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The study aims to identify the perceived authenticity of cheeses by consumers of different sociological generations in Mexico.

An online questionnaire was applied to 1,204 consumers. A Free Word Association (FWA) tool was used to determine the perceived authenticity of cheeses creating categories and dimensions. The sample was segmented into sociological generations. A chi-square test and a correspondence analysis were used to identify differences in the perception between generations. The information was complemented with word clouds of the cheeses mentioned and consumer testimonials about cheese consumption.

A total of 29 categories and ten dimensions revealed consumers' perception of cheese authenticity, most important of which were hedonic, rurality and new consumption. Authenticity is a mix of the pleasure of consuming the product, the link to rural life and new consumer values. Perceived authenticity is different in each sociological generation according to the dimensions of raw material, identity, market, new consumption and distrust, since it is related to the experiences of each generation. The results made it possible to contextualise another vision of the reality of the cheeses in the search for a quality seal.

The information contributes to the typification and promotion of cheeses in the process of patrimonialisation, by creating differentiated marketing tools that allow their valorisation.

This work contributes to the knowledge of the perceived authenticity of cheeses in the sociological generations, due to their differentiation by age, sociocultural, ethical, political and consumer aspects. It enables the knowledge of the consumer's perspective on these products.

This paper contributes to a dialogue about the psychoanalytic concept of free association and its application in the context of qualitative research interviewing. In doing so, it also adds to wider discussion regarding the relationship between clinical psychoanalysis, psychoanalytic psychotherapy and qualitative research.

Critical consideration of different perspectives on the application of free association in the qualitative research interview, extending earlier work addressing this issue. Differences and similarities in the way the concept of free association is articulated are examined regarding its framing in psychoanalysis and psychoanalytically oriented psychotherapy.

Whether researchers see themselves as borrowing, applying or drawing inspiration from free association, there is scope for muddling distinct ways of viewing it as it is conceived in psychoanalysis.

Considerations are outlined for researchers interested in psychoanalytically informed methods to be mindful of.

The purpose of this paper is to test the effect that anthropomorphic framing (i.e. robot vs automatic machine) has on consumers’ responses in case of service failure. Specifically, the authors hypothesize that consumers hold an unconscious association between the word “robot” and agency and that the higher agency attributed to self-service machines framed as robots (vs automatic machines) leads, in turn, to a more positive service evaluation in case of service failure.

The authors have conducted four experimental studies to test the framework presented in this paper. In Studies 1a and 1b, the authors used an Implicit Association Test to test for the unconscious association held by consumers about robots as being intelligent machines (i.e. agency). In Studies 2 and 3, the authors tested the effect that framing technology as robots (vs automatic machines) has on consumers’ responses to service failure using two online experiments across different consumption contexts (hotel, restaurant) and using different dependent variables (service evaluation, satisfaction and word-of-mouth).

The authors show that consumers evaluate more positively a service failure involving a self-service technology framed as a robot rather than one framed as an automatic machine. They provide evidence that this effect is driven by higher perceptions of agency and that the association between technology and agency held by consumers is an unconscious one.

This paper investigates a novel driver of consumers’ perception of agency of technology, namely, how the technology is framed. Moreover, this study sheds light on consumers’ responses to technology’s service failure.

The educational community – particularly higher education – should contribute to the new generation’s understanding of what sustainability entails. To do this, teachers must be aware of the need for education for sustainability. However, little is known about how university teachers understand or represent sustainability. This study aims to bridge the gap identified in the literature concerning university teachers’ representation of sustainability.

A total of 403 teachers from the University of the Basque Country participated in the study through a free association exercise based on the grid elaboration method.

In general terms, teachers are aware of the three dimensions that constitute sustainability, but differences were found in the way sustainability was represented depending on several factors such as the teaching field, previous knowledge of the 2030 Agenda and gender. Despite awareness of the need to incorporate sustainability, there was also reticence toward the way in which sustainability is being addressed in higher education. Those results were discussed considering the previous literature on sustainability.

The results allow the authors to conclude that knowledge of the 2030 Agenda leads teachers to have a more complete representation and greater recognition of sustainability. Thus, it would be necessary for universities to offer more training to teachers to promote a holistic understanding of sustainability and facilitate its incorporation into teaching.

The use of this method made it possible to collect, in a less biased and much more direct way, the teachers’ voices, to know the type of representation (holistic) or partial (only one of its dimensions: environmental, economic or social) that they have of sustainability, and to check whether their representation was linked to specific factors.

This study aims to investigate the content of hotel brands’ mission statements (MSs) and their relationship with selected attributes of hotel brands.

Content analysis of hotel brands’ MSs was used to detect the MSs’ key words, which were further processed by methods of social network analysis, complemented by clustering techniques and correspondence analysis on the generalized aggregated lexical tables, a special type of correspondence analysis.

Hotel brands operating in luxurious markets more often emphasize experiences than those in midscale markets. Furthermore, hotel brands with longer traditions and those with a large number of controlled rooms communicate words in their MSs that represent a rather traditional approach to hospitality. Younger hotel brands with fewer controlled rooms chose words that indicate a more commercially oriented approach. Finally, cluster analysis revealed four dimensions of hotel brands’ MSs, instead of the nine most typically used in mission statement component models.

