Introduction

Energy efficiency policies have an increasing precaution in the twenty-first century due to the effects of climate change. Energy efficiency policies can bring some advantages to economies in the aspects of the production process by reducing carbon dioxide emissions and fossil fuel energy consumption as well as providing security for energy supply. On the consumption side, energy efficiency policies can save the money of consumers (Costa-Campi et al. 2015). The recent evidence of Energy Information Administration (EIA 2017) indicates that the level of carbon dioxide emissions related to energy consumption significantly reduced in the Organization for Economic Co-operation and Development (OECD) countries since 2008. The continuity of this trend requires an increase in energy efficiency (i.e., the lower fuel economy)Footnote 1 especially in buildings and the transportation sector (Scott et al. 2016).Footnote 2 In short, energy efficiency can not only be a significant factor for providing sustainable economic growth but also for raising the green global economy. However, these issues depend on efficient energy and infrastructure policies; and therefore, it is needed to understand the determinants of energy efficiency. For this purpose, the paper aims to analyze how the development of the tourism industry affects energy efficiency in a panel data sample of 32 OECD countries.

Given that without new energy policies, the CO2 emissions, due to energy demand, are projected to increase by 28% from 2015 to 2040 (EIA 2017).Footnote 3 Besides, according to the EIA (2017), energy consumption in the OECD countries is expected to increase by 9% from 2015 to 2040. The industrial sector has the largest share (more than 50%) of energy consumption in 2015 and expected to be around 50% even by 2040. It is important to note that the energy demand in residential and transportation sectors is expected to increase much quicker than the industrial sector: For instance, the expected growth rate of energy consumption for the industry is 0.7%, while it is 1.1% for both the residential and transportation sectors in the world (EIA 2017). The difference between the growth rate between industry and transportation is higher in the OECD countries, and the growth rate is projected to be around 0.2% for the industry and 0.5% for residential and transportation sectors, respectively. The European Union (EU) has recently aimed to improve energy efficiency, and they have specifically targeted an annual reduction of 1.5% in domestic energy sales (EIA 2017). This target mainly relates to the evidence that economic activities and production in the OECD countries will move from energy-intensive industries to more service-oriented sectors, including tourism (Yuan et al. 2017). As a consequence, energy uses in buildings and transportation sectors for the OECD countries are projected to decline in the forthcoming decades, if the required new energy efficiency policies will be implemented effectively.

However, relatively underdeveloped infrastructures and large rural population (lack of shift from rural to urban areas) can negatively affect the development of energy efficiency in the residential and transportation sectors. It is also well argued that tourism contributes to higher energy consumption and carbon dioxide emissions. Hence, the tourism investments can be considered to play an essential role in minimizing energy uses by adopting the most advanced technologies in the tourism sector and making use of energy efficiency strategies (Alam and Paramati 2017; Paramati et al. 2018; Shiftan et al. 2003). Keeping this view in mind, policymakers and government officials of the OECD economies have initiated sustainable tourism investments in their economies. Indeed, tourism investments are aimed to improve energy efficiency by adopting advanced technologies in energy uses across the residential and transportation sectors and also building the hotels and restaurants in an environmentally friendly way. These factors may assist those economies in minimizing the use of energy and the growth of CO2 emissions. More specifically, hotels and other tourism-related services have significant potential for implementing energy efficiency measures and utilizing renewable energy sources. However, energy efficiency measures and renewable energy sources require new technology, and therefore, the investments in tourism facilities are crucial for understanding the potential gains of energy efficiency measures and renewable energy sources. At this stage, promoting energy efficiency in hotels can also create benefits not only for the overall performance of the economy and the objectives of the green economy but also it can enhance the image of hotels and decrease the operational costs of tourism facilities and the tourism-related activities. A lower level of operating expenses can increase the competitiveness of the tourism sector in the global area. However, it is noteworthy to mention that promoting environmental awareness to the customers is also an essential aspect of improving energy efficiency since the demand side of the market can also be a significant determinant factor.

