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Article

Does the Past Affect the Future? An Analysis of Consumers’ Dining Intentions towards Green Restaurants in the UK

by
Farah Shishan
1,
Ricardo Mahshi
2,
Brween Al Kurdi
3,
Firas Jamil Alotoum
4 and
Muhammad Turki Alshurideh
1,5,*
1
Department of Marketing, School of Business, The University of Jordan, Amman 11942, Jordan
2
Department of Tourism, Sport and Hotel Management, Griffith Business School, Griffith University, Brisbane 4222, Australia
3
Department of Marketing, Faculty of Economics and Administrative Sciences, The Hashemite University, Zarqa 591504, Jordan
4
Department of Marketing, School of Business, Isra University, Amman 11622, Jordan
5
Department of Management, College of Business Administration, University of Sharjah, Sharjah 27272, United Arab Emirates
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(1), 276; https://doi.org/10.3390/su14010276
Submission received: 10 November 2021 / Revised: 19 December 2021 / Accepted: 20 December 2021 / Published: 28 December 2021
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Abstract

:
Due to the growing notion of environmental protection, many restaurants have started to apply operational practices to diminish their carbon footprint, leading to the emergence of “green” restaurants. Green restaurants are establishments committed to minimizing adverse environmental consequences throughout their operations. Nevertheless, further research is warranted to examine consumer behavior in this field. Taking the consumers’ perspective, this study uses an augmented theory of planned behavior (TPB) and a cross-section of 896 British diners to explain their dining intentions towards green restaurants. The extended model of the TPB was tested to justify the addition of past behavior and the impact of sociodemographic characteristics. Using structural equation analysis, the results identified past behavior, perceived behavioral control, subjective descriptive norms, and attitude as critical factors influencing behavioral intention. Furthermore, apart from gender, the relationships between sociodemographics and intentions to dine at green restaurants were insignificant. This research provides insightful implications in the green restaurant domain and suggestions for future research.

1. Introduction

Climate change has profoundly affected human societies and the natural environment. Various researchers argue that the impacts of climate change will be destructive and long-lasting [1,2]. Furthermore, the United Nations panel on climate change, formally referred to as Intergovernmental Panel on Climate Change (IPCC), that represents 195 countries in the United Nations, states that the warming of the climate system is apparent [3]. Therefore, in light of the United Nations Sustainable Development Goals (SDGs) and with less than 10 years left to reach the target date of 2030, countries should accelerate and invest further efforts to find better solutions to climate change in order to genuinely change the world’s communities and economies [2]. In addition, all industry sectors, including tourism and hospitality, must play their role in supporting mitigation and adaptation measures to diminish climatic change [2].
Globally, tourism is economically sensitive to climate change since the integrated effects of climate change are likely to have wide-ranging effects on tourism destinations and, eventually, on tourism businesses’ success [4]. For instance, tourism operations significantly contribute to greenhouse gas emissions [5]. Within the tourism industry, the restaurant sector has been regarded as a primary driver of climate change. The restaurant sector is an essential component of the tourism value chain and has been criticized for consuming large quantities of energy and producing considerable greenhouse gas emissions [6]. The increasing number of environmental laws and pressure from the market have dramatically altered the sector’s responsiveness to environmental issues [7,8]. Therefore, dining establishments have started to adopt some green practices to reduce costs and maintain a competitive advantage [9,10,11], which introduced the notion of green dining establishments. Many green restaurants have implemented green initiatives by decreasing energy use and water consumption, recycling, and buying sustainable and fresh produce [12]. Some of these initiatives include avoiding plastic cutlery in the dining room, avoiding plastic water bottles, and installing energy-efficient equipment [13]. The adoption of these sustainable programs by restaurants reflected their environmental responsibility [11]. Investigating consumers’ intentions towards green dining establishments is viewed as a significant aspect that affects restaurants’ decisions around successfully implementing environmental programs [12].
Regarding consumers’ behavior in green restaurants, prior studies show conflicting evidence. For instance, consumers would appreciate dining at a restaurant that implements green practices because they believe that by engaging in pro-environmental behavior, they would help in protecting and preserving natural resources and the environment for future generations [13]. Notwithstanding, consumers were reluctant to dine at such establishments due to the fear of paying too much extra money [14]. Furthermore, some consumers are hesitant because they are suspicious of the restaurants’ real motive behind their green policy, which in turn could affect the efficacy of their environmental programs [15]. This skepticism is critical in the restaurant industry because gaining the support and assistance of consumers in green practices cannot be underestimated. Therefore, examining the factors that will impact consumers’ intention to choose a green restaurant over a traditional one is crucial and relevant to current restaurant operations.
Most prior research has found that different factors influence consumers’ support for restaurants’ green programs and lead to their behavioral intentions [10,14,16]. Understanding the rationale behind consumers making certain decisions and the main determinants for their choices would allow restaurateurs to positively influence consumers’ environmental behavior and increase the likelihood of dining at green restaurants [10,16]. Therefore, the theory of planned behavior (TPB) was adopted in the current investigation to build up a more profound knowledge of the antecedents of green dining intentions. The authors of the theory, Fishbein and Ajzen [17], suggested that individual behavior is expected to be affected by an individual’s attitude, injunctive and descriptive norms, and behavioral control perceptions. Several scholars have used the TPB to study environmental behaviors such as green purchasing behavior [18], household energy-saving behavior [19], and green hotel choice [20]. Moreover, several researchers [21,22] have studied individuals’ pro-environmental behavior using the TPB in the green restaurant context. Thus, it is evident that this theory can be adopted as the theoretical lens of this research to explain British consumers’ purchase intention towards green restaurants.
Over the years, the TPB has become widely accepted and prevalent in social psychology due to its parsimonious interpretation of rational behavior; however, some researchers counter-argue its sufficiency [23,24]. The TPB is a well-established social cognition model that has been applied to a wide range of fields [19,25,26,27]. While the theory was cited only 22 times in 1985, it has since grown to 4550 citations in 2010 [28]. In 2012, it was mentioned in 18,475 articles, with 1099 theses and 353 journal articles including the name of the theory as a keyword [29]. According to these researchers, the TPB leaves a substantial percentage of unexplained discrepancy in intentions and behavior. Consequently, Ajzen [30] proposed that the original variables in the theory might be augmented by comprising other factors that explain the variance in behavioral intention. Furthermore, it is evident in some studies that past behavior often directly predicts future behavior [31,32,33,34]. Recently, the influence of past behavior was investigated in relation to individuals’ environmental behavior [20,35]. However, past behavior effects related to consumer behavior received limited attention among researchers. Hence, the current study adopted the extended TPB framework that Fishbein and Ajzen [17] suggested by including past behavior to predict diners’ behavioral intentions towards these green establishments in the UK.
In addition, consumers’ demographics impacting their intentions to dine at these restaurants can be explored. Therefore, this study offers a deeper understanding of the psychosomatic and demographic factors that may affect consumers’ actions in the context of green dining establishments. Consumer research on green restaurant management is still regarded as an emerging academic subject. Green practices in numerous restaurants have, to some extent, failed to meet consumer demand. Hence, this study was undertaken from the diners’ perspective, with the hope that restauranteurs can identify factors that influence consumers’ decisions to dine at green restaurants.
Accordingly, the aim of this research was to: (1) investigate the underlying factors leading to diners’ intentions to select a green restaurant, (2) explore whether past behavior could contribute to the basic TPB model in the green restaurant setting, (3) investigate the impact of demographics in the TPB studies and initiate a framework that would assist in verifying the decision-making of green diners.
The study is organized as follows: the literature review presents insights into consumer state in the context of green dining establishments and develops the hypotheses and conceptual design of the research. In the methodology section, data collection and analysis procedures are presented, followed by the findings. The discussion and conclusions are then presented, followed by practical implications. Finally, limitations and further research are presented.

