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In the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality involve labor-intensive processes and rely on the expertise of connoisseurs proficient in identifying taste profiles and key quality factors. In this research, we introduce an innovative and efficient approach centered on the analysis of volatile organic compounds (VOCs) signals using an electronic nose, thereby empowering nonexperts to accurately assess wine quality.

To devise an optimal algorithm for this purpose, we conducted four computational experiments, culminating in the development of a specialized deep learning network. This network seamlessly integrates 1D-convolutional and long-short-term memory layers, tailor-made for the intricate task at hand. Rigorous validation ensued, employing a leave-one-out cross-validation methodology to scrutinize the efficacy of our design.

The outcomes of these e-demonstrates were subjected to meticulous evaluation and analysis, which unequivocally demonstrate that our proposed architecture consistently attains promising recognition accuracies, ranging impressively from 87.8% to an astonishing 99.41%. All this is achieved within a remarkably brief timeframe of a mere 4 seconds. These compelling findings have far-reaching implications, promising to revolutionize the assessment and tracking of wine quality, ultimately affording substantial benefits to the wine industry and all its stakeholders, with a particular focus on the critical aspect of VOCs signal analysis.

This research has not been published anywhere else.

The purpose of this paper is to present a conceptual frame for scholars who draws on the conflicting logics of the postpandemic university.

This feature paper is based on a systematic review of research and studies conducted in the field of higher education. It illustrates broader trends with respect to how the various elements of contemporary and conflicting challenges present themselves within higher education institutions (HEIs).

A combination of literature review and fieldwork across a broad range of scientific fields presents a potentially powerful means of reducing the gap between research and practice. For this reason, this paper sets out to provide conceptual perspectives as to contemporary and conflicting challenges in higher education.

This paper presents many descriptive results from HEIs in the western world which do not allow for making global inferences toward the entire higher education sector.

The results have a number of implications for the postpandemic university. Among them are that HEIs should not only be more open toward contemporary changes but also embrace previously excluded student populations with their purpose-driven and sustainable orientation toward life.

This paper presents a conceptual contribution to contemporary challenges in higher education as a way of refraining from one-size-fits-all approaches. It demonstrates how institutional positioning and profiling depend on conflicting logics. Consequently, each institution of higher learning needs to address these challenges in line with their strategic, economic and political settings.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

This study aims to explore auto mechanics awareness of repairs and maintenance related to the car’s cybersecurity and provide insights into challenges based on current practice.

This study is based on an empirical study consisting of semistructured interviews with representatives from both branded and independent auto workshops. The data was analyzed using thematic analysis. A version of the capability maturity model was introduced to the respondents as a self-evaluation of their cybersecurity awareness.

Cybersecurity was not found to be part of the current auto workshop work culture, and that there is a gap between independent workshops and branded workshops. Specifically, in how they function, approach problems and the tools and support available to them to resolve (particularly regarding previously unknown) issues.

Only auto workshop managers in Sweden were interviewed for this study. This role was picked because it is the most likely to have come in contact with cybersecurity-related issues. They may also have discussed the topic with mechanics, manufacturers or other auto workshops – thus providing a broader view of potential issues or challenges.

The challenges identified in this study offers actionable advice to car manufacturers, branded workshops and independent workshops. The goal is to further cooperation, improve knowledge sharing and avoid unnecessary safety or security issues.

As cars become smarter, they also become potential targets for cyberattacks, which in turn poses potential threats to human safety. However, research on auto workshops, which has previously ensured that cars are road safe, has received little research attention with regards to the role cybersecurity can play in repairs and maintenance. Insights from auto workshops can therefore shed light upon the unique challenges and issues tied to the cybersecurity of cars, and how they are kept up-to-date and road safe in the digital era.