proposition, the contribution to explaining the endogenous construct (PERF) of the moderator effect is small.

Conclusions

The implementation of a circular economy model requires a long-term perspective and will depend on how companies create added value, the support offered by public authorities and policy makers, as well as how consumers perceive it. The viability of this transformation requires the active involvement of all the agents involved (Aboelmaged, 2018).

Currently, policy makers have already taken on the challenge of approving laws that encourage or force their implementation (for example, in the Balearic Islands-Spain) and, in tune with the evolution of user preferences and society in general, companies start to take small steps in the transition towards circular business models. However, progress is slow and costly because it imposes the need to make changes with the promise of economic and environmental gains whose materiality requires a medium and/or long-term time horizon.

Empirical research has shown that green innovation in hotels and other Spanish accommodation has a positive impact on corporate performance, coinciding with results obtained in other geographical contexts as disparate as China (Gu, 2023). However, the study by Kuo et al. (2022) indicates that the adoption of eco-innovations does not have a direct impact on competitive improvements, and it is essential to have a competent human team committed to the complex and long process of change.

In this sense, it has been possible to demonstrate that the robustness of an OC focused on employee commitment and innovation is a positive factor that enhances the effect of GINN on PERF. This result highlights the importance of OC in dynamic and turbulent contexts and coincides with previous research (Oriade et al., 2021; Pham et al., 2023), by emphasizing that economic and environmental performance not only depends on the level of GINN adopted by hotels, but also strength of the OC that characterizes them.

In conclusion, green innovation in hotels is no longer limited to hard environmental aspects (construction, energy and consumption of raw materials), but will be deeply implemented in the service, when there are soft environmental aspects (culture, dynamic capacity, personal competencies, among others) in the hotel industry that support it. The study of the importance of these and other soft factors is established as a future line of research.

Finally, with a focus on practitioners, we would like to point out the importance of collaboration between stakeholders (policy makers, academics, firms, demand, etc.) in the development and distribution of knowledge on best practices as well as on technological solutions that promote the paradigm of the circular economy.