2. Literature Review

2.1. The Theory of Planned Behavior

In recent years, a rising concern in public regarding ecological aspects has become more prominent, with many people recognizing the seriousness of environmental problems [8]. This concern has also spilled into the hospitality industry, and researchers have devoted increased attention towards studying green restaurants [16]. Green restaurants mainly focus on reducing their energy and increasing efficiency by implementing the three “Rs” (reduce, reuse, and recycle) [36]. In addition, researchers have recently reported the emergence of several organizations to promote environmental practices [37], including the US-based Green Restaurant Association (GRA; for further details, check https://www.dinegreen.com/ (accessed on 9 November 2021)), the UK-based Sustainable Restaurant Association (SRA; for further details, check https://thesra.org/ (accessed on 9 November 2021)), and the Australian Green Table Program (GTP; for further details, check https://www.rca.asn.au/ (accessed on 9 November 2021)). These organizations assist dining establishments in becoming more environmentally responsible through incorporating green initiatives and training their employees.
At present, some consumers seek out restaurants that provide evidence of the execution of green programs, leading restaurant owners to adopt some green practices [16]. Consequently, “going green” can help restaurants establish a reputation and give them a competitive advantage over competitors in this sector [11]. However, a recent literature review indicated that out of 146 studies identified in the hospitality sector, only 25.3% investigated consumer behavior towards green initiatives [38]. The lack of research in this area was previously reported. For example, in an earlier study [26], the researchers reviewed 52 published studies and found that 28% of those studies focused on the consumer. In addition, they reported that only a few studies adopted theoretical perspectives, which is viewed as a shortcoming of the literature. Hence, it is essential to obtain comprehensive identification of the factors that would affect consumer purchasing behavior using a theoretical framework to develop promotion strategies that aim to influence consumer behavior in the green restaurant setting.
Within the TPB, intentions and perceptions of behavioral control are the immediate antecedents of a person’s behavior [27,39]. The model suggests that intentions are impacted by the interaction between three factors: individuals’ assessment of the behavior (attitude); their perception of likely challenges and difficulties of conducting the behavior (perceived behavioral control); and their perception of what is usual or desirable in a group or a situation (social norms) [30]. Attitude refers to a feeling of favorableness or unfavorableness that an individual has towards certain behaviors [20,40]. Further, attitudes are gained through learning and experience, thus creating a positive or negative valued tendency, leading to a consistent behavior towards specifically defined issues, such as a product or a tourist destination [41]. While perceived behavioral control “reflects the influence of personal capacities and actual constraints regarding the target behavior on intentions” [42], social norms refer to the behaviors that are considered appropriate in certain groups [20,34]. Social norms sum up individuals’ perceptions of social influence and whether significant others support their participation in a specific context [42]. Social norms originated from the study of Fishbein and Azjen [43], where they argue that prevailing determinants of behavior should go beyond attitudes by including a social normative factor. In its initial framework, the TPB, the social norms were only referred to as what is considered appropriate or inappropriate by influential people, for example, family and friends (subjective injunctive norms). However, some scholars have argued that norms should be broadly presented, implying what is usually performed in addition to what is endorsed by these important people [39]. Considering the previous argument, the framework of the TPB was extended by including descriptive norms and injunctive norms as the two elements of subjective norms. According to Fishbein and Ajzen [17], injunctive norms are derived from injunctive normative beliefs related to referents’ thoughts about performing a behavior. In contrast, descriptive norms are derived from the descriptive normative beliefs related to referents’ actual behavior. The impact of descriptive norms on behavior has been supported by many researchers who used the TPB model in different settings [17,20,27,39].
Despite the popularity of the TPB, researchers have expressed concern about its narrow sufficiency of the factors predicting intentional behavior [31]. For example, the results of a comprehensive literature review support the significant impact of past behavior on intentions [33]. Moreover, Ajzen [28] indicated that it is essential to include a measure of past experience in the TPB model to enhance the model’s prediction aspect of future behavior. This is because the consistency of past behavior usually reflects the habit strength, which in turn influences future behavior [31]. However, even if the behavior was not consistent, the past behavior indirectly impacts behavior through intentions because individuals are more likely to form favorable intentions about their previous actions [33]. Indeed, many scholars in different domains have included this construct as a factor impacting intention, which improved the theory’s predictive power [20,35,44]. Therefore, this study extended the TPB by adding “past behavior” to the framework (see Figure 1) and proposed five hypotheses:
Hypothesis 1 (H1).
Attitudes are positively associated with consumers’ intentions to dine at a green dining establishment.
Hypothesis 2 (H2).
Subjective injunctive norms are positively associated with consumers’ intentions to dine at a green dining establishment.
Hypothesis 3 (H3).
Subjective descriptive norms are positively associated with consumers’ intentions to dine at a green dining establishment.
Hypothesis 4 (H4).
Perceived behavioral control is positively associated with consumers’ intentions to dine at a green dining establishment.
Hypothesis 5 (H5).
Past behavior is positively associated with consumers’ intentions to dine at a green dining establishment.

