An Intelligent Mechanism to Automatically Discover Emerging Technology Trends: Exploring Regulatory Technology

Technology trend analysis uses data relevant to historical performance and extrapolates it to estimate and assess the future potential of technology. Such analysis is used to analyze emerging technologies or predict the growing markets that influence the resulting social or economic development to assist in effective decision-making. Traditional trend analysis methods are time-consuming and require considerable labor. Moreover, the implemented processes may largely rely on the specific knowledge of the domain experts. With the advancement in the areas of science and technology, emerging cross-domain trends have received growing attention for its considerable influence on society and the economy. Consequently, emerging cross-domain predictions that combine or complement various technologies or integrate with diverse disciplines may be more critical than other tools and applications in the same domain. This study uses a design science research methodology, a text mining technique, and social network analysis (SNA) to analyze the development trends concerning the presentation of the product or service information on a company's website. This study applies regulatory technology (RegTech) as a case to analyze and justify the emerging cross-disciplinary trend. Furthermore, an experimental study is conducted using the Google search engine to verify and validate the proposed research mechanism at the end of this study. The study results reveal that, compared with Google Trends and Google Correlate, the research mechanism proposed in this study is more illustrative, feasible, and promising because it reduces noise and avoids the additional time and effort required to perform a further in-depth exploration to obtain the information.

Metaheuristic Algorithms Based on Compromise Programming for Multi-Objective Urban Shipment Problem

The Vehicle Routing Problem (VRP) and its variants are found in many fields, especially logistics. In this study, we introduced an adaptive method to a complex VRP. It combines multi-objective optimization and several forms of VRPs with practical requirements for an urban shipment system. The optimizer needs to consider terrain and traffic conditions. The proposed model also considers customers' expectations, shipper considerations as goals, and the common goal like transportation cost. We offered compromise programming to approach the multi-objective problem by decomposing the original multi-objective problem into a minimized distance-based problem. We designed a hybrid version of the Genetic algorithm with the Local Search algorithm to solve the proposed problem. We evaluate the effectiveness of the proposed algorithm with the Tabu Search algorithm, the original Genetic algorithm on the tested dataset. The results show that our method is an effective decision-making tool for the multi-objective VRP and an effective solver for the new variation of VRP.

The Retail Industry’s Impact of Artificial Intelligence Chatbots and Augmented-Reality Applications: An examination of trust and satisfaction of the Youth Vietnamese online shopping

As competition in the retail industry heats up, businesses are increasingly resorting to kinds of artificial intelligence (AI) to differentiate themselves. E-commerce firms are combining technologies such as AI chatbots and augmented reality applications (ARA), which have established themselves as prominent customer service solutions in the practitioner area. However, little is known about consumers’ views and participation with developing technologies when they are implemented in a retail setting. A theory-based study model was developed to elucidate the motivational factors required for effective decision-making in this environment. The proposed model was supported by empirical testing conducted as a field study.

Review of studies of blockchain technology effects on the shipping industry

Decision-making is a prolific research area in the internet era, which has propelled globalization and the virtual elimination of many country border barriers. However, effective decision-making in the shipping industry is a time consuming and often complicated process. Digital evolution has provided new innovative organizational operation methods. Blockchain technology—a basic component of the Fourth Industrial Revolution—is one such innovation that promises to alter the process of decision-making. However, only a few academic studies have explored the decision-making aspect of blockchain technology. Moreover, there is a dearth of comprehensive research on how blockchain affects decisions in the shipping industry. This study explored how this novice technology can address issues, such as vast documentation and information asymmetry in the shipping industry. Specifically, grounded theory was used to qualitatively investigate extant practices and examine the potential impact of blockchain technology on decision-making in the shipping industry and the potential of using blockchain technology to emancipate decision-making. The study results indicate that the instant and reliable data-sharing capability of blockchain can significantly impact the shipping industry, while transforming its decision-making processes.