Globalization can also be one of the significant factors to drive the customer demand for energy efficiency measures in the tourism facilities. The impact of globalization indicators is mainly due to an issue that globalization increases consumers’ desire for goods and services and producers become further integrated into global supply chains. Thus, it can significantly affect energy efficiency. Also, these indicators (foreign direct investment (FDI) and trade openness) can also bring technologies from other countries to the OECD countries; hence, these global factors can further improve energy efficiency. To control the effects of globalization over the study period, the models include the FDI inflows and trade openness, which can play a considerable role in energy efficiency.

Given this backdrop, the paper aims to examine the impact of tourism investments on energy efficiency across the residential and transportation sectors in 32 OECD economies using annual data from 1995 to 2012. The results from the long-run elasticities show that tourism investments improve energy efficiency across the transportation and residential sectors. More specially, the growth of tourism investments helps the transportation and residential sectors to reduce the use of energy to produce one unit of economic output. Similarly, the paper demonstrates that the growth in FDI inflows and trade openness also improve energy efficiency in the transportation and residential sectors of the OECD economies. The findings from short-run causalities indicate that the tourism investments Granger cause the use of energy in transportation and residential sectors, while there is no evidence of reverse causality. Given these findings, tourism investments are playing an essential role in the tourism industry to improve energy efficiency across the residential and transportation sectors. Therefore, the policymakers and government officials of these economies should further implement sustainable tourism policies, including initiating further tourism investments in the industry. All these factors can assist the OECD economies in ensuring sustainable tourism growth. To the best of authors’ knowledge, this paper is the first cross-country study to investigate the effect of tourism investments on energy efficiency. Hence, the article adds significant value to the empirical literature and also to the policies and practical implications.

The rest of the paper is organized as follows. The “Literature review” section reviews the relevant literature on the determinants of energy efficiency. The “Data, models, and methodology” section explains the nature of data, measurement, the empirical models, and the econometric methodology. The “Empirical Results” section discusses the observed results. The “Discussion and Policy Implications” section provides a detailed discussion of the findings and the relevant policy and practical implications. Finally, the conclusion of the paper is discussed in the “Conclusion” section.

Literature review

Various papers in the literature examine the determinants of energy efficiency across the industry (manufacturing), residential, and transportation sectors. Most of those papers based on the survey data at the firm level, and they generally focus on a specific country or a region. For example, Abadie et al. (2012) and Blass et al. (2014) use the data for the small and the medium manufacturing (industrial) enterprises in the United States (U.S.) for the period from 1984 to 2009, while Costa-Campi et al. (2015) consider data for the Spanish firms in manufacturing over the period 2008–2011. These papers observe that innovative behavior of the firms can provide energy efficiency and a decline of environmental degradation are among the leading objective of innovation.Footnote 4 Following this branch of literature, the empirical models consider the FDI inflows and trade openness as benchmark indicators of innovation, which are the potential drivers of energy efficiency across residential and transportation sectors in the OECD countries. Furthermore, these indicators (FDI inflows and trade openness) also account for the globalization effect on energy efficiency. According to Dreher (2006) and Gozgor (2018), globalization increases consumers’ demand for goods and services (measured by the trade openness), and producers become further integrated into global supply chains (measured by the FDI inflows). In line with these findings, the models test the hypothesis whether the trade openness and the FDI inflows can significantly affect the energy efficiency across residential buildings and transportation sector. In addition, since there is a positive correlation between per capita gross domestic product (GDP) and the probability of investing in energy technologies in residential buildings and transportation sector is observed in the previous literature (see e.g., Long 1993; Mills and Schleich 2012; Nair et al. 2010); hence, the empirical models include the per capita GDP in the estimations.

Indeed, the tourism sector is a significant part of the world economy as it not only provides much employment and income opportunities for the local community but also provides revenues for the local and national governments and even enormous foreign exchange reserves (Alam and Paramati 2016). As a result of increasing tourism activities around the world, every year, millions of tourists travel to vast distances (Gössling et al. 2013). Those millions of travelers stay in hotels, which consume a significant amount of energy (Bohdanowicz et al. 2001). At this point, the hospitality industry is the largest business in the globe, and the energy used in the hospitality industry produces a significant amount of greenhouse gas emissions (Babaei et al. 2015).