2.2. Demographic Characteristics

Previous studies have examined the impact of demographic profiles to better comprehend consumer behavior in several settings. Notably, some studies in the green restaurant setting have verified the effect of gender, age, education, and income on consumers’ decisions [14,45]; nevertheless, the results have been inconclusive.
Starting with gender, some researchers report that females are more inclined to be environmentally mindful and form intentions to dine at green establishments [45]. Moreover, another study in 2017 reported that women were prepared to pay more for pro-environmental initiatives in these establishments compared to men [12]. Specifically, women are more fulfilled with all the programs implemented in green hotels than men [46]. Other researchers argue that females tend to count on different sources of knowledge prior to making a decision [47]. Indeed, they depend on the evidence in the external world rather than resort to their personal judgments. Recent work in 2020, however, reported an insignificant relationship between gender and choosing a green restaurant [48].
The second personal factor that received attention from many scholars is age, yet the results in green consumer behavior studies regarding the role of age are inconsistent. For instance, some scholars reported that younger consumers are inclined to pay extra for green restaurants than older consumers [12,14]. They further state that younger people tend to be more knowledgeable about green restaurants, which may motivate them to dine at such restaurants. Nevertheless, other researchers indicate that behavioral intentions towards green restaurants are not statistically significant among different age groups [48].
The vital role of income and education in affecting pro-environmental decision-making has also been identified in the literature. For example, income impacts the intent to dine and the willingness to pay extra at a green dining establishment [48]. However, in developing a profile of green travelers who book in a green lodging establishment, a study in 2011 indicated that components of intentions do not significantly change among different education and income groups [49]. Furthermore, other researchers report that there is no actual variance between the education groups in consumers’ involvement in green practices [46]. In sum, earlier research on personal attributes shows contradictory results regarding travelers’ intentions due to their sociodemographic factors, including age, gender, income, and education, suggesting that further research is warranted in this area.

3. Materials and Methods

Selecting a suitable research design depends on the research problem [50]. If the research problem calls to test and validate existing theories, researchers should apply quantitative research methods [51]. Therefore, a quantitative approach was used to achieve the study objective, which is to validate the constructs of the extended model of the TPB.

3.1. Questionnaire Development

The first section of the survey included the factors that determine the intention (attitude, injunctive and descriptive norms, perceived behavioral control, and past behavior). The second section consisted of items measuring the intention. Finally, the last section included questions to profile the participants, including gender, age, marital status, education, and income.
Scales measuring all variables referenced previous studies. Attitudes towards dining at a green restaurant were measured using seven adjective pairs [17,20], for example, “Dining at a green restaurant is positive”. Second, subjective injunctive norms were assessed by three modified items [17,39] (e.g., “Individuals who I personally consider significant think I should dine at a green dining establishment in the near future”). Third, two items were used to assess subjective descriptive norms [17,20] (e.g., “Most individuals who I personally consider significant will dine at a green dining establishment in the near future”). Perceived behavioral control was assessed through three items [17,39] (“whether or not I dine at a green dining establishment in the future is entirely my decision”). As for past behavior, it was assessed by two items [17,20]: “During the last 12 months, I have dined at a green dining establishment” and “During the last 12 months, how often have you dined at a green dining establishment?”. Finally, intentions were assessed through three items (e.g., “I intend to dine at a green dining establishment during the coming 12 months” [17,39]. Attitude was assessed on a 10-point scale (1–10) using each adjective pair, and all the items for the other constructs were assessed using a 10-point continuous metric scale (0 = highly disagree, 10 = highly agree).
The importance of ensuring the validity and integrity of the survey has been highlighted by several researchers [20,27,52]. The survey was accordingly developed through several stages. Firstly, the survey’s face validity was attained by reviewing the literature related to survey design and the topics included in the questionnaire. In addition, three academic experts were consulted to confirm the suitability of the survey and the scales used. Following that, a pilot study was performed on 50 people to assess the psychometric properties of the TPB factors. As a result, Cronbach’s alpha coefficients varied from 0.88 to 0.95, which are acceptable, as they all appeared higher than the minimum (0.7) [53].

3.2. Sampling and Data Collection

The study used Qualtrics™ to distribute the questionnaire through an online survey in March 2020. Some advantages of employing online surveys include a random selection of individuals, access to individuals in distant locations, speed of response, and convenience of automated data collection [54].
The sample was limited to British diners who were mindful of green dining establishments and were willing to dine at such establishments in the near future. A purposive quota sampling method enhanced the results’ generalizability and provided a gender-balanced representative sample. The final number of usable surveys that were analyzed was 896. In the gender category, the study sample comprised 484 women (54%) and 412 men (46%). In the age category, 47% of the sample were aged 20–39, followed by smaller proportions aged 40–49 (19.8%), 50–59 (13.3%), 60 and above (11.2%), and under 20 (8.7%). Married individuals (40.6%) outnumbered those who reported being single (34.9%), de facto (13.6%), divorced (4.4%), separated (3.9%), or widowed (2.6%). The respondents were mainly employed full-time (44.2%) or part-time (25.3%). As for education, 45% of the participants reported holding an undergraduate degree, and 23.1% hold a postgraduate degree, while the percentage of participants with college certificates and vocational training was 31.9%. The gross annual income for most of the respondents was between GBP 30,000 and 100,000.

3.3. Data Analysis

SPSS and AMOS 22 were employed to analyze the data. First, a data screening process was conducted rigorously. Researchers used two main techniques to control common method bias: research procedure design and statistical controls. Firstly, participants were informed that the survey was developed and implemented, bearing in mind their anonymity; as a result, they were less likely to change their answers to make them more socially acceptable [55]. Secondly, Harman’s one-factor test was conducted on the scale measurement items. Principal component analysis (PCA) revealed a 6-factor solution, with a total variance explained of 68%, with factor loadings for measurement items above 0.5 and communalities above 0.6.
Afterwards, a two-step structural equation modeling (SEM) approach was performed [56]. The first step involved confirmatory factor analysis (CFA) which mainly validates the constructs’ reliability and validity (measurement model). The next step involved obtaining the best-fitting model and examining the relationships between the factors (structural model) through SEM. Multiple regression and factor analysis could be collectively performed to assess a series of dependent relationships by utilizing SEM simultaneously. Finally, to examine the effect of demographic variables, ANOVA tests were performed.

