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The purpose of the present study is to examine and validate a research model encompassing power distance belief, need for uniqueness, self-monitoring, self-construal, social adjustive attitude, and value-expressive attitude as the causal antecedents for conspicuous luxury consumption.

Survey data was collected from a large consumer panel. The study applied a combinatory partial least squares structural equation modelling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approach in examining the research hypotheses and proposition.

The results indicated the effects of power distance belief, need for uniqueness, self-monitoring, and self-construal on social adjustive attitude and value-expressive attitude, which in turn determine conspicuous luxury consumption. In addition, the fsQCA findings revealed three configurations that articulate the complex interactions of the causal antecedents.

This study enriches the literature by providing a comprehensive understanding of the psychological motivation factors that drive conspicuous luxury consumption and assists luxury retailers in developing targeted strategies to appeal to consumers.

This study aims to integrate the theory of planned behavior (TPB) and the value-belief-norm (VBN) theory into a meta-analytic framework to synthesize green consumption literature.

By integrating the findings from 173 studies, a meta-analysis was performed adopting several analytical methods: bivariate analysis, moderation analysis and path analysis.

VBN- and TPB-based psychological factors (adverse consequences, ascribed responsibility, personal norms, subjective norms, attitude and perceived behavioral control) mediate the effects of altruistic, biospheric and egoistic values on green purchase intention. Further, inconsistencies in the proposed relationships are due to cultural factors (i.e. individualism-collectivism, power distance, uncertainty avoidance, masculinity–femininity, short- vs long-term orientation and indulgence-restraint) and countries’ human development status.

The authors selected papers published in English; hence, other relevant papers in this domain published in other languages might have been missed.

The findings are useful to marketers of green offerings in designing strategies, i.e. specific messages, targeting different customers based on countries’ cultural score and human development index, to harvest positive customer responses.

This study is the pioneering attempt to synthesize the TPB- and VBN-based quantitative literature on green consumer behavior to resolve the reported inconsistent findings.

Urbanization is driving the growth of China’s carbon footprint. It’s important to investigate what factors, how and to what extent, affect carbon footprints embedded in various categories of rural and urban households’ consumption.

We employ an environmental extended input-output model to assess and compare the rural-urban household carbon footprints and perform a multivariant regression analysis to identify the varying relationships of the determinants on rural and urban household carbon footprints based on the panel data of Chinese households from 2012 to 2018.

The results show evidence of urbanity density effect on direct carbon footprints and countervailing effect on indirect carbon footprints. The old dependency ratio has no significant effect on rural family emissions but has a significantly negative effect on urban direct and indirect carbon footprints. A higher child dependency ratio is associated with less rural household carbon emissions while the opposite is true for urban households. Taking advantage of recycled fuel saves direct carbon emissions and this green lifestyle benefits urban households more by saving more carbon emissions. There is a positive relationship between consumption structure ratio and direct carbon footprints while a negative relationship with indirect carbon footprints and this impact is less significant for urban households. The higher the price level of water, electricity and fuel, the lower the rural household’s direct carbon footprints. Private car ownership consistently augments household carbon footprints across rural and urban areas.

This paper provides comprehensive findings to understand the relationships between an array of determinants and China’s rural-urban carbon emissions, empowering China’s contribution to the global effort on climate mitigation.

Little is known about how religious-related beliefs (i.e. karmic beliefs and beliefs in a just world) might affect consumers to engage in more environmentally friendly behavior. Drawing on the justice motive theory, this study aims to explore the individual, complementary, congruent and incongruent impacts of karmic beliefs and belief in a just world on consumers’ proenvironmental consumption.

A sample of 736 consumers was recruited by means of a mall-intercept survey in the most populus cities in Vietnam. An advanced technique – polynomial regression with response surface analysis – was used to test the hypothesized model, whereas the PROCESS macro approach was used to estimate indirect effects.

The findings indicate that while karmic beliefs do not directly affect proenvironmental consumption, they can inspire environmentally friendly behaviors through belief in a just world. High levels of both beliefs enhance proenvironmental consumption, but imbalanced levels erode such behaviors. Importantly, the findings revealed gender differences concerning the role of religious beliefs in influencing proenvironmental consumption among male and female consumers.

The findings of this study offered several theoretical and managerial implications for proenvironmental consumption.

The research provides new insights into how religious beliefs (karmic beliefs and belief in a just world) affect, interact, balance and imbalance with each other to trigger proenvironmental consumption. The research also contributes to the sustainable consumption literature by indicating the mediation roles of belief in a just world and proenvironmental consumption intention in the relationship between beliefs in karma and actual proenvironmental consumption behavior, as well as offering empirical evidence about the gender differences regarding these relationships.

The psychological foundations of consumers’ reasons for product choices are analyzed in the field of marketing. The purpose of this research is to identify the implicit reasons for white meat consumption in the UK and Turkey.

In the scope of the means-end chain theory, in-depth interviews were conducted with individuals, and the reasons for consumers’ product preferences were revealed by moving from concrete to abstract.

It has been determined that the white meat consumption of Muslims in the UK is primarily shaped by their religious approach. In Turkey, on the contrary, both consumption patterns and reasons for preference are changing. It has been found that white meat consumption is associated with values such as security needs, satisfaction with life, self-fulfillment and happiness.

This research has contributed to the marketing literature by examining consumers’ implicit consumption reasons for white meat in the context of religion and culture.

Marketing strategies should focus on building trust in halal certification, particularly in the UK. Brands should associate their promotion strategies with feelings of security and happiness, which are associated in the minds of consumers.

