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This research aims to determine the factors that affected Bitcoin price return in the period before and during the COVID-19 pandemic.

The independent variables used in this study are hashrate, transaction volume, social media and some macroeconomics variables. The data are processed using the vector error correction model (VECM) to determine the short-term and long-term relationships between variables.

The research shows that (1) Twitter and Gold significantly affected Bitcoin in the short term before the COVID-19 pandemic; (2) hashrate, transaction volume, Twitter and the financial stress index had a significant effect on Bitcoin in the long term before the COVID-19 pandemic; (3) the volatility index had a significant effect on Bitcoin in the short term during the COVID-19 pandemic; and (4) hashrate, transaction volume, Twitter and CHF/USD had a significant effect on Bitcoin in the long term during the COVID-19 pandemic.

This research provides explanation about factors affecting Bitcoin so investors and regulators can pay more attention and prepare for the potential risks as well as to get a good understanding of market conditions for greater crypto adoption in the future.

The novelty in this study is the various factors driving the Bitcoin price were analyzed before and during the COVID-19 pandemic including the social media, as sentiment, interestingly, is being a predictive power for Bitcoin price return.

Using the Analytical Hierarchy Process, this study aims to identify organizational and market factors that prevent hoteliers from adopting greener management systems. This study first constructs a list of critical factors based on expert judgments reported in the literature and the responses from a select group of experienced managers. Then, the list is further refined by six hotel managers who consolidate the factors, which results in four categories explained by 20 items. Subsequently, this study draws from surveys on an expert panel consisting of 20 study subjects who are familiar with hotel operations. The survey results show that hoteliers’ abilities to create a greener image are the most important factor influencing the managers’ decisions to adopt environmentally friendly management schemes. Nevertheless, their motivation of adopting a green strategy seems to be associated with a marketing strategy, instead of generic environmental stewardship.

The purpose of this paper is to understand how perceptions of fair treatment impact voluntary behaviors of information technology (IT) professionals beneficial to the achievement of organizational goals. Specifically, social exchange and psychological contract theory provide a framework to consider whether equitable treatment of employees and preservation of implied contracts are indicators of beneficial, extra‐role behaviors.

The study employs a questionnaire targeting IT professionals to test a model derived from theory and prior IT personnel literature.

IT employees reciprocate demonstrations of equity and maintenance of implied contracts by added beneficial behaviors not explicit to their job requirements. This relationship is partially mediated by their trust held in the organization.

This study considered two related but distinct social exchange concepts in the same model of IT personnel behavior that had previously been considered independently indicating the need to consider both in future models. Generalizations of the observed result are limited by the use of cross‐sectional data from a single culture.

Managers of IT personnel must design and implement procedures that guarantee equitable distribution of resources and rewards. Management honoring contacts that are merely implicit and derived internally by the IT employee is crucial in promoting beneficial behaviors that fall outside explicit job requirements.

The paper highlights how IT employees reciprocate in the technology work environment. In exchange for an organization honoring contracts that are merely perceived and providing an equitable structure, IT professionals are willing to go beyond required job descriptions to achieve goals.

The World Health Organization Suicide trends in at-risk territories study is a multi-site regional research program operating first in French Polynesia and countries of the Western Pacific, then extended to the world. The aims of the study were to establish a monitoring system for suicidal behaviors and to conduct a randomised control trial intervention for non-fatal suicidal behaviors. The latter part is the purpose of the present article. Over the period 2008-2010, 515 patients were admitted at the Emergency Department of the Centre Hospitalier de Polynésie Française for suicidal behavior. Those then hospitalized in the Psychiatry Emergency Unit were asked to be involved in the study and randomly allocated to either Treatment As Usual (TAU) or TAU plus Brief Intervention and Contact (BIC), which provides a psycho-education session and a follow-up of 9 phone contacts over an 18-months period. One hundred persons were assigned to TAU, while 100 participants were allocated to the BIC group. At the end of the follow-up there were no significant differences between the two groups in terms of number of presentations to the hospital for repeated suicidal behaviors. Although the study could not demonstrate the superiority of a treatment over the other, nevertheless – given its importance – the investigation captured public attention and was able to contribute to the awareness of the need of suicide prevention in French Polynesia. The BIC model of intervention seemed to particularly suit the geographical and health care context of the country.