4. Results

4.1. Hypotheses Results

CFA was employed to evaluate the model fit using the indicators of the goodness of fit [57]. Specifically, all constructs were considered for unidimensionality, construct validity, and reliability.
The CFA findings revealed that the model fits the data (x2 = 583.4, df = 156, p < 0.001, x2/df = 3.73, RMSEA = 0.063, CFI = 0.913, TLI = 0.911) [57]. According to these researchers, the proposed recommended level for RMSEA is a value smaller than or equal to 0.08 [57]. Composite reliability, which signifies the internal consistency, varied between 0.603 and 0.943. These values surpassed the proposed threshold of 0.6 [57]. The average variance extracted (AVE) values exceeded the recommended threshold level of 0.5 [57] and ranged between 0.6311 and 0.923. In addition, AVE was higher than the squared values for the correlation with the related construct between constructs [57]. Consequently, discriminant and convergent validity were validated. The details of the CFA results are presented in Table 1.
Later, structural equation modeling (SEM) was conducted. For hypotheses testing, path coefficients of the augmented TPB model were analyzed. The findings from the SEM are summarized in Figure 2 and Table 2.
Regarding the TPB major constructs, the findings indicated that behavioral intentions are a significant function of attitudes (β = 0.32, p < 0.01), subjective descriptive norms (β = 0.12, p < 0.01), and perceived behavioral control (β = 0.52, p < 0.01). Therefore, H1, H3, and H4 were supported. Perceived behavioral control was reported as the most prominent factor in determining intentions. This finding indicates that the degree of barriers perceived by consumers to dining at a green restaurant affects their behavioral intention. As for the influence of subjective injunctive norms on intentions, they were not found to be significant (β = 0.04, p > 0.05). Thus, H2 was not supported. This indicates that respondents’ intention to dine at a green restaurant was not associated with the expectations of significant others. Attitudes, subjective descriptive norms, and control perceptions are responsible for explaining a substantial percentage of the variance in intentions to dine at a green restaurant, and subjective injunctive norms did not impact consumers’ behavioral intentions. Intentions to dine at green establishments were also found to be influenced by past behavior (β = 0.16, p < 0.01); therefore, Hypothesis 5 was supported. This finding justifies the extension of the TPB by including past behavior in the model.
As for the whole model, the obtained R2 was 0.41. This finding implies that approximately 0.41 percent of the variation in intention is explained by attitudes, subjective descriptive norms, perceived behavioral control, and past behavior, which demonstrates the robust predictive power of the theory.

4.2. The Demographics Effect

To examine the effect of sociodemographics on intention (INT) and compare the scores among the different groups, an independent-sample t-test and ANOVA tests were conducted. Firstly, an independent-sample t-test was conducted to compare the intention score for males and females. The findings revealed that males and females differed in their intentions to dine at green dining establishments. The mean score (M) and standard deviation (SD) in intentions for females (M = 5.7, SD = 0.94) were slightly higher than for males (M = 5.3, SD = 0.55). Additionally, there was a significant difference between females and males as to their intentions to dine at a green dining establishment (t = 3.3, p = 0.001).
A one-way between-group analysis of variance (ANOVA) was performed to determine the effect of age on the intentions to dine at green restaurants. Participants were split up into five groups according to their age category. The results indicated that mean scores in dining intentions for the lowest age group (under 20 years) were slightly higher than other groups. Nevertheless, the ANOVA results indicated no significant difference among age groups (intention: F = 1.13, p = 0.21).
The impact of gross income was tested. The findings indicated no statistically significant difference among different groups regarding their intentions to dine at a green dining establishment. Furthermore, the ANOVA tests results did not generate statistically significant disparities in intentions among different income groups (F = 0.54, p = 0.76). Finally, a one-way between-group analysis of variance was performed to determine the impact of education on the intentions to dine at green restaurants. The ANOVA tests results did not generate statistically significant differences in dining intentions among education groups (intention to dine: F = 0.3.6, p = 0.007).

5. Discussion

Consumers’ behavior in the green restaurant context has received limited attention from scholars. This study investigated TPB validity within the green dining establishment context and identified relationships among various constructs of the TPB and past behavior among consumers. Overall, the TPB framework effectively predicted consumers’ intentions to dine at a green dining establishment. The findings indicated that perceived behavioral control, attitude, and descriptive norms predict consumers’ intentions. These conclusions are consistent with previous research. In addition, the TPB model could be augmented by including other constructs to improve the model’s predictive power [30]. Past behavior was included in the model to ascertain if this construct explains additional variance after the primary constructs of the TPB are investigated. The results of this study assisted with the development of a better understanding of consumers’ previous actions and if they impact their intentions to dine at green dining establishments.
The study evaluated the role of the constructs of the TPB within the green dining establishment context. The results of this study assisted in understanding the impact of these constructs on diners’ intentions towards green dining establishments. Surprisingly, the study findings revealed that PBC strongly influences the respondents’ intentions to dine at a green dining establishment, which means that consumers would save and preserve the environment without compromising their own convenience. This same result has been previously reported [58]. A possible explanation of this phenomenon might be the challenges of going green in the mind of the British consumers, such as price, location, standardization, and dearth of information [59]. If any of the previously mentioned challenges existed, consumers’ intention to dine at a green restaurant would be weakened. Hence, it is preferable that restauranteurs communicate with their customers and build some awareness towards choosing a green restaurant and provide information of the existence or not of any potential challenges.
Consumers’ intention to dine at a green restaurant is also affected by the attitude. This finding is in line with the results of previous studies [20,25], indicating that consumers’ attitudes substantially impact their green purchase decision. Furthermore, the findings add to the evidence that marketing appeals stressing a specific behavior’s benefits are perceived as more effective. In other words, individuals might consider performing a given behavior when they assume that such behavior would generate positive outcomes.
It is worth mentioning that this investigation used the updated TPB model, which divides social norms into injunctive and descriptive norms. These two conceptualizations of social norms refer to the expected and most common action in a particular situation [20]. This study provided empirical evidence concerning the influence of these two factors on consumers’ behavioral intentions towards green establishments. Interestingly, the results highlighted that injunctive norms do not significantly impact consumers’ intentions, while descriptive norms do. This could be due to the research sample because these findings suggest that among British consumers, how important referents actually behave in the green restaurant context is more important than how these referents expect individuals to act [60]. Thus, behavioral intentions to dine at green restaurants depended on family, friends, and colleagues’ actions, not their views and expectations [61,62]. However, the association between subjective descriptive norms and green dining intentions is rather weak (β = 0.12). The United Kingdom is regarded as an individualistic society, implying that consumption patterns reflect personal-advocating lifestyles, with marginal reliance on others [63].
Past behavior had a strong impact on behavioral intentions, where customers’ intention to dine at a green restaurant becomes stronger with past experience of such establishments [35]. This finding is consistent with the argument of Fishbein and Ajzen [17] for adding past behavior to the TPB framework since it provides a better insight into consumers’ decision-making process. Thus, green dining establishment managers need to enhance green restaurant consumers’ experience and satisfaction level during their visit.
This study demonstrated that, with the exclusion of gender, diners’ intentions to choose a green dining establishment were not substantially diverse with age, annual income and educational level. The data analysis revealed that female participants had a superior intention of dining at a green restaurant than males. Few previous studies undertaken in the green dining establishment context contain similar results [12,45]. This finding helps restauranteurs understand the characteristics of their target segment. Female consumers tend to handle information in a more comprehensive and explanatory mode, relying on multiple sources of information [47]. Consequently, to attract more women consumers, marketers at green dining establishments should provide more useful and substantial information, and this warrants further investigation.
For the other characteristics, however, the results indicated no difference in intentions among age, income, and education. A number of pro-environmental studies reported insignificant roles of these demographics in the green restaurant setting [46,48,49]. Overall, the findings indicate that aspects of sociodemographic characteristics are not significant in understanding consumers’ intentions to dine at a green dining establishment. This may be encouraging news for restaurant marketers as it gives more flexibility by permitting them to extend their market beyond different target groups.