At this point, there are only a few papers which investigate the effects of tourism indicators on energy efficiency measures. For instance, Becken and Cavanagh (2003) analyze the energy consumption of the tourism sector in New Zealand during 1999 and 2001. The authors provide potential implications for energy efficiency of vehicles and accommodation providers. In a further study, Becken and Hay (2007) discuss the potential risks and opportunities in the tourism sector to affect the pattern of climate change, including energy efficiency measures. In their seminal paper, Gössling et al. (2005) conclude that limiting the consumption of fossil-related energy source is the main issue for achieving the objectives of sustainable tourism development. Finally, Scott et al. (2016) illustrate that the consumption of fossil fuels is associated with the emissions of greenhouse and it is the leading environmental problem. The increasing greenhouse gases can have a significant adverse effect on climate change and also on the tourism industry. Indeed, hotels and tourism-related services have more considerable potential for implementing energy efficiency measures and utilizing renewable energy sources. However, implementing energy efficiency measures and using renewable energy sources require new technology (Gozgor 2016). Therefore, tourism investments (improvements) can enhance existing techniques for saving energy to address environmental degradation, thus the pattern of global climate change (Paramati et al. 2018). Therefore, there could be a significant link between tourism investments and energy efficiency due to the residential (e.g., hotels) and transportation activities (e.g., air, rail, road, and sea).

To add these papers, the recent empirical study by Alam and Paramati (2017) focus on the effects of tourism investments on tourism development and the level of carbon dioxide emissions in a panel of ten major tourism-based economies over the period 1995–2013. According to the results, tourism investments not only promote the growth of the tourism industry but also help to reduce CO2 emissions.Footnote 5 In line with the model of Alam and Paramati (2017), our paper considers the tourism investments as the leading indicator of tourism development, but it focuses on the indirect effects of tourism investments on environmental quality by enhancing energy efficiency in residential and transportation sectors of the OECD countries.

Also, Hochman and Timilsina (2017) investigate the barriers on the implementation and adoption of energy-efficient technologies for commercial and industrial firms in Ukraine, and they conclude that lack of knowledge and awareness are significant barriers to the approval of energy-efficient technologies in those firms. However, it is also argued that the high barrier to energy efficiency is minimized for tourism sector because the hospitality businesses have to maintain the positive image, including more green and eco-lodgings and transportation services (Babaei et al. 2015). Therefore, the investments in energy-efficient technologies in the tourism sector can save energy consumption, improve productivity, and reduce carbon dioxide emissions from the productive areas. Increased investment in greening the tourism sector can contribute to improved efficiency in resource use and minimize environmental degradation, attribute to the expectations of tourists regarding responsible natural resource management and also the needs of communities that support or are affected by tourism projects and the environment (United Nations Environment Program 2011). However, the hypothesis of the causality running from tourism investment to energy efficiency as put forward by the above explanations has not yet investigated in the literature.

To conclude the literature review, we observed that there are various papers, which examine the determinants of energy efficiency; however, the previous studies neglected the effects of tourism investments on energy efficiency across the residential and the transportation sectors. Considering the role of tourism investments as the benchmark indicator of tourism development on energy efficiency, we provide the first empirical evidence on this subject. For this purpose, this study focuses on a panel of 32 OECD countries throughout 1995–2012. To be consistent with the previous literature on energy efficiency, we include the FDI inflows, trade openness, and per capita income in the models along with the tourism investments. Therefore, the findings derived from this paper have important practical implications and add new knowledge to the empirical literature.

Data, models, and methodology

Data description and empirical models

The present paper collects yearly data from 1995 to 2012 from 32 OECD economies, such as Australia, Austria, Canada, Chile, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea Republic, Latvia, Mexico, the Netherlands, New Zealand, Norway, Poland, Portugal, Slovenia, Spain, Sweden, Switzerland, Turkey, the United Kingdom (UK), and the U.S. The balanced panel dataset on the selected variables and countries of the OECD economies is only available from 1995 to 2012; hence, the sample period of the study is determined by the availability of annual data.

