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This article describes financial professionals' perceptions of their clients' financial behaviors and the explanatory factors underlying these behaviors.

In this qualitative research, the authors seek to understand financial professionals' experiences in relation to how their clients manage their own finances. The authors conduct and analyze 26 semi-structured interviews with financial professionals from several industries within the financial sector in Canada.

The professionals in this study noted that despite their clients' financial knowledge, several other factors can explain these individuals' financial behaviors. They include psychological factors (such as financial bias, the need for instant gratification, and the lack of awareness regarding the long-term effects of certain types of financial behaviors), financial habits (such as lifestyle, financial planning and lack of discipline) and the financial system's flexibility with respect to debt financing and repayment. These perceptions are categorized according to whether they are related to debt financing or repayment, savings or investments.

By using a qualitative methodology that relies on the perceptions of financial professionals, this study aims to better understand the financial behaviors of individuals and households, and these behaviors' underlying factors. This study's findings could be useful to various stakeholders interested, in one way or another, in financial literacy, such as organizations aiming to strengthen and promote financial literacy, educators, researchers, regulatory bodies of financial institutions and financial advisers.

Utility strikes have spawned companies specializing in providing a priori analyses of the underground. Geophysical techniques such as Ground Penetrating Radar (GPR) are harnessed for this purpose. However, analyzing GPR data is labour-intensive and repetitive. It may therefore be worthwhile to amplify this process by means of Machine Learning (ML). In this work, harnessing the ADR design science methodology, an Intelligence Amplification (IA) system is designed that uses ML for decision-making with respect to utility material type. It is driven by three novel classes of Convolutional Neural Networks (CNNs) trained for this purpose, which yield accuracies of 81.5% with outliers of 86%. The tool is grounded in the available literature on IA, ML and GPR and is embedded into a generic analysis process. Early validation activities confirm its business value.

Although networked hospitality businesses as Airbnb are a recent phenomenon, a rapid growth has made them a serious competitor for the hospitality industry with important consequences for tourism and for tourist destinations. The purpose of this paper is to analyse the nature of the phenomenon, its potential further development in the next five years and the impact this developments will have on tourism, on hotels and on city destinations.

A literature study, combined with scenario workshops and a Delphi panel, were used to map current trends and uncertainties. With this input, future scenarios were elaborated using the Global Business Network (“scenario cross”) method.

Network platforms as Airbnb are often classified under something called the “Sharing Economy”, a denomination that obscures their true nature. Airbnb is a challenging innovation to which traditional hospitality will have to respond. Its impact has at the same time led to a call for regulatory policies. The definition of these policies and the evolution of tourism are variables that determine future scenarios. Attempts to ban the phenomenon mean a disincentive to innovation and protect oligopolistic markets; more receptive policies may have the desired results if tourism grows moderately but in booming destinations they may lead to a harmful commercialization.

Until now, Airbnb has been described in conceptual studies about the so-called “Sharing economy”, or more recently in empirical studies about isolated effects of holiday rentals. This paper contextualizes the evolution of networked hospitality and seeks to synthesize the sum of its impacts, thus enabling businesses and local governments to define positions and strategies.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

The characteristics of the Internet of Things (IoT) are such that traditional models of trust developed within interpersonal, organizational, virtual and information systems contexts may be inappropriate for use within an IoT context. The purpose of this paper is to offer empirically generated understandings of trust within potential IoT applications.

In an attempt to capture and communicate the complex and all-pervading but frequently inconspicuous nature of ubiquitous technologies within potential IoT techno-systems, propositions developed are investigated using a novel mixed methods research design combining a videographic projective technique with a quantitative survey, sampling 1,200 respondents.

Research findings suggest the dimensionality of trust may vary according to the IoT techno-service context being assessed.

The contribution of this paper is twofold. First, and from a theoretical perspective, it offers a conceptual foundation for trust dimensions within potential IoT applications based upon empirical evaluation. Second, and from a pragmatic perspective, the paper offers insights into how findings may guide practitioners in developing appropriate trust management systems dependent upon the characteristics of particular techno-service contexts.

This research evaluates (1) work situations prompting participants to recall memories of a wilderness-based leadership training program, (2) the content of such memories, and (3) the leadership attitudes and behaviors inspired by those memories.

A qualitative content analysis of semi-structured interviews was performed with 36 leaders who had participated in a wilderness leadership transformation program in the past (on average six years before).

The findings suggest that, at moments with emotional pressure and psychological stress, episodic memories of wilderness experiences have a positive influence on actual leadership style. Memories involved moments of solitude, a deep connection with nature, and peer-to-peer counseling. The interviewees regularly relived their emotion-laden wilderness experiences, acquiring direction and guidance. Simultaneously, episodic memories of nature immersion promoted an enduring transformation of their leadership styles.

The findings cannot be blindly generalized as referring to all leaders. The leaders in this study are a subset of leaders who are inclined towards personal growth and leadership development. It is challenging to motivate leaders unkeen on changing to achieve better leadership.

This study indicates that the inclusion of emotional concepts to address the root causes of learning among leaders might be the most promising way to innovate leadership development.

The present study makes a novel contribution to relevant literature by examining leadership transformation through episodic remembrance of leaders' experiences in nature.