Various demands and requirements of foreign home-buyers from different background are yet unclear to most of the residential developers. The aim of this study is to blueprint a fuzzy mapping of psychological phenomena reflected in consumer behavior, and to develop a Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) decision making model to assist residential developers in dealing with potential foreign customers. Through a questionnaire survey in the form of pair wise comparison matrix among 126 expatriates, this study introduces a new approach to assist residential developers dealing with expatriates' preference on house purchase in Malaysia in a simple and efficient way. With this fuzzy mapping, residential developers could utilize psychological phenomena to manipulate expatriates' preference on housing purchase rather than to merely comply passively.

This study aims to investigate the impact that knowledge management (KM) capabilities have on school effectiveness in career and technical education (CTE) in Taiwan.

The study adopted a survey research. A total of 439 valid samples were obtained and subsequently verified with structural equation modeling.

The results indicated that KM capabilities consist of two main dimensions, namely, the KM enabler capabilities and the KM process capabilities. The former includes structures, cultures and information technology support, whereas the latter includes acquisitions, storage, sharing and applications. In terms of the relationships among the dimensions of the model structure, the KM enabler capabilities managed to effectively predict the KM process capabilities, and the KM process capabilities managed to effectively predict the perceived school effectiveness.

Based on the results, improvement of the KM enabler capabilities and process capabilities of higher education institutions of CTE is recommended so that their school effectiveness may be improved. Because the participants were not randomly selected, the generalizability of the results should be further examined.

This study encourages practitioners to focus their KM practices on KM enabler capabilities and the KM process capabilities.

The current study provided an insight into and further understanding of the model regarding the relationships among the KM enabler capabilities, the KM process capabilities and the school effectiveness.

The purpose of this paper is to construct and evaluate value and growth portfolios in Portugal, Italy, Ireland, Greece and Spain, which are commonly known as the EU PIIGS, from 2003 to 2015. Previous research evidence suggests that stocks trading at a lower price relative to their fundamentals (value stocks) tend to outperform stocks that trade at higher prices (growth stocks) in the long run. Although this market anomaly has been studied immensely worldwide, especially for the US stock market, there is no clear evidence whether such an assertion is applicable in less-renowned countries.

The paper utilises Fama and Macbeth (1973) regressions and its model extensions.

This paper finds a significant value premium in these countries, which is compatible with previous studies conducted worldwide.

To the best of the authors’ knowledge, this is the first attempt to examine this asset pricing anomaly in the PIIGS.

The purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.

The authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.

The authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.

This study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.

New regulatory initiatives, principally MiFID and RegNMS, challenge wholesale financial firms to prove that they can provide best execution for their clients. This article aims to outline the background to the problem and suggest that current research into SVM/DAPR applications may provide a practical approach.

The article presents a desk review of current issues in “best execution” based on work with European brokers and others, followed by initial, promising trial of SVM/DAPR.

The article finds that brokers need automated tools, e.g. “sifting engines” that help them to focus compliance efforts on anomalous trades.

Although brokers appear to need assistance in identifying anomalous trades, whether they place significant effort in compliance depends on regulatory enforcement.

MiFID and RegNMS will require changes in current practice. SVM/DAPR approaches appear to be worth further investigation.

Forthcoming requirements in MiFID and RegNMS mean that buy‐side and sell‐side firms need to find ways of showing regulators that they are sifting through their trading volumes in a justifiable, methodical manner looking for anomalous trades and investigating them, in order to prove “best execution”. The objective was to see if a SVM/DAPR approach could help identify equity trade anomalies for compliance investigation.

A major stock exchange, a computer systems supplier, four brokers and a statistical firm undertook a cooperative research project to determine whether automated statistical processing of trade and order information could provide a tighter focus on the most likely trades for best execution compliance investigation.

The support vector machine approach worked on UK equities and has significant potential for other markets such as foreign exchange, fixed income and commodities.

The research has implications for risk professionals as a generic approach to trading anomaly detection. The prototype compliance workstation can be trialed.

Automated anomaly detection could transform the role of compliance and risk in financial institutions.