6. Conclusions

Consumer researchers have called upon future researchers to delve deep into consumers’ behavior in the restaurant sector [10,14,22]. A theory-driven approach towards the behavioral components of environmental issues is expected to provide a strong foundation for recognizing and managing these issues. Therefore, the current research employed the TPB as the framework of the examination, as the ability of this model to predict intentions and behavior has been verified within several settings. Findings from this research confirm the power of the TPB to predict British consumers’ intentions to dine at green restaurants. Some researchers argue that limited attention has been devoted to recognizing determinants influencing green decisions [26]. Further, the findings also suggest four main key constructs (attitude, subjective descriptive norms, perceived behavioral control, and past behavior) that affect consumers’ decisions towards dining at a green restaurant in the UK. Therefore, this study contributes to the context of green restaurants by adopting an empirical investigation using the TPB extended framework to explain consumers’ behavior.
This is the first study to separately assess injunctive and descriptive norms in the green restaurant context to the authors’ knowledge. Moreover, some studies report that diners might be alarmed by environmental issues [12]; others suggest that consumers are skeptical about restaurants’ environmental practices [15]. Subsequently, this study offers a unique aspect to the recent understanding of British consumers’ behavioral intentions towards dining at green restaurants.
This investigation provides some practical suggestions to dining establishment managers about positively influencing diners’ behavior towards green restaurants. This is mainly warranted due to the restaurant industry’s reported negative impact on the environment and its effects on consumer dining behavior. As a result, managers and owners of dining establishments are under pressure, driven by increasing consumer demand, to become environmentally friendly with their restaurant operations and initiatives. The current study implied that concerned managers, who are willing to embrace pro-environmental strategies, can better understand and influence consumers’ behavioral intentions, which is central to the decision-making process. Furthermore, managers who advertise their green operations and programs gain a competitive advantage over similar dining establishments that adopt traditional procedures and operations. To ensure that customers are well-informed, managers should design promotional efforts that primarily describe the restaurant’s broad green programs. These efforts could emphasize the perception that many significant others would dine at such establishments and reinforce the positive outcomes of dining at green restaurants. Consequently, consumers who dine at green restaurants may develop solid personal beliefs that their eating habits align with their environmental responsibilities. Managers must also obtain independent third-party accreditation and communicate it with their customers. These efforts may assist customers in becoming more familiar with the green initiatives implemented in such establishments, allowing consumers to make better-informed decisions.
This study revealed the strong impact of PBC; therefore, it is advisable for restaurateurs to improve the accessibility of their green dining establishments and disseminate information through all means to attract potential consumers [58]. Though consumers might hold positive perceptions of green restaurants, they might also be concerned about the factors that obstruct their decision. Subsequently, restauranteurs need to deliver marketing messages that clarify the aims of their green initiatives to enable them to grasp the concepts behind applying such initiatives and sculpt the reputation of these restaurants. These messages should also aim to create a sense of control for these consumers. As consumers are not yet sufficiently ready to sacrifice for the environment, restaurants should simply become accessible to these consumers by maximizing exposure and disseminating information. Further, they ought to inform prospective diners that the execution of pro-environmental initiatives does not essentially compromise the service quality and that the charged prices in green restaurants are quite sensible. The challenge for restaurant managers is finding the right balance via integrity and clarity in their promotions and green initiatives. Hopefully, with several means of information dissemination, consumers’ environmental concerns will be elevated, eventually leading them to dine at green restaurants. Restaurant managers should also enhance the dining experience of their consumers as this would help build customer loyalty and create positive word of mouth regarding their experience in green restaurants [20].
Finally, consumer behavior research in the context of green restaurants has frequently endeavored to examine consumers’ intentions and link them with demographic characteristics [14,48]. However, apart from gender, the relationships between consumers’ sociodemographic characteristics and intentions to dine at green restaurants were insignificant. Consequently, females could be targeted with effective and transparent environmental knowledge as they embody an essential target market, which merits further investigation.

7. Limitations and Directions for Further Research

As with all empirical work, this research includes some limitations. Firstly, this study examined intention instead of behavior. Therefore, it is advisable to collect data to examine the actual consumers’ decision-making process in relation to dining at a green restaurant. Secondly, an online questionnaire was distributed to reach many diners across the UK. However, it would be interesting to collect the data in a real setting with restaurants employing green initiatives to assess their decision-making process [13].
This study shed light on the significance of looking thoroughly at different variables that could be investigated to ensure the completeness of the model as the model used in this study explained only 41% of the participants’ behavioral intentions. This indicates that there are many more factors researchers could dig deeper into that could be associated with consumers’ behavioral intention. For instance, they could look at the role of knowledge and self-concepts. Future research could replicate this study in countries other than the UK to examine if the investigated constructs are identified as significant in different cultures. In summary, this study presents the effect of some psychological and demographic components on diners’ behavioral intentions, which is anticipated to enhance our knowledge regarding the decision-making process employed by these diners in the green restaurant setting.

