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The purpose of this paper is to investigate the relationship between consumption values (CV), destination cues (DC), nostalgia and attitude in the selection of destination for educational tourism, and the mediating effect of destination image (DI).

The research applied descriptive statistics, confirmatory factor analysis (CFA) and structural equation modelling techniques. The study tested the reliability and validity of the measurement model through CFA, Cronbach’s α and inter-correlation analyses. This research applied the structural equation model to examine the relationship between the research variables using 250 foreign students.

The results of data analysis support the stated hypotheses. All the direct relationships were significant and positive. However, DI found a partial mediating role among the relationships. Theoretical and practical implications are also discussed.

From this research the tourism researchers, policymakers and managers of the respective higher learning institution may develop a complete understanding of the antecedents of attitude formation of the edu-tourists which were not even studied before from the perspective of educational tourism.

To date, there have been few empirical studies examining the attitude of the edu-tourists in the selection of a destination for educational tourism. Therefore, understanding the purpose of CV, DC and nostalgia in a tourist’s decision-making operation, and their theoretical relationship, will make both scientific and practical contributions.

This study aims to provide novel insight into cognitive and emotional factors contributing to green customer citizenship behaviours, as mediated by green attitudes in general and moderated by culture.

The investigation was guided by the “value attitude behaviour hierarchy” and green customer emotions, which served as a framework for understanding the mediating effect of attitude on the relationships between cognitive and emotional factors (green consumption values and emotional affinity towards nature) and customer citizenship advocacy and feedback behaviours. Data was obtained from respondents in the USA and South Korea. Multi-group confirmatory factor analysis, structural equation modelling, bootstrapping and Wald tests were performed to conclude on the model and verify the moderating effect of culture on the indirect effects established.

In both countries, green consumption values and emotional affinity towards nature positively influence green attitudes and stimulate feedback behaviour. Green attitudes only predict advocacy in the USA. Culture moderates the majority of the indirect effects examined.

The model presents a novel approach to stimulate green advocacy and feedback behaviours and may aid firms in closing the “green gap” and co-create value with customers. Firms could profit from customers advocating the benefits of green purchasing to other customers and providing feedback on interventions required that will convince reluctant customers to make a purchase.

This study offers a multicultural perspective on the connection between a novel set of cognitive and emotional factors and green customer citizenship advocacy and feedback behaviours that may directly and indirectly influence green purchasing, value co-creation and closing of the “green gap”.

This study aims to develop a framework to identify the drivers underpinning food tourists' behavioral intentions (BIs). This framework centers on examining how local food consumption value (TLFCV), local food experiential value (TLFEV) and social media influencers (SMIs) impact upon tourists’ attitudes toward local food (ATLF) and food destination image (FDI). The impact of ATLF and FDI on tourists’ BIs is also examined.

PLS-SEM was used to test the hypothesized relationships using survey responses from 379 tourists visiting Rasht, Iran.

The results demonstrate that TLFCV, TLFEV and SMIs can be used to populate a theoretical framework for predicting and understanding the factors influencing tourists’ ATLF and FDI. Specifically, positive ATLF and FDI stimulated positive BIs (e.g., intending to recommend Iranian food to others and intending to revisit Iran in future for culinary tourism purposes).

The findings provide managers and practitioners within the culinary tourism industry with suggestions for how best to strategically market their offerings to increase inbound food tourism.

This study is one of the first to empirically evaluate the drivers of food tourists' BIs, presenting a newly developed model for deployment in future research. Originality is also established by simultaneously investigating TLFCV and TLFEV within the context of food tourism.

Consumer value (CV) is endemic to marketing, and therefore, it is a crucial notion to understand the evolution of tourism research. This paper aims to review the main achievements made on CV in tourism and hospitality literature and also the shortcomings and propose avenues for future research on tourism through the lens of CV.

Through relevant citations from 1975 to 2020, a figure describes diachronically the role of CV in different paradigm flaws, both pre and post digitization: experiential consumption in the 1980s, service quality-satisfaction discussion in early 1990s, customer relationship in late 1990s and Service Dominant Logic in 2000s and beyond.

