VINERS Method for the Multiple Criteria Analysis and Neuromarketing of Best Places to Live

The best and worst places to live have been analysed in the world for many years and multiple criteria analysis has been used for that purpose. The quality of housing and its environment, pollution, green places, public spaces, physical movement and health, crime rates and individual safety, the wellbeing of youngsters, unemployment, job value, economic scarcity, governance, circadian rhythm, weekly rhythm and other factors are the focus of such analyses that aim to determine levels of positive emotions and happiness in built environment. Questionnaires are the most common tool for such analyses, where inhabitants are asked to rank their happiness experience as a whole in built environment. Many studies demonstrate that happy people are effective in multiple areas of their life including job efficiency, salary, health, human relations, etc. The innovative aspect of this research stems from the fact that biometric technologies (affective attitudes, emotional and physiological states) and the VINERS method developed by the authors are used to determine the best places to live and to serve neuro ads of homes for sale. To do this, rational segments of homebuyers are determined according to their demographic profiles (age, gender, education, marital status, families with children, main source of income), consumer psychographics and behaviour (happy, sad and angry along with valence and heart rate) and then select a rational video ad for such rational segment. The aim of our research is to develop the VINERS Method for the Multiple Criteria Analysis and Neuromarketing of Best Places to Live (VINERS method) by combining the Somatic Marker Hypothesis, biometrics, neuromarketing and COPRAS method. This article presents a case study to demonstrate the VINERS method put to practice

COVID-19 and Green Housing: A Review of Relevant Literature

This review presents an analysis of three hypotheses. The articles provide a specific perspective on green housing before, during, and post COVID-19. The validations of these hypotheses were performed by analyzing the scientific literature worldwide and by adding a statistical analysis of appropriate articles from the Scopus database. The purpose of this review is to overview the research written on housing developments during the upsurge of COVID-19 along with the responses from the green building sector, because this field appears to be rapidly emerging by the sheer volume of research studies currently undertaken. Foremost peer-reviewed journals covering construction, urban studies, real estate, energy, civil engineering, buildings, indoor air, management, economics, business, environmental studies, and environmental sciences that were published last year were selected for review. The review was conducted by applying a combination of various keywords and the criteria for paper selection, including sustainable building, green construction, green building, resource-efficient, a building’s lifecycle, COVID-19, energy, water, consumption, health effects, comfort, occupant behaviors, policy, economy, Industry 5.0, energy-efficient retrofitting, and profit. Two, innovative elements in this study stand out when comparing it with the most advanced research on green housing before, during, and after COVID-19. The first innovation relates to the integrated analyses of COVID-19 pandemic, housing policies of countries and cities pertinent to COVID-19 that impact green housing and the wellbeing of their residents as well as the impact made by residents and a housing policy on the dispersion of COVID-19. This research additionally establishes that a green building analysis is markedly more effective when the analysis comprehensively covers the life process of a green building, the participating interest groups that have their own goals they wish to implement, the COVID-19 situation, and the external micro- and macro-level environments as a singular entity

Sustainable Construction Investment, Real Estate Development, and COVID-19: A Review of Literature in the Field

Aspects of sustainable construction investment and real estate development (CIRED) and their interrelations during the period pre-, intra-, and post-COVID-19, are presented in the research. Applications of the topic model, environmental psychology theory, building life cycle method, and certain elements of bibliometrics, webometrics, article level metrics, altmetrics, and scientometrics make it possible to perform a quantitative analysis on CIRED. The CIRED topic model was developed in seven steps. This paper aims to present a literature review on CIRED throughout the pandemic and to look at the responses from the real estate and construction sector. This sector is a field that appears to be rapidly expanding, judging from the volume of current research papers. This review focuses on last year’s leading peer-reviewed journals. A combination of various keywords was applied for the review and the criteria for paper selections included construction investment, real estate development, civil engineering, COVID-19, and sustainability, as well as residential, industrial, commercial, land, and special purpose real estate, along with their risks, strategies, and trends. The articles reviewed for this paper, which analyzes three hypotheses, look at pre-, intra-, and post-pandemic CIRED. The three hypotheses were validated by analyzing scientific publications from around the world. Two innovative elements make this study stand out among the most advanced research on pre-, intra-, and post-pandemic CIRED. The first of the two innovations is the integrated analysis of the COVID-19 pandemic, COVID-19-related national policies, and business investment strategies relevant to CIRED and the interests of investors as well as on the impact a CIRED policy and investors make on the spread of COVID-19. In addition, this research demonstrates a marked increase in the effectiveness of a CIRED analysis, when the life cycle of a CIRED, the involved stakeholders with their own individual interests, the COVID-19 situation, and the external micro-, meso-, and macro-environments are covered comprehensively as a single entity

A Review of AI Cloud and Edge Sensors, Methods, and Applications for the Recognition of Emotional, Affective and Physiological States

Affective, emotional, and physiological states (AFFECT) detection and recognition by capturing human signals is a fast-growing area, which has been applied across numerous domains. The research aim is to review publications on how techniques that use brain and biometric sensors can be used for AFFECT recognition, consolidate the findings, provide a rationale for the current methods, compare the effectiveness of existing methods, and quantify how likely they are to address the issues/challenges in the field. In efforts to achieve the key goals of Society 5.0, Industry 5.0, and human-centered design better, the recognition of emotional, affective, and physiological states is progressively becoming an important matter and offers tremendous growth of knowledge and progress in these and other related fields. In this research, a review of AFFECT recognition brain and biometric sensors, methods, and applications was performed, based on Plutchik’s wheel of emotions. Due to the immense variety of existing sensors and sensing systems, this study aimed to provide an analysis of the available sensors that can be used to define human AFFECT, and to classify them based on the type of sensing area and their efficiency in real implementations. Based on statistical and multiple criteria analysis across 169 nations, our outcomes introduce a connection between a nation’s success, its number of Web of Science articles published, and its frequency of citation on AFFECT recognition. The principal conclusions present how this research contributes to the big picture in the field under analysis and explore forthcoming study trends