Author Contributions

Conceptualization, F.S. and R.M.; methodology, R.M. and B.A.K. and M.T.A.; software, F.J.A.; validation, B.A.K. and F.J.A.; formal analysis, R.M.; investigation, M.T.A.; resources, F.S.; data curation, R.M.; writing—original draft preparation, F.S. and R.M.; writing—review and editing F.S. and B.A.K.; visualization, B.A.K.; supervision, F.S.; project administration, F.S. and M.T.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Liu, K.-N.; Hu, C.; Lin, M.-C.; Tsai, T.-I.; Xiao, Q. Brand knowledge and non-financial brand performance in the green restaurants: Mediating effect of brand attitude. Int. J. Hosp. Manag. 2020, 89, 102566. [Google Scholar] [CrossRef]
  2. Intergovernmental Panel on Climate Change. Climate Change 2021—Impacts, Adaptation and Vulnerability: Regional Aspects; Cambridge University Press: Cambridge, UK, 2021. [Google Scholar]
  3. United Nations Environmental Programme. The Sustainable Tourism Programme. Available online: https://stories.undp.org/categories/sustainable-tourism?year=2020 (accessed on 9 November 2021).
  4. Fang, Y.; Yin, J.; Wu, B. Climate change and tourism: A scientometric analysis using CiteSpace. J. Sustain. Tour. 2018, 26, 108–126. [Google Scholar] [CrossRef]
  5. Alaali, N.; Al Marzouqi, A.; Dahabreh, F.; Mouzaek, E.; Portal, R.; Salloum, S. The Impact of Adopting Corporate Governance Strategic Performance in the Tourism Sector: A Case Study in the Kingdom of Bahrain. J. Leg. Ethical Regul. 2021, 24, 1–18. [Google Scholar]
  6. Fennell, D.A.; Bowyer, E. Tourism and sustainable transformation: A discussion and application to tourism food consumption. Tour. Recreat. Res. 2020, 45, 119–131. [Google Scholar] [CrossRef]
  7. Alshurideh, M.; Kurdi, B.A.; Shaltoni, A.M.; Ghuff, S.S. Determinants of pro-environmental behavior in the context of emerging economies. Int. J. Sustain. Soc. 2019, 11, 257–277. [Google Scholar] [CrossRef]
  8. Panda, T.K.; Kumar, A.; Jakhar, S.; Luthra, S.; Garza-Reyes, J.A.; Kazancoglu, I.; Nayak, S.S. Social and environmental sustainability model on consumers’ altruism, green purchase intention, green brand loyalty and evangelism. J. Clean. Prod. 2020, 243, 118575. [Google Scholar] [CrossRef]
  9. Alameeri, K.; Alshurideh, M.; Al Kurdi, B.; Salloum, S.A. The Effect of Work Environment Happiness on Employee Leadership. In International Conference on Advanced Intelligent Systems and Informatics; Springer: Cario, Egypt, 2020; pp. 668–680. [Google Scholar]
  10. Han, H. Theory of green purchase behavior (TGPB): A new theory for sustainable consumption of green hotel and green restaurant products. Bus. Strategy Environ. 2020, 29, 2815–2828. [Google Scholar] [CrossRef]
  11. Peng, N. Luxury restaurants’ risks when implementing new environmentally friendly programs–evidence from luxury restaurants in Taiwan. Int. J. Contemp. Hosp. Manag. 2020, 32, 2409–2427. [Google Scholar] [CrossRef]
  12. Namkung, Y.; Jang, S. Are consumers willing to pay more for green practices at restaurants? J. Hosp. Tour. Res. 2017, 41, 329–356. [Google Scholar] [CrossRef]
  13. Nimri, R.; Dharmesti, M.; Arcodia, C.; Mahshi, R. UK consumers’ ethical beliefs towards dining at green restaurants: A qualitative evaluation. J. Hosp. Tour. Manag. 2021, 48, 572–581. [Google Scholar] [CrossRef]
  14. Sarmiento, C.V.; El Hanandeh, A. Customers’ perceptions and expectations of environmentally sustainable restaurant and the development of green index: The case of the Gold Coast, Australia. Sustain. Prod. Consum. 2018, 15, 16–24. [Google Scholar] [CrossRef]
  15. Lee, K. Consumer Skepticism about Quick Service Restaurants’ Corporate Social Responsibility Activities. J. Foodserv. Bus. Res. 2020, 23, 417–441. [Google Scholar] [CrossRef]
  16. Kim, M.J.; Hall, C.M. Can sustainable restaurant practices enhance customer loyalty? The roles of value theory and environmental concerns. J. Hosp. Tour. Manag. 2020, 43, 127–138. [Google Scholar] [CrossRef]
  17. Fishbein, M.; Ajzen, I. Predicting and Changing Behavior: The Reasoned Action Approach; Taylor & Francis: Abingdon, UK, 2010. [Google Scholar]
  18. Paul, J.; Modi, A.; Patel, J. Predicting green product consumption using theory of planned behavior and reasoned action. J. Retail. Consum. Serv. 2016, 29, 123–134. [Google Scholar] [CrossRef]
  19. Gao, L.; Wang, S.; Li, J.; Li, H. Application of the extended theory of planned behavior to understand individual’s energy saving behavior in workplaces. Resour. Conserv. Recycl. 2017, 127, 107–113. [Google Scholar] [CrossRef]
  20. Nimri, R.; Patiar, A.; Kensbock, S.; Jin, X. Consumers’ intention to stay in green hotels in Australia: Theorization and implications. J. Hosp. Tour. Res. 2020, 44, 149–168. [Google Scholar] [CrossRef]
  21. Jang, S.Y.; Chung, J.Y.; Kim, Y. Effects of Environmentally Friendly Perceptions on Customers’ Intentions to Visit Environmentally Friendly Restaurants: An Extended Theory of Planned Behavior. Asia Pac. J. Tour. Res. 2015, 20, 599–618. [Google Scholar] [CrossRef]
  22. Moon, S.-J. Investigating beliefs, attitudes, and intentions regarding green restaurant patronage: An application of the extended theory of planned behavior with moderating effects of gender and age. Int. J. Hosp. Manag. 2021, 92, 102727. [Google Scholar] [CrossRef]