Tourism services have been preferred fields for inquiry on CV, helping to describe the idiosyncrasy of nearly all tourism consumption settings. Although there is not a clear picture on the number and nature of value dimensions (intra-variable perspective), nor in the direct and indirect effects on the quality-value-satisfaction-loyalty chain (inter-variable), new CV frameworks favor ecosystems of value (different stakeholders, different times and places and mixed motivations) in more comprehensive models.

This paper depicts how CV has contributed to tourism development as a behavioral science through the past 75 years. Moreover, it preconizes that CV is still a valid construct to address all new challenges of human beings as tourists, either online or offline, by enlightening phenomena such as e-value co-creation, over-tourism, peer-to-peer consumption and the power of tourism transformative value.

The rail transport sector in China represents one of the largest consumers of energy today, and the primary purpose of this paper is to examine the causes of changes in energy consumption of Chinese national rail transport (ECCNRT).

For this study, reasonable indicators as factors that affected conversion volume (CV) and unit energy consumption (UEC) based on statistical data from 1990 to 2010 were selected. CV and UEC models were established by regression analysis and tested using real data of 2011-2014. The CV model indicates it has an exponential relationship with GDP. Besides, there is a quantitative relationship between UEC and the quantity of locomotives. The ECCNRT calculation model was proposed and ECCNRT model data were compared with the real data. Impacts of different factors on ECCNRT were analyzed with economic principles.

The analysis conducted shows that the calculation model can reflect variation of ECCNRT precisely, and ECCNRT has a quantitative relation with GDP and quantities of locomotives. GDP accounts for changes of ECCNRT 20.02 per cent, while those for quantity of diesel locomotives and electric locomotives are 26.87 and 53.11 per cent, respectively. The number of electric locomotives is the main factor that influences variation of ECCNRT.

Through regression analysis, this study discovered the inner quantitative relationship between the conversion volume (important index of Chinese national rail transport production) and GDP. In addition, this study establishes the ECCNRT model according to the Chinese national rail transport data, which can be used to calculate the amount of ECCNRT and conduct quantitative analysis for different impacts of various factors on ECCNRT’s changes.

This research paper aims to investigate the effects of gradual deployment of market penetration rates (MPR) of connected vehicles (MPR of CVs) on delay time and fuel consumption.

A real-world origin-destination demand matrix survey was conducted in Boston, MA to identify the number of peak hour passing vehicles in the case study.

The results showed that as the number of CVs (MPR) in the network increases, the total delay time decreases by an average of 14% and the fuel consumption decreases by an average of 56%, respectively, from scenarios 3 to 15 compared to scenario 2.

The first limitation of this study was considering a small network. The considered network shows a small part of the case study.

This study can be a milestone for future research regarding gradual deployment of CVs’ effects on transport networks. Efficient policy(s) may define based on the results of this network for Brockton transport network.

The purpose of this paper is to study the service-profit chain (SPC) on e-service quality dimensions, online customer value (CV) dimensions, e-satisfaction, and e-loyalty in an e-commerce context.

A total of 2,813 internet customers filled in an online questionnaire after completing a specified task on one of 28 wine web sites from seven countries.

The results highlight the impact of the dimensions of e-service quality (information, aesthetics, ease of use, security/privacy, and reliability) on the dimensions of online CV (functional, economic, and social value) as they affect e-satisfaction, which in turn influences e-loyalty. The results validate the SPC in an e-commerce context and also stress the partial mediating role of the dimensions of online CV between the dimensions of e-service quality and e-satisfaction.

The sample may not exactly match the customer profile of the web sites analyzed. In order to generalize the results, future research should replicate this study with a customer sample from each web site. Future research could also take into account other variables that may have an influence on the relationships identified. Additionally it would be interesting to replicate the study in other industries and undertake longitudinal studies in one or more industries.

From a managerial point of view, online retailers, especially in the wine sector, can positively affect CV, satisfaction, and loyalty by focussing on information, aesthetics, ease of use, security/privacy, and reliability.

