Search results

The transaction process of an office building is known to be time consuming and inefficient, in part due to the lack of market transparency. The purpose of this paper is to focus on the development of a blockchain application that can improve the transaction process of office buildings in the Netherlands.

Conducting design science research, the current transaction process of an office building and status quo of blockchain technology in real estate is investigated. Subsequently, multiple parties are interviewed to define major pain points within the process. The interview findings are used to design a blockchain solution which overcomes the aforementioned pain points. After designing, the interviewees are asked again to pragmatically validate the proposed model.

One of the major pain points identified concerning the transaction process of an office building is that it is difficult to define the characteristics of a property, due to lack of data structure and quality. The proposed application improves the way specific assets are understood by structuring physical and contractual information in one place and guarantees the quality of the data by using the blockchain mechanisms.

A blockchain application is proposed, which can improve the transaction process of an office building.

Recent studies indicate that blockchain technology could lead to improvements in efficiency, transparency and therefore trust within the transaction process. Therefore, the proposed application is of value for the future of real estate data management and the transaction process.

Intelligence level of a crowd network is defined as the expected reward of the network when completing the latest tasks (e.g. last N tasks). The purpose of this paper is to improve the intelligence level of a crowd network by optimizing the profession distribution of the crowd network.

Based on the concept of information entropy, this paper introduces the concept of business entropy and puts forward several factors affecting business entropy to analyze the relationship between the intelligence level and the profession distribution of the crowd network. This paper introduced Profession Distribution Deviation and Subject Interaction Pattern as the two factors which affect business entropy. By quantifying and combining the two factors, a Multi-Factor Business Entropy Quantitative (MFBEQ) model is proposed to calculate the business entropy of a crowd network. Finally, the differential evolution model and k-means clustering are applied to crowd intelligence network, and the species distribution of intelligent subjects is found, so as to achieve quantitative analysis of business entropy.

By establishing the MFBEQ model, this paper found that when the profession distribution of a crowd network is deviate less to the expected distribution, the intelligence level of a crowd network will be higher. Moreover, when subjects within the crowd network interact with each other more actively, the intelligence level of a crowd network becomes higher.

This paper aims to build the MFBEQ model according to factors that are related to business entropy and then uses the model to evaluate the intelligence level of a number of crowd networks.

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.

This study aims to identify the propensity for clients (legal and natural persons) to adopt peer-to-peer (P2P) short-term insurance policies as opposed to traditional and/or centralized short-term.

In this paper data was collected through a survey of 102 sampled short-term insurance clients using convenience sampling. The TAM2 questionnaire was adapted to evaluate the intention to adopt a P2P insurance policy.

The findings of this study shed light on the factors influencing the adoption and (dis)continuation of short-term insurance products, both traditional and digital, among South African consumers. The results demonstrate that perceived usefulness, ease of use, trust, risk perception and subjective norm play crucial roles in individuals' intention to use or (dis)continue the use of these insurance products.

The study's findings provide actionable insights for practitioners in the short-term insurance sector, with a focus on marketers and e-commerce professionals. These insights emphasize the need to prioritize user-friendly design and trust-building measures in the development of P2P insurance systems. Additionally, practitioners should consider harnessing the power of social influence and carefully balancing innovative features with familiarity in their marketing efforts. These strategies are poised to enhance the adoption and competitive positioning of P2P insurance solutions amidst the evolving landscape of digital transformation.

This study makes a substantial contribution by employing the technology acceptance model (TAM) in a novel and unconventional manner. It not only explicates the intricate dynamics governing the adoption and discontinuation of short-term insurance products, encompassing both conventional and digital alternatives, within the South African consumer milieu but also extends its purview to infer the reasons behind the limited widespread adoption of the digital counterpart, despite its superior value proposition compared to the traditional offering. The findings elucidate the critical determinants shaping individuals' decisions in this dynamic market segment. This research enhances the global discourse on insurance adoption with a unique South African perspective and furnishes insurers and marketers with empirically grounded insights to optimize their strategies and cultivate substantive connections with their target demographic.

Current models of transaction credit in the e-commerce network face many problems, such as the one-sided measurement, low accuracy and insufficient anti-aggression solutions. This paper aims to address these problems by studying the transaction credit problem in the crowd transaction network.

This study divides the transaction credit into two parts, direct transaction credit and recommended transaction credit, and it proposes a model based on the crowd transaction network. The direct transaction credit comprehensively includes various factors influencing the transaction credit, including transaction evaluation, transaction time, transaction status, transaction amount and transaction times. The recommendation transaction credit introduces two types of recommendation nodes and constructs the recommendation credibility for each type. This paper also proposes a “buyer + circle of friends” method to store and update the transaction credit data.

The simulation results show that this model is superior with high accuracy and anti-aggression.

The direct transaction credit improves the accuracy of the transaction credit data. The recommendation transaction credit strengthens the anti-aggression of the transaction credit data. In addition, the “buyer + circle of friends” method fully uses the computing of the storage ability of the internet, and it also solves the failure problem of using a single node.