In this paper, it is aimed to empirically investigate the impact of tourism investments on energy efficiency across transportation, residential, and overall economy by accounting other potential determinants in the models, such as FDI net inflows, per capita income, and trade openness. The tourism investments are measured in a million USD (real prices) (TI);Footnote 6 the energy intensity of the transportation sector is in MJ/2011 USD PPP (TEI); energy intensity of residential sector is in GJ/household (REI); energy intensity of overall economy is of final energy in MJ/2011 USD PPP (OEI), FDI, net inflows as a percentage of GDP (FDI), and real GDP per capita income in constant 2010 USD (PI). Finally, trade openness is the total exports and imports as a percentage of GDP (TO). We obtain the required data on TI from the World Travel and Tourism Council (WTTC), while data on TEI, REI, and OEI downloaded from the “Sustainable Energy for All” dataset of the World Bank; and finally, data on PI, FDI, and TO collected from the “World Development Indicators (WDI)” dataset of the World Bank. As implied from the description of the variables, they measured in different units; hence, the study converts all these variables into natural logarithms before the empirical estimations.

The objective of this research is to empirically investigate the impact of tourism investment on energy efficiency of transportation, residential, and overall economy of the 32 OECD economies. To achieve the above objectives, following traditional energy demand models, we use the following equations:

$$ {\mathrm{TEI}}_{\mathrm{i}\mathrm{t}}=f\ \left({\mathrm{FDI}}_{\mathrm{i}\mathrm{t}},{\mathrm{PI}}_{\mathrm{i}\mathrm{t}},{\mathrm{TO}}_{\mathrm{i}\mathrm{t}},{\mathrm{TI}}_{\mathrm{i}\mathrm{t}},{\mathrm{v}}_{\mathrm{i}}\right) $$
(1)
$$ {\mathrm{REI}}_{\mathrm{it}}=f\ \left({\mathrm{FDI}}_{\mathrm{it}},{\mathrm{PI}}_{\mathrm{it}},{\mathrm{TO}}_{\mathrm{it}},{\mathrm{TI}}_{\mathrm{it}},{v}_i\right) $$
(2)
$$ {\mathrm{OEI}}_{\mathrm{it}}=f\ \left({\mathrm{FDI}}_{\mathrm{it}},{\mathrm{PI}}_{\mathrm{it}},{\mathrm{TO}}_{\mathrm{it}},{\mathrm{TI}}_{\mathrm{it}},{v}_i\right) $$
(3)

In Eq. (1), (2), and (3), where TEI, REI, OEI, FDI, PI, TO, and TI indicate the energy efficiency of transportation, residential, overall economy, FDI inflows, per capita income, trade openness, and tourism investments, respectively. Similarly, vi represents for the individual (country) fixed-effects; and i and t capture the cross-section and period, respectively.

Econometric methodology

To begin the investigation, we examine the order of integration of variables using several panel unit root tests. It is important to understand the order of integration of the variables before employing any econometric technique. This knowledge will help us to choose the appropriate econometric methodology. The paper makes use of five-panel unit root tests that examine common, as well as individual, unit root processes. For instance, the common unit root process is analyzed using Levin et al. (2002) and Breitung (2002) tests, while the individual unit root process is investigated using Im et al. (2003) and two Fisher type tests, such as the Augmented Dickey and Fuller (ADF) and Phillips and Perron (PP). The Fisher-type unit root tests are developed based on the approach suggested by Maddala and Wu (1999). All of these unit root tests follow the null hypothesis of a unit root as against the alternative hypothesis of no unit root in general.

The long-run energy efficiency elasticities of transportation, residential, and the overall economy are investigated using the panel autoregressive distributed lag (ARDL) models. The significance of the ARDL method is that it can be applied to the model, which possesses a different order of integration of the variables, that is, either I (0) or I (1). Therefore, given the nature of the variables, the ARDL model is more appropriate to examine the long-run energy efficiency elasticities.Footnote 7 To this end, the paper applies the panel approach suggested by Pesaran et al. (2001). This panel ARDL approach assumes the cross-sectional independence, implying that the disturbances are independently distributed across units and over time with the zero mean and the constant variances. The appropriate lag length for this test is selected based on the Akaike Information Criteria (AIC).