  23. de Vries, H.; Dijkstra, M.; Kuhlman, P. Self-efficacy: The third factor besides attitude and subjective norm as a predictor of behavioral intentions. Health Educ. Res. 1988, 3, 273–282. [Google Scholar] [CrossRef]
  24. Towler, G.; Shepherd, R. Modification of Fishbein and Ajzen’s theory of reasoned action to predict chip consumption. Food Qual. Prefer. 1991, 3, 37–45. [Google Scholar] [CrossRef]
  25. Han, H.; Hsu, T.; Sheu, C. Application of the Theory of Planned Behavior to green hotel choice: Testing the effect of environmental friendly activities. Tour. Manag. 2010, 31, 325–334. [Google Scholar] [CrossRef]
  26. Myung, E.; McClaren, A.; Li, L. Environmentally related research in scholarly hospitality journals: Current status and future opportunities. Int. J. Hosp. Manag. 2012, 31, 1264–1275. [Google Scholar] [CrossRef]
  27. Yang, E.C.L.; Nimri, R.; Lai, M.Y. Uncovering the critical drivers of solo holiday attitudes and intentions. Tour. Manag. Perspect. 2022, 41, 100913. [Google Scholar] [CrossRef]
  28. Ajzen, I. The theory of planned behavior: Reactions and reflections. Psychol. Health 2011, 26, 1113–1127. [Google Scholar] [CrossRef] [PubMed]
  29. Chang, L.-l. Influencing Factors on Creative Tourists’ Revisiting Intentions: The Roles Of Motivation, Experience And Perceived Value. Ph.D. Thesis, Clemson University, Clemson, SC, USA, 2013. [Google Scholar]
  30. Ajzen, I. The Theory of Planned Behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [Google Scholar] [CrossRef]
  31. Lam, T.; Hsu, C.H. Theory of planned behavior: Potential travelers from China. J. Hosp. Tour. Res. 2004, 28, 463–482. [Google Scholar] [CrossRef]
  32. Sommer, L. The theory of planned behavior and the impact of past behavior. Int. Bus. Econ. Res. J. 2011, 10, 91. [Google Scholar]
  33. Ouellette, J.A.; Wood, W. Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychol. Bull. 1998, 124, 54. [Google Scholar] [CrossRef]
  34. Wang, J.; Ritchie, B.W. Understanding accommodation managers’ crisis planning intention: An application of the theory of planned behavior. Tour. Manag. 2012, 33, 1057–1067. [Google Scholar] [CrossRef]
  35. Han, H.; Kim, Y. An investigation of green hotel customers’ decision formation: Developing an extended model of the theory of planned behavior. Int. J. Hosp. Manag. 2010, 29, 659–668. [Google Scholar] [CrossRef]
  36. Namkung, Y.; Jang, S. Effects of restaurant green practices on brand equity formation: Do green practices really matter? Int. J. Hosp. Manag. 2013, 33, 85–95. [Google Scholar] [CrossRef]
  37. Higgins-Desbiolles, F.; Moskwa, E.; Wijesinghe, G. How sustainable is sustainable hospitality research? A review of sustainable restaurant literature from 1991 to 2015. Curr. Issues Tour. 2017, 22, 1–30. [Google Scholar] [CrossRef]
  38. Kim, S.; Lee, K.; Fairhurst, A. The review of “green” research in hospitality, 2000–2014: Current trends and future research directions. Int. J. Contemp. Hosp. Manag. 2017, 29, 226–247. [Google Scholar] [CrossRef]
  39. De Leeuw, A.; Valois, P.; Ajzen, I.; Schmidt, P. Using the theory of planned behavior to identify key beliefs underlying pro-environmental behavior in high-school students: Implications for educational interventions. J. Environ. Psychol. 2015, 42, 128–138. [Google Scholar] [CrossRef]
  40. Teng, Y.M.; Wu, K.S.; Liu, H.H. Integrating Altruism and the Theory of Planned Behavior to Predict Patronage Intention of a Green Hotel. J. Hosp. Tour. Res. 2015, 39, 299–315. [Google Scholar] [CrossRef]
  41. Hsu, C.; Huang, S. An Extension of the Theory of Planned Behavior Model for Tourists. J. Hosp. Tour. Res. 2010, 36, 390–417. [Google Scholar] [CrossRef]
  42. Hagger, M.S.; Chatzisarantis, N.L.; Barkoukis, V.; Wang, J.C.; Hein, V.; Pihu, M.; Soós, I.; Karsai, I. Cross-cultural generalizability of the theory of planned behavior among young people in a physical activity context. J. Sport Exerc. Psychol. 2007, 29, 1–19. [Google Scholar] [CrossRef] [Green Version]
  43. Fishbein, M.; Ajzen, I. Attitude, Intention and Behavior: An Introduction to Theory and Research Reading; Addison-Wesley: Boston, MA, USA, 1975. [Google Scholar]
  44. Ryu, K.; Jang, S. Intention to experience local cuisine in a travel destination: The modified theory of reasoned action. J. Hosp. Tour. Res. 2006, 30, 507–516. [Google Scholar] [CrossRef]
  45. DiPietro, R.B.; Gregory, S.; Jackson, A. Going green in quick-service restaurants: Customer perceptions and intentions. Int. J. Hosp. Tour. Adm. 2013, 14, 139–156. [Google Scholar] [CrossRef]
  46. Berezan, O.; Millar, M.; Raab, C. Sustainable Hotel Practices and Guest Satisfaction Levels. Int. J. Hosp. Tour. Adm. 2014, 15, 1–18. [Google Scholar] [CrossRef]
  47. Kim, D.-Y.; Lehto, X.Y.; Morrison, A.M. Gender differences in online travel information search: Implications for marketing communications on the internet. Tour. Manag. 2007, 28, 423–433. [Google Scholar] [CrossRef]
  48. Nicolau, J.L.; Guix, M.; Hernandez-Maskivker, G.; Molenkamp, N. Millennials’ willingness to pay for green restaurants. Int. J. Hosp. Manag. 2020, 90, 102601. [Google Scholar] [CrossRef]
  49. Han, H.; Hsu, T.; Lee, A.; Sheu, C. Are lodging customers ready to go green? An examination of attitudes, demographics, and eco-friendly intentions. Int. J. Hosp. Manag. 2011, 30, 345–355. [Google Scholar] [CrossRef]