With the rapid growth of the Internet of Things (IoT) market and requirement, low power wide area (LPWA) technologies have become popular. In various LPWA technologies, Narrow Band IoT (NB-IoT) and long range (LoRa) are two main leading competitive technologies. Compared with NB-IoT networks, which are mainly built and managed by mobile network operators, LoRa wide area networks (LoRaWAN) are mainly operated by private companies or organizations, which suggests two issues: trust of the private network operators and lack of network coverage. This study aims to propose a conceptual architecture design of a blockchain built-in solution for LoRaWAN network servers to solve these two issues for LoRaWAN IoT solution.

The study proposed modeling, model analysis and architecture design.

The proposed solution uses the blockchain technology to build an open, trusted, decentralized and tamper-proof system, which provides the indisputable mechanism to verify that the data of a transaction has existed at a specific time in the network.

To the best of our knowledge, this is the first work that integrates blockchain technology and LoRaWAN IoT technology.

Blockchain is a distributed ledger, in which the blocks containing transaction details are connected chronologically to form a series of chains, thus raising the possibility of improving the process and innovating business model for the financial institutions. The purpose of this paper is to study the actual cases of Blockchain applied in Korea in 2017, so that a vision of business model innovation of financial institutions can be drawn.

The financial institutions in Korea are in the technology verification stage to introduce Blockchain technology. Since there is an insufficient amount of actual measurement data, case study method was adopted. The authors interviewed ICT officers of major banks in Korea. The purpose of the interview was to understand the relationship between Blockchain and business models of financial institutions, and the effects and challenges that Blockchain has on the business model of financial institutions.

From the perspective of financial institutions, the emergence of Blockchain does not just have technical significance – emergence of highly efficient database system – but has the possibility that if the business model of existing financial intermediaries disappears or get reduced, the financial services relying on them can disappear altogether, or some of them can be replaced, and financial transaction patterns of consumers can be changed. As a case studies researched for this paper, it was discovered that the distributed characteristic of Blockchain cannot be applied when actually developing financial services.

This study aims to explore the need for highly technological complexes for control and monitoring, as well as, new concepts and methodologies for maritime resource exploration and exploitation, which are in great demand nowadays.

This paper provides an analysis of demand, means of creation and development of the methodology and infrastructure for global monitoring, pollution control and supervision of smart systems for activities in exploration, future resource exploitation in deep-water and coastal areas based on Smarthub architecture, Unmanned Aircraft System (UAS), Continuous Acquisition and Life-Cycle Support (CALS) and Blockchain technologies.

Observational, experimental, simulation, derivational, hybrid descriptive and analytical models, as well as, surrogate models were created, analyzed and implemented for assigned tasks realization. Concept of distributed system for marine environmental monitoring, control and supervising as pilot technology in the context of Technology Readiness Levels (TRL) 3–5 was designed and evaluated.

The activities described in this article should be realized in the design and development of a complex, reliable, robust and sustainable monitoring and inspection system for the control and evaluation of the impact and risk assessment of the exploration and future exploitation of maritime resources.

This paper aims to investigate the influence of trust on adopting and implementing blockchain technology in higher education institutions (HEIs) in Brazil.

This study uses an exploratory qualitative approach to understand the construct of trust in the context of the educational sector. Data were collected through semistructured questionnaires and online interviews.

The research identified that, for most potential blockchain users, trust positively influences the HEIs, because benefits such as secure data sharing and transaction transparency could optimize the daily routine and avoid fraud in academic documents, providing a cooperative and reliable working environment. In addition, the results suggest that trust is needed to overcome challenges related to issues such as costs and privacy.

This study contributes to the advances in the emerging literature on blockchain in the educational sector as a system with the potential to generate trust, as well as the literature on the technology acceptance models.

For HEI managers and practitioners, this study highlights the need for a greater understanding of the influence of trust in the relationships between HEIs and other stakeholders.

This work shows that adopting blockchain technologies would allow users to build social relationships of trust in a cooperative work environment and develop trusted behavior by sharing data securely and transparently.

To the best of the authors’ knowledge, this is one of the first studies on the adoption and implementation of blockchain in the education sector in Brazil.

This qualitative study aims to explore the activities that guests perform while staying in Airbnbs, emotions associated with these experiences and the components of memorable Airbnb experiences.

An empirical study of a qualitative nature was conducted using a self-administered open-ended questionnaire among tourists who had stayed in an Airbnb in the past three years. Data were collected using two different sources for triangulation purposes, referred to as Studies 1 and 2.

Many respondents reported conducting similar activities while at home and while staying in an Airbnb, supporting Burch’s (1969) spill-over theory. Travellers mostly recalled mundane activities, such as cooking. The results suggest that the spill-over effect is more prevalent in the Airbnb context than in other accommodation types, as one often travels from one’s own home to another’s home. Respondents associated their Airbnb experience with the positive emotion of joy. Respondents mentioned numerous reasons for having felt joy during their Airbnb experiences, such as sharing the trip with travel companions and spending time with friends.

Airbnb should clearly define host’s tasks and responsibilities, hosts should treat guests in a friendly manner, which includes resolving any problems they face in relation to the rental property.

This paper proposes a new conceptual framework for a memorable Airbnb experience, which comprises several components: socialising and bonding with friends and family members, location, the host’s hospitality, a homely feeling, home amenities and negative experiences (the poor condition of the room and a dishonest host).