Finally, the paper applies the short-run bivariate panel non-causality test to examine the direction of causal relationships among the variables of energy efficiency of transportation, residential, and overall economy, as well as the FDI inflows, per capita income, and trade openness. For this reason, the paper focuses on the approach suggested by Dumitrescu and Hurlin (2012). This test requires all the variables to be stationary; hence, we applied to the first difference data series of these variables. The null hypothesis of no causality tested against the alternative hypothesis of causality at least for a few cross-sections. The Wald statistics are computed separately for each cross-section, and the panel test value obtained by taking the cross-sectional average of the individual Wald statistics.

Empirical results

Preliminary analysis of the data

Firstly, the paper provides a preliminary analysis of the variables included in the empirical models. Table 1 shows summary statistics on the individual OECD economies for the period from 1995 to 2012. Among 32 OECD economies, we observed that the energy efficiency in transportation, residential, and overall economy are significantly higher in the countries like Turkey and Mexico, while it is lower in the U.S. and Iceland, respectively. Likewise, Japan had received the lowest FDI inflows among the considered OECD economies, whereas the Netherlands received the highest. Japan also has the lowest trade openness among these countries. The per capita income ranges from 8597 US$ (Mexico) to 83,980 US$ (Norway). Finally, the tourism investments also vary across these OECD economies; specifically, it ranges from 183 million US$ (Latvia) to 135,466 million US$ (U.S.). Overall, the OECD countries invest 10,640 million US$ per year, on average, during the sample period.

Table 1 Summary statistics on the individual OECD economies (1995–2012)
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Table 2 reports the compounded annual growth rates on the individual OECD economies for the period of 1995 to 2012. It is interesting to notice that the country that has significant growth in tourism investment is associated with the largest reduction in the overall energy intensity. For instance, Latvia has shown a growth rate of 13.34% in tourism investments, whereas it has shown the highest level, among the considered countries, of reduction in overall energy intensity, i.e., 3.84%. On the other hand, Iceland experienced the lowest growth in tourism investment, i.e., 0.54% only, whereas its reduction in the overall energy intensity is only 0.01%, and it is the lowest among all 32 OECD countries. However, some other countries such as Greece, Japan, the Netherlands, and Spain have shown negative growth in tourism investments. It is also important to note that all of the OECD economies have shown the positive growth rate in per capita income.

Table 2 Compounded annual average growth rates on the individual OECD economies (1995–2012)
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Findings on order of integration of the variables

To begin the empirical investigation, we firstly investigated the order of integration of the selected variables. We used several panel unit root tests since it is an important step in the appropriate modeling strategy for the subsequent empirical analyses. Therefore, it is applied five versions of panel unit root tests, namely LLC (Levin et al. 2002), Breitung test (Breitung 2002), the IPS (Im et al. 2003), and the Fisher ADF, and the Fisher PP (Maddala and Wu 1999; Choi 2001). The results of these tests on the level and the first difference data series are shown in Table 3. All panel unit root tests have been estimated by including constant and trend variables. The results of these panel unit root tests show the mixed order of integration. The LLC test indicates that all variables are stationary except the overall energy efficiency and the real GDP per capita. The Breitung test, however, indicates that all variables are non-stationary except the FDI, trade openness, and tourism investments. The IPS test and the ADF test indicate that all variables are stationary except the real GDP per capita. The PP test indicates that the overall energy efficiency, the real GDP per capita, and the trade openness are non-stationary at the levels. Therefore, it is safe to conclude that the FDI and the tourism investments are stationary variables, but the evidence is mixed for others. The results, therefore, suggest that some of the variables are stationary at the levels, while some other variables are non-stationary. Given that, the paper applies these unit root tests on the first order difference data series and the findings show that the null hypothesis is strongly rejected for all of the variables. Based on these findings, we concluded that the variables of this study have a mixed order of integration, i.e., either I (0) or I (1).

