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Augmented reality (AR) is an advanced version of the dynamic physical space that is perceived and received via visual, audio, digital and other sensory stimuli. The capabilities of virtual technologies change the field of university and education considerably. The necessity of using virtual technologies in the education field was revealed more in unforeseen disasters such as the COVID-19 pandemic. The adoption of a technology by its users is an important factor in the successful implementation of the technology. The present study evaluates several factors affecting the adoption of AR technology in the realm of tertiary education.

This study is applied in nature, and the necessary data were gathered through a survey questionnaire. The opinions of 621 students were investigated using a simple random sampling method. The multinomial logit test was used in this research.

It was found that individual and social factors such as age, education level, major and economic characteristics such as one’s income in a month, expenses of a person in a month, the level of access to high-speed internet and access to a laptop or smartphone are effective in AR technology adoption in the field of academic education.

The theoretical contribution of this study is to identify the key factors that influence the adoption of AR technology and develop a model specifically applicable to the educational field. The results of this research can be used by university managers and educational policymakers for the efficient and effective use of this technology.

This study explores the viability of incorporating more expensive organic wheat flour into speciality bakery products, which are of superior quality, thus justifying the higher cost. As consumers may be reluctant to purchase organic speciality baked goods due to unfavorable taste associations with organic foods, particularly those consumed as a treat or for pleasure, this study investigates the impact of providing taste assurances and origin information on consumer acceptance and WTP for organic speciality bakery products.

Using data from an online survey of US consumers, random parameter logit models were estimated and willingness-to-pay (WTP) values were calculated.

Study results show that the use of more expensive organic flour is justified for speciality bakery products when favorable taste assurances are provided or for consumers who value organic foods. Freshness indictors were only important in the case of speciality breads, but not for other products. Finally, improving consumer awareness of organic labeling standards does not significantly impact their organic product preferences or taste perceptions.

This analysis aims to identify the product information likely to increase the consumption of organic speciality bakery/pastry products and thus support the incorporation of organic wheat flour into these higher-value products.

While previous choice experiment studies have extensively examined consumer preferences for organic products, few have evaluated the impact of providing taste and freshness indicators, particularly in the context of vice goods. This study examines the impact of providing taste and freshness indicators on consumer acceptance and WTP for various organic speciality bakery/pastry products in stated choice experiments, where consumers to not have the option to taste the product. Specifically, we examine if taste and freshness assurances reduce potential negative organic product taste biases.

This paper aims to explore factors contributing to music popularity using machine learning approaches.

A dataset comprising 204,853 songs from Spotify was used for analysis. The popularity of a song was predicted using predictive machine learning models, with the results showing the superiority of the random forest model across key performance metrics.

The analysis identifies crucial genre and audio features influencing music popularity. Additionally, genre specific analysis reveals that the impact of music features on music popularity varies across different genres.

The findings offer valuable insights for music artists, digital marketers and music platform researchers to understand and focus on the most impactful music features that drive the success of digital music, to devise more targeted marketing strategies and tactics based on popularity predictions, and more effectively capitalize on popular songs in this digital streaming age.

While previous research has explored different factors that may contribute to the popularity of music, this study makes a pioneering effort as the first to consider the intricate interplay between genre and audio features in predicting digital music popularity.

This paper aims to explore the outcomes of an analysis on day by day task – journey planning conduct of senior citizens by using a modern dynamic model and a family unit travel overview, gathered in Bhubaneswar, Odisha, of India in 2018. The task-journey planning display assumes an unique time–space-constrained planning development.

The main commitment of this paper is to reveal day by day task – journey planning conduct through a comprehensive dynamic framework. Numerous behavioural subtleties are revealed by the subsequent empirical model. These incorporate the role that income plays in directing outside time consumption decisions of senior citizens. Senior citizens in the most elevated and least salary classes will in general have minor varieties in time consumption decisions than those in middle pay classifications. Generally speaking, the time consumption decisions become progressively steady with expanding age, demonstrating that more task durations and lower task recurrence become progressively predominant with increasing age.