This study is a new study in terms of revealing the connotations of consumers about consuming chicken and fish and showing the implicit needs that the brands can emotionally associate with.

Reducing aircraft fuel consumption has become a paramount research area, focusing on optimizing operational parameters like speed and altitude during the cruise phase. However, the existing methods for fuel reduction often rely on complex experimental calculations and data extraction from embedded systems, making practical implementation challenging. To address this, this study aims to devise a simple and accessible approach using available information.

In this paper, a novel analytic method to estimate and optimize fuel consumption for aircraft equipped with jet engines is proposed, with a particular emphasis on speed and altitude parameters. The dynamic variations in weight caused by fuel consumption during flight are also accounted for. The derived fuel consumption equation was rigorously validated by applying it to the Boeing 737–700 and comparing the results against the fuel consumption reference tables provided in the Boeing manual. Remarkably, the equation yielded closely aligned outcomes across various altitudes studied. In the second part of this paper, a pioneering approach is introduced by leveraging the particle swarm optimization algorithm (PSO). This novel application of PSO allows us to explore the equation’s potential in finding the optimal altitude and speed for an actual flight from Algiers to Brussels.

The results demonstrate that using the main findings of this study, including the innovative equation and the application of PSO, significantly simplifies and expedites the process of determining the ideal parameters, showcasing the practical applicability of the approach.

The suggested methodology stands out for its simplicity and practicality, particularly when compared to alternative approaches, owing to the ready availability of data for utilization. Nevertheless, its applicability is limited in scenarios where zero wind effects are a prevailing factor.

The research opens up new possibilities for fuel-efficient aviation, with a particular focus on the development of a unique fuel consumption equation and the pioneering use of the PSO algorithm for optimizing flight parameters. This study’s accessible approach can pave the way for more environmentally conscious and economical flight operations.

Comfort foods consumption and linkages to stress coping strategies have received little attention in the business research on food products and services. This paper aims to explore comfort foods consumption among older Americans and how stress-coping strategies are related to their consumption frequency and variety of comfort foods.

Older Americans aged 50–99 years (N = 1,428) in the Health and Retirement Study were surveyed on their frequency and variety of comfort foods consumption and their consumption coping strategies. Data were analyzed and regression models were estimated.

Demographically, baby boomer, male, and non-Hispanic whites reported higher frequency and variety of comfort foods consumption. Comfort foods consumption in frequency and variety was significantly higher (lower) when “eat more” (“use alcohol”) was the endorsed coping strategy.

Research findings furthered research on the consumption of comfort foods among older American adults and added new insights into their coping behavior, both of which may help businesses be more targeted in serving comfort foods to the mature market and the public sector to tailor their services to older adults.

Using data from five developed countries — the UK, the USA, Norway, Italy and Belgium — food consumption trends are examined. The movement towards healthier eating (internationally) is documented and discussed, and underlying factors which influence the consumer are mentioned. The five countries selected demonstrate many of the typical characteristics of the developed world's eating habits. Probable future trends are listed.

The purpose of this paper is to assess the influence of availability of fruits and vegetables on adult workers' consumption adequacy in the workplace.

A total of 1,344 workers, who have had meals in 30 different companies, located in the city of São Paulo, Brazil, are assessed. Two indicators are used to assess the following: workers' consumption of fruits and vegetables; usual consumption, found through a questionnaire on frequency of consumption of these foods; and workplace consumption, assessed with a food consumption questionnaire provided by the company. Availability of fruits and vegetables in the menus is obtained using the descriptions of meals given to workers on three consecutive days. Data analysis is performed with logistic regression models that used two outcomes: usual consumption of fruits and vegetables and consumption of these foods in the workplace. Explanatory variables are divided into two levels: the first one was comprised by workers' characteristics (sex, age and level of education), and the second one by food availability in the workplace.

Consumption of fruits and vegetables, both the usual one and that in the workplace, is higher in women, and also in older individuals and those with higher level of education. Availability of fruits and vegetables in the workplace has a significant impact on usual food consumption and especially on the workplace, in which case the variable shows greatest impact on consumption.

This study demonstrates the importance of the availability of fruits and vegetables in the workplace that influence consumption of food by workers, revealing the importance of using this environment to promote healthy eating.

This paper aims to develop a single regression model (instead of developing models separately for each thread type) to predict the sewing thread consumption for cotton and polyester staple spun threads.

A single regression model is developed for predicting sewing thread consumption for cotton and polyester threads. The polyester sewing threads have lower sewing thread consumption as compared to cotton threads because of their higher elongation behaviour. The model differentiates between the cotton and polyester sewing threads using their elongation values at peak levels of tensions experienced by the sewing threads during stitch tightening. By comparing the estimated thread consumption values with actual values, the effectiveness of model is evaluated with root mean square error and coefficient of determination (R²).

During the sewing process, by understanding the behaviour of different types of sewing threads, it is possible to develop a single regression model for all types of threads.

The sewing thread consumption can be easily calculated for cotton and polyester sewing threads using a single regression equation using the sewing assembly thickness, stitch density and elongation of thread at peak tension. The garment manufacturers need not depend on different charts for sewing thread consumption for stock management.

The sewing thread consumption is different for different types of threads, and garment manufacturers have to depend on different charts given by sewing thread manufacturers or use different equations for each type of threads. Using this single regression equation, sewing thread consumption for cotton and polyester sewing thread can be estimated accurately.