This paper is the first to study the SPC by examining service quality dimensions, CV dimensions, satisfaction, and loyalty in an online context. It extends the knowledge of online retailing by validating the SPC on the dimensions of traditional service concepts, such as service quality and CV. The findings can assist online retailers to better understand the dynamics of online customer relationships and the implications for customer satisfaction and ultimately loyalty.

The purpose of the present study is intended to fill a research gap, by advancing a conceptual model which brings novel insights on the relationships between socially responsible consumption and consumer’s need for uniqueness.

Relying on a questionnaire-based survey for data collection, the proposed model was tested using the partial least squares (PLS) algorithm for structural equation modeling (SEM), which allows the assessment of the models containing both formative and reflective constructs.

The research found that 73.7 per cent of the variance in the consumer’s belief in the importance of personal power to make a difference through socially responsible choices is explained by the proposed model. Moreover, four of the five factors of socially responsible consumption fully mediate the positive effect of the consumer’s need for uniqueness on the importance attached to personal socially responsible choices in driving positive change.

The study avails a phenomenological perspective by offering novel insights from a Romanian sample. The limitation associated with a country-centric vision is compensated through the contextual analysis and integration of a new point of reference in the overall framework of socially responsible consumption.

The evidence is indicative of new consumption insights and should be closely considered by companies.

The study draws upon a conceptual model integrating the relationships between socially responsible consumption and a psychological characteristic – the consumer’s need for uniqueness – which has been never tested as such before.

Electricity demand forecasting has always been a key issue, and inaccurate forecasts may mislead policymakers. To accurately predict China’s electricity demand up to 2030, this paper aims to establish a cross-validation-based linear model selection system, which can consider many factors to avoid missing useful information and select the best model according to estimated out-of-sample forecast performances.

With the nine identified influencing factors of electricity demand, this system first determines the parameters in four alternative fitting procedures, where for each procedure a lot of cross-validation is performed and the most frequently selected value is determined. Then, through comparing the out-of-sample performances of the traditional multiple linear regression and the four selected alternative fitting procedures, the best model is selected in view of forecast accuracy and stability and used for forecasting under four scenarios. Besides the baseline scenario, this paper investigates lower and higher economic growth and higher consumption share.

The results show the following: China will consume 7,120.49 TWh, 9,080.38 TWh and 11,649.73 TWh of electricity in 2020, 2025 and 2030, respectively; there is hardly any possibility of decoupling between economic development level and electricity demand; and shifting China from an investment-driven economy to a consumption-driven economy is greatly beneficial to save electricity.

Following insights are obtained: reasonable infrastructure construction plans should be made for increasing electricity demand; increasing electricity demand further challenges China’s greenhouse gas reduction target; and the fact of increasing electricity demand should be taken into account for China’s prompting electrification policies.

The purpose of this investigation is to develop a hybrid fuzzy TOPSIS methodology in order to understand in a practical and integrated way, the consuming and buying behavior of EU residents towards Fishery and Aquaculture Products (FAPs), with an emphasis in the consumption and buying frequency.

Data were obtained from the Special Eurobarometer Survey (European Union, 2018b), which is a survey of 27,732 EU residents with different socio-demographic characteristics that represent the 28 EU countries. A hybrid fuzzy TOPSIS methodology that synthesizes the consuming and buying behavior of the EU residents toward FAPs was developed.

The results show that among the countries, Spain has the highest consumption and buying patterns of FAPs, while among the generations it corresponds to the residents born between 1928 and 1945. In addition, there are important differences that depend on the country of residence as well as the generation of the residents. The elasticity analysis evidenced that marketing strategies would have the biggest impact in the countries located in the Central-Eastern zone of the EU and on the generation formed by the people born after 1980.

Although in the literature there are many studies that aimed to understand the behavior of consumers for FAPs, few investigations have focused on analyzing and integrating both the consumption and buying behavior, and to our best knowledge, there are no studies providing a methodology that allow making comparisons between different countries regarding the consumption and buying behavior of FAPs.