SARS-CoV-2, alcohol consumption, poor social behaviour, and the COVID-19 pandemic

Studies dealing with the SARS-CoV-2 virus and the COVID-19 disease have concentrated on the study of the virus and the disease themselves, but a knowledge of the causes responsible for the pandemic is still lacking. Crucial for effective decision making and control of the pandemic is a thorough and critical analysis of data regarding COVID-19, which shows an intimate relation between the number of cases/deaths and the consumption of alcohol. Ranked top 30 countries in COVID-19 cases/deaths and alcohol consumption coincide, with only a few exceptions. This coincidence is not fortuitous nor surprising, because excessive alcohol consumption is known to have pernicious effects on social behaviour, i.e. lead to deviant and irresponsible behaviour, which greatly promotes transmission

Higher Education Institutional Strategies to Sustain Quality Education

During the COVID-19 pandemic, higher education institutions (HEIs) faced serious challenges that raised concerns about sustaining the quality of education delivered to students and the quality of the graduates produced. Many HEIs throughout the world were unable to sustain the quality of teaching and learning due to many issues including lack of clear strategies, policies, procedures, and practices. This chapter will identify successful practices of HEIs for achieving sustainable quality education during COVID-19, based on transformation strategies in line with United Nations Sustainable Development Goals. This chapter will also highlight the role of governance in strategic decision making throughout strategy transformation and the impact of leaders on effective decision making during the crisis in developing successful practices for sustainable quality education.

Big Data Classification and Internet of Things in Healthcare

Every single day, a massive amount of data is generated by different medical data sources. Processing this wealth of data is indeed a daunting task, and it forces us to adopt smart and scalable computational strategies, including machine intelligence, big data analytics, and data classification. The authors can use the Big Data analysis for effective decision making in healthcare domain using the existing machine learning algorithms with some modification to it. The fundamental purpose of this article is to summarize the role of Big Data analysis in healthcare, and to provide a comprehensive analysis of the various techniques involved in mining big data. This article provides an overview of Big Data, applicability of it in healthcare, some of the work in progress and a future works. Therefore, in this article, the use of machine learning techniques is proposed for real-time diabetic patient data analysis from IoT devices and gateways.

Application and Recent Trends in Implementation of Internet of Things: A comprehensive review

Internet of Things (IoT) is an evolving technology in the current era with a combination of diverse computational technologies, objects, animals and human. The objects in the IoT framework transmit data among themselves and they are assigned with unique numbers for identification. The communication among the network is established by identification system and functions without any centralized system. Advancement in the sensor network has made automation in numerous field and integration of soft computing technology in the IoT system has made effective decision making. The objects resides in the IoT system acts intelligent and perform the actions intelligently. The IoT based technology enhances daily life of humans via connected devices and makes living things context-aware. The information collected from sensors will be processed with the computational algorithms and effective predictions are accomplished. In this article, recent applications and soft computing algorithms are reviewed. In addition to that numerous applications based on IoT is also discussed in this article.

Analysis of Principals’ Decision-Making: A Literature Study

This research was conducted to analyze the decision making by the principal. The analysis is carried out on the stages of decision making, influencing variables and factors, so that decision making is better. Effective decision making will make the school able to realize its vision and goals. This research uses the literature study method. The main source of research data is articles on school principals' decision-making obtained from Google Scholar. The technique of data collection is done by the method of documentation. The results showed that the principal has carried out the decision-making process by following six decision-making steps: problem identification, gathering information, developing alternative solutions, choosing the best alternative, implementing alternatives, and evaluating decisions. There are five variables that influence decision making by the principal. The five variables are self-efficacy, administration knowledge, management information system, emotional quotient and personality. Decision-making by the principal will be more effective by involving teachers and education staff.

Institutional Commitment Problems and Regional Autonomy: The Catalan Case

This article examines what constitutional arrangements are more likely to facilitate the transfer of effective decision-making power to the regional level. We show that certain constitutional arrangements can result in institutional commitment problems between regional minority and national majority groups, which in turn influence levels of regional autonomy across regions. Specifically, we examine how the depth and scope of decentralization depend on the presence of federal agreements and the availability of institutional guarantees that make the federal contracts credible. Analyzing regional-level data, we show that regions where identity minority groups are majoritarian enjoy more regional autonomy when the commitment problem has resulted in a satisfactory national accommodation. Our findings highlight two important scenarios. The first occurs when the institutional commitment problem is solved, and regional minority groups are granted substantial levels of regional autonomy. The second scenario takes place when the commitment problem is not institutionally accommodated, and hence regional minority groups have systematically lower levels of autonomy. This article illustrates that both federal contracts and credible agreements are important tools to understand regional decision-making powers.