Understanding the frequencies and networks of keywords, and their relationship with hotel brand attributes, will help create more focussed MSs. This will strengthen hotel brands, raise their revenues and subsequently increase company performance.

The analysis provides valuable insight into MSs in the specific tourism context of hotel brands. The authors have achieved this with the use of a wide range of advanced network analytic methods. These insights can guide hotel brands to better position themselves in the competitive tourism accommodation market.

This paper aims to illustrate the extensive benefits of qualitative data analysis as a rarely undertaken process in post-occupancy evaluation surveys. As a result, there is limited evidence of what occupants say about their buildings, especially for operational parameters, as opposed to how they rate them. While quantitative analyses provide useful information on how workers feel about workplace operational factors, qualitative analyses provide richer information on what aspects of the workplace workers identify as influential to their comfort, well-being and productivity.

The authors analysed 6,938 comments from office buildings worldwide on workers’ perception of workplace operational factors: design, storage, needs, space at desks and storage in their work environments. These factors were analysed based on the buildings’ design intent and use, and the associated comments were coded into positive, negative and balanced comments. The authors used a combination of coding, descriptive analysis, content analysis and word cloud to dissect the comments.

The findings showed that whereas workers rated these operational factors favourably, there were significantly more negative comments about each factor. Also, the Chi-square test showed a significant association (p < 0.01) between the satisfaction scale and the type of comments received for all the operational factors. This means that when a factor is rated high in the satisfaction score (5–7), there were fewer negative and more positive comments and vice versa. The word cloud analysis highlighted vital aspects of the office environment the workers mostly commented on, such as open plan design, natural lighting, space and windows, toilets, facilities, kitchens, meeting room booking systems, storage and furniture.

This study highlights the importance of dissecting building occupants’ comments as integral to building performance monitoring and measurement. These emphasise the richness and value of respondents’ comments and the importance of critically analysing them. A limitation is that only 6,938 comments were viable for analysis because most comments were either incomplete with no meaning or were not provided. This underlines the importance of encouraging respondents to comment and express their feelings in questionnaire surveys. Also, the building use studies questionnaire data set presents extensive opportunities for further analyses of interrelationships between demographics, building characteristics and environmental and operational factors.

The findings from this study can be applied to future projects and facility management to maintain and improve office buildings throughout their life cycle. Also, these findings are essential in predicting the requirements of future workplaces for robust workplace designs and management.

The authors identified specific comments on the performance of workplaces across the globe, showing similarities and differences between sustainable, conventional, commercial and institutional buildings. Specifically, the analysis showed that office workers’ comments do not always corroborate the ratings they give their buildings. There was a significantly higher percentage of negative comments than positive comments despite the high satisfaction scores of the operational factors.

In times of crisis, such as the Covid-19 global pandemic, journalists who write about biomedical information must have the strategic aim to be clearly and easily understood by everyone. In this study, we assume that journalistic discourse could benefit from language redundancy to improve clarity and simplicity aimed at science popularization. The concept of language redundancy is theoretically discussed with the support of discourse analysis and information theory. The methodology adopted is a corpus-based qualitative approach. Two corpora samples with Brazilian Portuguese (BP) texts on Covid-19 were collected. One with texts from a monthly science digital magazine called Pesquisa FAPESP aimed at students and researchers for scientific information dissemination and the other with popular language texts from a news Portal G1 (Rede Globo) aimed at unspecified and/or non-specialized readers. The materials were filtered with two descriptors: “vaccine” and “test.” Preliminary analysis of examples from these materials revealed two categories of redundancy: paraphrastic and polysemic. Paraphrastic redundancy is based on concomitant language reformulation of words, sentences, text excerpts, or even larger units. Polysemic redundancy does not easily show material evidence, but is based on cognitively predictable semantic association in socio-cultural domains. Both kinds of redundancy contribute, each in their own way, to improving text readability for science popularization in Brazil.

The purpose of this study is threefold: firstly, to compare Pakistani and French consumers’ perceptions of well-being; secondly, to investigate how consumers in both countries relate to food; and thirdly, to assess whether they associate food with well-being.

Thirty participants (15 French and 15 Pakistani) between the ages of 24 and 35 were interviewed, using convenience and snow bowling sampling. Data triangulation was performed by combining three qualitative techniques, word association, photo-elicitation-based interviewing and open-ended questions to explore consumer perceptions of well-being, food and food well-being.

The study’s findings suggest that well-being is a broad concept in which food is an ingredient. Food and well-being share common elements, and food well-being can be defined as an individual’s psychological, physical, social and societal relationship with food ascribed by affordability and food literacy.

Pleasure, sharing and respect emerged as dimensions of food well-being that can be applied to transfigure consumer behaviour and reduce over-consumption, food waste and hunger. The dimensions of well-being and food were explored for both countries to understand their cultural nuances and determine the influence of food on well-being. This comparative analysis will help researchers understand consumers’ preferences for food in various aspects from two regions. This study can potentially contribute to scale development in food and well-being, which can help researchers measure the effects of food and well-being in different sectors of the economy, particularly in health care. The most aspiring aspect of the current research is the insights unveiled during interactions with research participants, which will help develop consumer baseline feelings.

In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.