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Contrary to the traditional technology project perspective, real estate investors see building-specific renewable energy (on-site energy) investments as part of the property and as something affecting the property’s ability to produce a (net) cash flow. This paper aims to show the value-influencing mechanism of on-site energy production from a professional property investors’ perspective.

The value-influencing mechanism is presented with a case study of a prime logistics property located in the Helsinki metropolitan area, Finland. The case study results are compared with the results of a survey answered by over 70 property valuation professionals in the Finnish real estate market.

Current valuation practice supports the presented value-creation mechanism based on the capitalisation of the savings generated by a building’s own energy production. Valuation professionals see benefits beyond decreased operating expenses such as enhanced image and better saleability. However, valuers acted more conservatively than expected when transferring these additional benefits to the cash flows of the case property.

Because the savings in operating expenses can be capitalised into the property value, property investors should consider on-site energy production when the return of on-site energy exceeds the return of the property. This enhances the profitability of on-site energy, especially in urban areas with low initial yields.

This is the first research paper to open the value-influencing mechanism of on-site energy production from a professional property investors’ perspective in commercial properties and to confirm it from a market study.

In the literature there are numerous tests that compare the accuracy of automated valuation models (AVMs). These models first train themselves with price data and property characteristics, then they are tested by measuring their ability to predict prices. Most of them compare the effectiveness of traditional econometric models against the use of machine learning algorithms. Although the latter seem to offer better performance, there is not yet a complete survey of the literature to confirm the hypothesis.

All tests comparing regression analysis and AVMs machine learning on the same data set have been identified. The scores obtained in terms of accuracy were then compared with each other.

Machine learning models are more accurate than traditional regression analysis in their ability to predict value. Nevertheless, many authors point out as their limit their black box nature and their poor inferential abilities.

AVMs machine learning offers a huge advantage for all real estate operators who know and can use them. Their use in public policy or litigation can be critical.

According to the author, this is the first systematic review that collects all the articles produced on the subject done comparing the results obtained.

This article describes the interviews the authors conducted in late 2021 with 19 researchers at the Department of Classical Philology and Italian Studies at the University of Bologna. The main purpose was to shed light on the definition of the word “data” in the humanities domain, as far as FAIR data management practices are concerned, and on what researchers think of the term.

The authors invited one researcher for each of the official disciplinary areas represented within the department and all 19 accepted to participate in the study. Participants were then divided into five main research areas: philology and literary criticism, language and linguistics, history of art, computer science and archival studies. The interviews were transcribed and analysed using a grounded theory approach.

A list of 13 research data types has been compiled thanks to the information collected from participants. The term “data” does not emerge as especially problematic, although a good deal of confusion remains. Looking at current research management practices, methodologies and teamwork appear more central than previously reported.

Our findings confirm that “data” within the FAIR framework should include all types of inputs and outputs humanities research work with, including publications. Also, the participants of this study appear ready for a discussion around making their research data FAIR: they do not find the terminology particularly problematic, while they rely on precise and recognised methodologies, as well as on sharing and collaboration with colleagues.

The purpose of this paper is to investigate KM practices that may be in place in the higher education institutions (HEIs) and whether the KM practices are made known to the employees for improving the teaching and learning environment provided at the Malaysian higher education institutions.

Data were collected using a personal administrated method made available to private higher education institutions academic members in five states with 30 or more employees. A total of 1,100 survey questionnaires were handed out, out of which 273 were collected and were usable (24.8 per cent response rate). The sample was checked for response and non-response bias. Results were tested using SPSS application and questionnaire tools.

It was essential to establish the knowledge management (KM) capacity in key areas such as the ability to recognise experts within the institution, leadership’s innovation, knowledge sharing and knowledge acquiring work culture, and technology usage. KM tools and techniques would help the institutions to meet their competitive goals; therefore, it is vital for HEIs to create KM awareness among the employees.

Similar to most studies, it is anticipated that the participants’ awareness of KM practices at their HEIs is very high. The samples were collected to evaluate the general view of KM awareness and how participants perceived KM practices. The total samples received for this study were expected; however, they were sufficient to study the impact.

This paper provides support for the importance of KM practices and employees awareness at HEIs to enhance innovation and performance teaching and learning environment.

This paper is one of the first papers to find empirical support for the role of KM practices at HEIs. Further, the positioning of KM practices as a competitive tool can be considered as an influential factor to competitive advantage.

In a modern world increasingly perceived as uncertain, the mere purchase of a household cleaning product, or a seemingly harmless bottle of milk, conveys interrogations about potential hazards, from environmental to health impacts. The main purpose of this paper is to suggest that risk could be considered as one of the major dimensions of choice for a wide range of concerns and markets, alongside aspiration/satisfaction, and tackled efficiently by mobilizing the recent findings of cognitive sciences, neurosciences and evolutionary psychology. It is felt that consumer research could benefit more widely from psychological and evolutionary-grounded risk theories.

In this study, some 50 years of marketing management literature, as well as risk-specialized literature, was examined in an attempt to get a grasp of how risk is handled by consumer sciences and of whether they make some use of the most recent academic works on mental biases, non-mainstream decision-making processes or evolutionary roots of behavior. We then tested and formulated several hypotheses regarding risk profiles and preferences in the sector of insurance, by participating in an Axa Research Fund–Paris School of Economics research project.

It is suggested that consumer profiles could be enriched by risk-taking attitudes, that risk could be part of the “reason why” of brand positioning, and that brand, as well as public policy communication, could benefit from a targeted use of risk perception biases.

This paper proposes to apply evolutionary-based psychological concepts to build perceptual maps describing people and consumers on both aspiration and risk attitude axis, and to design communication tools according to psychological research on message framing and biases. Such an approach mobilizes not only the recent findings of cognitive sciences and neurosciences but also the understanding of the roots of risk attitudes and perception. Those maps and framing could probably be applied to many sectors, markets and public issues, from commodities to personal products and services (food, luxury goods, electronics, financial products, tourism, design or insurance).

Mobile Facebook (m-Facebook) creates many business opportunities for brands and firms while increasingly drawing interest in scientific literature. However, research is scarce on the immersive experiences prompted by m-Facebook, and how these experiences facilitate users’ engagement, their positive attitude towards Facebook and their continued use of it. The paper aims to discuss these issues.

This paper theoretically and empirically analyses m-Facebook users’ immersive experiences, along with their affective and behavioural effects.

The results reveal the important role of imagery, presence and flow in the context of m-Facebook; the interplay between these three immersive phenomena; and the influence the user’s optimum stimulation level has on them.

The investigation offers a foundation for understanding users’ immersive experiences on m-Facebook, and informs practitioners who aim to enhance users’ engagement with, attitude towards, and continued use of m-Facebook content.