Day by day task-type and area decisions reveal a reasonable irregular utility-amplifying level headed conduct of senior residents. Unmistakably expanding spatial availability to different task areas is an urgent factor in characterizing every day outside task interest of senior residents. It is likewise evident that the assorted variety of outside task-type decisions decreases with rise in age and senior citizens are major touchy to auto journey hour than to travel or non-mechanized journey hour.

The fundamental constraint to the dynamic structure is that the mode decision model was viewed as exogenic to the demonstrating framework. The essential purpose behind this supposition that was that senior citizens in the Bhubaneswar are overwhelmingly customers of the local car. Coordination of the mode decision display part inside this structure would deliver a full task-based journey request model that could catch trip age, starting times, outing circulation and mode decision using a solitary demonstrating framework.

This study aims to investigate the impact of consumer ethnocentrism on consumers' evaluation of blockchain-based traceability information. It also examined how the use of quick response (QR) codes for traceability affects consumers' evaluation of traceable food products.

An online choice experiment was conducted to determine consumers' evaluation of the blockchain-based traceability of Feta cheese with a quota sample of 715 Greek consumers. Pearson bivariate correlation and mean comparison were used to examine the relationship between consumer ethnocentrism and QR use behaviour. Random parameter logit models were employed to examine consumers’ valuation of the examined attributes and interaction terms.

The results show that ethnocentric consumers are willing to pay more for blockchain-based traceability information. Ethnocentric consumers tend to scan QR codes with traceability information. Spending more time reading traceability information embedded in QR codes does not lead to a higher willingness-to-pay (WTP) for traceable food products.

The findings suggest that patriotic marketing messages can draw consumers' attention to blockchain-based traceability information. The modest WTP for and low familiarity with blockchain-based traceability systems raise the need for educating consumers regarding the benefits of blockchain in traceability systems.

This is the first study to provide timely empirical evidence of a positive WTP for blockchain-based traceability information for a processed dairy product. This study is the first to attempt to distinguish the effects of the intention to scan QR codes and reading information embedded in QR codes on consumers’ valuation of food attributes.

The purpose of this paper is to study the effects of sports sponsorship on brand equity using two managerially related outcomes: price premium and market share.

This study uses a best–worst discrete choice experiment (BWDCE) and compares the outcome with that of the purchase intention scale, an established probabilistic measure of purchase intention. The total sample consists of 409 fans of three soccer teams sponsored by three different competing brands: Nike, Adidas and Puma.

With sports sponsorship, fans were willing to pay more for the sponsor’s product, with the sponsoring brand obtaining the highest market share. Prominent brands generally performed better than less prominent brands. The best–worst scaling method was also 35% more accurate in predicting brand choice than a purchase intention scale.

Future research could use the same method to study other types of sponsors, such as title sponsors or other product categories.

Sponsorship managers can use this methodology to assess the return on investment in sponsorship engagement.

Prior sponsorship studies on brand equity tend to ignore market share or fans’ willingness to pay a price premium for a sponsor’s goods and services. However, these two measures are crucial in assessing the effectiveness of sponsorship. This study demonstrates how to conduct such an assessment using the BWDCE method. It provides a clearer picture of sponsorship in terms of its economic value, which is more managerially useful.

The social sciences have extensively studied meals; nonetheless, a few have investigated the menu format, with all the data originating from European countries. Within this framework, the novelty of this research is that it analyses the relationship between social class and lunch structure among adults in a Global South city: Santiago, Chile.

The study worked with data from the Survey of Commensality in Adults (>18) of the Metropolitan Region, which used a questionnaire and a self-administered eating event diary. The analysis unit was lunches (n = 3,595). The dependent variable was the structure of the lunches (single course, starter with a main course, a main course with dessert or a full-course menu with starter, main course and dessert). The independent variable was the individual’s social class (either the working, intermediate or service class).

The data showed that lunches are mostly semi- or fully structured (only 44.5% of the lunches reported by the participants contained a single course). The odds of eating a single course were lower in the service class than the working one and the odds of eating a full-course meal were higher in the service class than the working one.