Table 3 Results of the panel unit root tests
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Findings of long-run energy efficiency elasticities

Since above panel unit root tests confirm the mixed order of integration of the selected variables, hence, the study uses the panel ARDL model of Pesaran et al. (2001) to investigate the long-run elasticities of the energy efficiency across transportation, residential, and overall economy of the 32 OECD economies. More specifically, the paper investigates the impact of tourism investments on energy efficiency by accounting other potential determinants, such as per capita income, FDI inflows, and trade openness in the models. The significance of the panel ARDL method is that it allows estimating long-run parameters even in the presence of a mixed order of integration of the variables. Furthermore, it accommodates endogeneity concerns that may occur in the models. We present the findings of the panel ARDL models in Table 4. The results indicate that tourism investments have played a considerable role in improving energy efficiency across transportation, residential, and the overall economy.

Table 4 Results of the long-run estimations using panel ARDL models
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According to the results presented in Table 4, a 1% growth in tourism investment reduces the energy use in transportation, residential, and overall economy by 0.024, 0.078, and 0.042%, respectively. It implies that higher tourism investments lead to higher energy efficiency across the transportation, residential, and overall economy of the OECD economies. Furthermore, the results establish that the growth in FDI inflows and trade openness also improve the energy efficiencies in these economies. However, the increase in per capita income raises energy use across transportation and residential sectors but reduces the overall energy consumption in the marketplace.

The long-run elasticities indicate that the tourism investments, along with the FDI inflows and trade openness (except in the case of the overall energy efficiency) significantly promote energy efficiency in the OECD countries, while the real GDP per capita growth promotes the overall energy efficiency, but adversely affects the energy efficiency in transportation and residential sectors. These results show that tourism investments have a significant positive impact on energy efficiency across the considered industries in the paper.

Findings on short-run causalities

Finally, the paper examines short-run causalities among the variables of energy efficiency indicators, the GDP per capita, the FDI inflows, the trade openness, and the tourism investments. The study uses heterogeneous causality technique of Dumitrescu and Hurlin (2012) to estimate the short-run dynamics among the variables. We display the short-run causalities in Table 5.

Table 5 Results of the short-run heterogeneous panel non-causalities
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The causality test results demonstrate that the tourism investments Granger cause the energy efficiency of transportation and residential sectors, but it has no significant impact on the energy efficiency of the overall economy in the short-run. Similarly, the results display bidirectional causality between FDI inflows and energy efficiency of transportation and also between per capita income and energy efficiency of transport. On the other hand, we find that the unidirectional causality that runs from per capita and trade openness to the energy efficiency of the residential and overall economy. Hence, these short-run findings on causal relationships among the consider variables imply that the tourism investments play an essential role to affect the energy efficiency of transportation and residential sectors. Similarly, the per capita income and trade openness also cause energy efficiency.

Discussion and policy implications

Based on the empirical findings from long-run and short-run estimations, it suggests that tourism development (investments) has a positive environmental impact on the economy given the adoption of more environmentally friendly strategies and technologies. Besides, the empirical results demonstrate that it is possible to invest in tourism to offset tourism-based carbon dioxide emissions, especially in the residential and transportation sectors. Several policy implications in regard to enhancing the level of energy efficiency in the OECD economies can derive from the long-run estimates. The findings establish that the tourism development not only provides an opportunity for residents to participate in direct employment but also enhances energy efficiency through the investment in renewable energy and energy efficiency technologies both in residential and transportation sectors.

Several previous studies suggest that tourism development leads to higher pollution and environmental degradation (Raza et al. 2017; Sun 2016; Zhang and Gao 2016). However, the development of low-carbon and sustainable tourism (i.e., investment in the industry) can ensure that it develops sustainability for the benefits of the local economy by enhancing national energy efficiency both in residential and transportation sectors (e.g., the usage of green energy and energy efficiency practices in hotels and hospitality industry, including pubs and restaurants). The energy efficiency in the whole economy can provide through several successful businesses approaches in accordance with the corporate social responsibility (CSR) principles, including adopting and implementing sustainable supply-chain initiatives, and focusing on business to business marketing rather than business to consumer marketing (Dodds and Joppe 2005), and fostering clean energy sources (Sun 2016).