  50. Creswell, J.W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches; Sage Publications: Thousand Oaks, CA, USA, 2013; Volume 4. [Google Scholar]
  51. Denzin, N.K.; Lincoln, Y.S. The Sage Handbook of Qualitative Research; Sage: Thousand Oaks, CA, USA, 2011; Volume 4. [Google Scholar]
  52. Collingridge, D. Validating a questionnaire. Retrieved Febr. 2014, 25, 2017. [Google Scholar]
  53. Netemeyer, R.; Bearden, W.; Sharma, S. Scaling Procedures: Issues and Applications; Sage Publications: Thousand Oaks, CA, USA, 2003. [Google Scholar]
  54. Van Selm, M.; Jankowski, N.W. Conducting online surveys. Qual. Quant. 2006, 40, 435–456. [Google Scholar] [CrossRef]
  55. Kang, H.J.A.; Busser, J.A. Impact of service climate and psychological capital on employee engagement: The role of organizational hierarchy. Int. J. Hosp. Manag. 2018, 75, 1–9. [Google Scholar] [CrossRef]
  56. Anderson, J.C.; Gerbing, D.W. Structural equation modeling in practice: A review and recommended two-step approach. Psychol. Bull. 1988, 103, 411. [Google Scholar] [CrossRef]
  57. Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E. Multivariate Data Analysis; Pearson: London, UK, 2010. [Google Scholar]
  58. Chang, L.H.; Tsai, C.H.; Yeh, S.S. Evaluation of Green Hotel Guests’ Behavioral Intention. Adv. Hosp. Leis. 2014, 10, 75–89. [Google Scholar]
  59. Nimri, R.; Patiar, A.; Kensbock, S. A green step forward: Eliciting consumers’ purchasing decisions regarding green hotel accommodation in Australia. J. Hosp. Tour. Manag. 2017, 33, 43–50. [Google Scholar] [CrossRef]
  60. Al kurdi, B. Healthy-Food Choice and Purchasing Behavior Analysis: An Exploratory Study of Families in the UK. PhD. Thesis, Durham University, Durham, UK, 2016. [Google Scholar]
  61. Alshurideh, M.T. Do we care about what we buy or eat? A practical study of the healthy foods eaten by Jordanian youth. Int. J. Bus. Manag. 2014, 9, 65. [Google Scholar] [CrossRef]
  62. Joghee, S.; Alzoubi, H.M.; Alshurideh, M.; Al Kurdi, B. The Role of Business Intelligence Systems on Green Supply Chain Management: Empirical Analysis of FMCG in the UAE. In Proceedings of the International Conference on Artificial Intelligence and Computer Vision, Settat, Morocco, 28–30 June 2021; Springer: Settat, Morocco, 2021; pp. 539–552. [Google Scholar]
  63. Hofstede, G. Dimensionalizing Cultures: The Hofstede Model in Context. Online Read. Psychol. Cult. 2011, 2, 1–26. [Google Scholar] [CrossRef]
Sustainability 14 00276 g001 550
Figure 1. Proposed extended theory of planned behavior model.
Figure 1. Proposed extended theory of planned behavior model.
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Figure 2. Path analysis for the model. ** p < 0.01. Note ATT: attitude; SIN: subjective injunctive norm; SDN: subjective descriptive norm; PBC: perceived behavioral control; PB; past behavior; INT: intention.
Figure 2. Path analysis for the model. ** p < 0.01. Note ATT: attitude; SIN: subjective injunctive norm; SDN: subjective descriptive norm; PBC: perceived behavioral control; PB; past behavior; INT: intention.
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Table
Table 1. Correlations among latent constructs (squared) and reliabilities of constructs.
Table 1. Correlations among latent constructs (squared) and reliabilities of constructs.
MeasureATTSINSDNPBCPBINT
ATT1.000
SIN0.077 (0.006)1.000
SDN0.335 (0.112)0.647 (0.419)1.000
PBC0.379 (0.143)0.031 (0.001)0.242 (0.059)1.000
PB0.145 (0.021)0.077 (0.006)0.269 (0.072)0.463 (0.214)1.000
INT0.187 (0.035)0.154 (0.024)0.306 (0.0936)0.682 (0.465)0.631 (0.398)1.000
Mean5.454.784.925.835.265.31
SD0.9231.0711.1871.2350.9821.288
CR0.9430.6030.9090.8070.7280.768
AVE0.7180.6110.9230.7890.6430.741
Note: ATT: attitude; SIN: subjective injunctive norm; SDN: subjective descriptive norm; PBC: perceived behavioral control; PB; past behavior; INT: intention. Model measurement fit: x2 = 583.4, df = 156, p < 0.001, x2/df = 3.73, RMSEA = 0.063, CFI = 0.913, TLI = 0.911.
Table
Table 2. Structural equation modeling results.
Table 2. Structural equation modeling results.
PathsCoefficientT-ValueHypotheses
ATT → INT0.326.53H1: Supported
SIN → INT0.040.68H2: Not Supported
SDN → INT0.122.12H3: Supported
PBC → INT0.5218.19H4: Supported
PB → INT0.163.76H5: Supported
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Shishan, F.; Mahshi, R.; Al Kurdi, B.; Alotoum, F.J.; Alshurideh, M.T. Does the Past Affect the Future? An Analysis of Consumers’ Dining Intentions towards Green Restaurants in the UK. Sustainability 2022, 14, 276. https://doi.org/10.3390/su14010276

AMA Style

Shishan F, Mahshi R, Al Kurdi B, Alotoum FJ, Alshurideh MT. Does the Past Affect the Future? An Analysis of Consumers’ Dining Intentions towards Green Restaurants in the UK. Sustainability. 2022; 14(1):276. https://doi.org/10.3390/su14010276

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Shishan, Farah, Ricardo Mahshi, Brween Al Kurdi, Firas Jamil Alotoum, and Muhammad Turki Alshurideh. 2022. "Does the Past Affect the Future? An Analysis of Consumers’ Dining Intentions towards Green Restaurants in the UK" Sustainability 14, no. 1: 276. https://doi.org/10.3390/su14010276

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