The results provide new quantitative evidence from a representative sample of a Global South city about the relevance of social class as a differentiating factor in food, specifically regarding the existence of simpler meals among the lower classes.

This study aims to find the key drivers of green innovation in family firms by examining firm characteristics and geographical factors. It seeks to develop a conceptual framework that explains how internal resources and external environments influence environmental innovation practices in these businesses.

Using machine learning (ML) methods, this study develops a predictive model for green innovation in family firms, drawing on data from 3,289 family businesses across 27 EU Member States and 12 additional countries. The study integrates the Resource-Based View (RBV) and Location Theory to analyze the impact of firm-level resources and geographical contexts on green innovation outcomes.

The results show that both firm-specific resources, such as size, digital capabilities, years of operation and geographical factors, like country location, significantly influence the likelihood of family firms engaging in environmental innovation. Larger, technologically advanced firms are more likely to adopt sustainable practices, and geographic location is crucial due to different regulatory environments and market conditions.

The findings reinforce the RBV by showing the importance of firm-specific resources in driving green innovation and extend Location Theory by emphasizing the role of geographic factors. The study enriches the theoretical understanding of family businesses by showing how noneconomic goals, such as socioemotional wealth and legacy preservation, influence environmental innovation strategies.

Family firms can leverage these findings to enhance their green innovation efforts by investing in technology, fostering sustainability and recognizing the impact of geographic factors. Aligning innovation strategies with both economic and noneconomic goals can help family businesses improve market positioning, comply with regulations and maintain a strong family legacy.

This research contributes a new perspective by integrating the RBV and Location Theory to explore green innovation in family firms, highlighting the interplay between internal resources and external environments. It also shows the effectiveness of machine learning methods in predicting environmental innovation, providing deeper insights than traditional statistical techniques.

As a response to challenges that globalization poses, governments often utilize an expansionary fiscal policy, a mix of increased compensation spending and capital tax cuts. To account for these policy measures that are consistent with neither the compensation nor the efficiency hypothesis, this study examines government fractionalization as the key conditional factor.

We test our hypothesis with a country-year data covering 24 OECD countries from 1980 to 2011. To examine how a single country juggles compensation spending and capital taxation policies jointly, we employ a research strategy that classifies governments into four categories based on their implementation of the two policies and examine the link between imports and fiscal policy choices conditioned on government fractionalization.

This study shows that highly fractionalized governments are more likely to implement an expansionary fiscal policy than marginally fractionalized governments as a policy response to economic globalization and import shock.

Our findings imply that fractionalized governments are likely to face budget deficits and debt crises, as the expansionary fiscal policy persists over time.

By examining government fractionalization as one of the critical factors that constrain the fiscal policy choice, this study enhances our understanding of the relationship between economic globalization and compensation or efficiency policies. The arguments and findings in this study explain why governments utilize the seeming incompatible policy preferences over increased compensation spending and reduced capital tax burdens as a response to globalization, potentially subsuming both hypotheses.

This paper reports on a project looking at consumer perceptions of terroir in the UK, using cheese as a stimulus for the data collection.

Data collection was based on a consumer survey using a discrete choice experiment which included a number of cues to, and stories about, terroir. Analysis of preferences produced three latent classes with varying attitudes towards terroir cues for cheese. There was also an open-ended question giving rise to a qualitative analysis of respondents understanding of the work “terroir”.

When faced with the terroir cues most used some positively to make their choices. A PDO label and stories about the production region and method and business structure all generally offered positive utility.

Terroir is a widely used term in the marketing of (especially) wine, particularly in Europe, offering a form of authenticity and has been very important in policies to sustain the economies of otherwise declining rural areas. It has been adopted by producers in the English-speaking world but is less widely recognised, by consumers. The significance of this study is that it is the first large-scale survey of British consumer perceptions around a key tool for rural businesses – terroir – and one of the first around a non-wine product, and it explores the stories which resonate most effectively with consumers.