Besides, the results are in line with existing literature, indicating that both the FDI inflows and the trade openness play a considerable role in reducing energy uses across the sectors in 32 OECD economies (Lee 2013; Mielnik and Goldemberg 2002; Zheng et al. 2011). These results imply that free trade and the promotion of inward FDI, in particular, encourage more efficient energy use to combat CO2 emissions (Gozgor 2017; Sbia et al. 2014). For instance, the real estate projects of artificial islands are huge energy-intensive projects; therefore, the government of the United Arab Emirates (UAE) facilitates the FDI inflows to green energy projects. These findings imply that the policymakers and government officials should consider different policies for different sectoral FDI since the FDI can be a source of innovation in promoting energy efficiency, but the outcome varies in magnitude and significance by the sectoral FDI (Doytch and Narayan 2016).

The established conclusion is that investments in the tourism sector enhance the energy efficiency for the economy. Therefore, the policymakers of the OECD countries should provide the incentives in the form of subsidies and financial support to the tourism industry to replace older machines and facilities with more efficient models, improving operational and infrastructure use, and adopting more of clean energy sources. The policymakers in government should also recognize that the above environment-friendly business practices can reduce the carbon dioxide emission levels in these countries by avoiding or reducing the use of fossil fuel energy and benefit the well-being of the local communities. Moreover, the business owners and managers should also realize that more efficient use of energy not only result in a reduction of operating costs but also attracts more international tourists, especially from the developed countries.

Given the above findings, policymakers should initiate more of sustainable tourism development policies, which may assist those countries in enhancing energy efficiency and reducing energy intensity in the long run. Equally important, the government should develop holistic and comprehensive tourism development strategies in partnership with the community and industry stakeholders (Dodds and Joppe 2005). For instance, the Green Lights Program between “Green Lights Partner” and the United States Environmental Protection Agency (USEPA) encourages the use of energy-efficient lighting.

Given the above evidence and arguments, we suggest that the policymakers, government officials, travel agencies, and stakeholders in the industry should realize the substantial benefit of the tourism investments and use of renewable energy for the general enhancement of energy efficiency across the OECD countries. Therefore, political leaders should consider the tourism investment and, hence, energy efficiency as an essential tool in their energy policy portfolio. Among other areas, government officers should initiate policies to promote sustainable tourism investments and the procedures related to the promotion and use of renewable energy sources. These policies may include information provision and energy audits from the government officials as the energy efficiency investments are affordable to small- and medium-sized enterprises due to a wide range of sophisticated technologies and services, which are difficult to determine their quality either before or after purchase. Consequently, the information costs of obtaining and processing information on the energy efficiency can be high (Jollands et al. 2010). Besides, the lack of information, knowledge, and awareness are significant barriers to the adoption of energy-efficient technologies (Hochman and Timilsina 2017). The difficult access to financing is another barrier, which further impedes investment in these technologies, especially for the small-and-medium-sized enterprises; and without easy access to funding, many energy-efficient investments are unlikely to be implemented (Hochman and Timilsina 2017; Jollands et al. 2010). Nevertheless, the commitment to sustainable development from the industry and government level is definite, but not yet decisive in the choice of customers.

Conclusion

The paper analyzed the impact of tourism investments on the energy efficiency of the transportation, residential, and overall economy in a panel of 32 OECD countries. Using annual data from 1995 to 2012, we employed various panel econometric techniques to achieve the research objectives. Given the nature of variables, the paper applied the panel ARDL models to estimate the long-run energy intensity elasticities. According to the long-run estimations, tourism investments play an essential role in improving energy efficiency across transportation and residential sectors. Furthermore, we find that both the FDI inflows and trade openness play a considerable role in reducing energy uses across these sectors. Finally, we observed that tourism investments cause energy efficiency both in the residential and transportation industries in the short-run. Given these findings, the paper provided new empirical knowledge on the nexus between tourism investments and energy efficiency by discussing various policies and practical implications. Future research may focus on country cases, especially large developing economies (e.g., China and India), the most-visited developing countries (e.g., Mexico, Thailand, and Turkey), or the small-island countries (e.g., the Maldives), which can be ideal sample countries in order to analyze the relationship between tourism indicators and energy efficiency.