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Avatars, which are used as a technology and marketing tactic, can embody consumer-facing employees and mimic their real-life roles on companies' websites, thereby playing a key role in enhancing the relationships between consumers and brands in the online environment. Academics and practitioners have increasingly acknowledged the significance of the consumer-brand relationship in both traditional and online contexts. However, the impersonal nature of the online environment is considered to be a hindrance to the development of these relationships. Despite the importance of this technology, little attention has been paid to the investigation of the avatar concept from a marketing perspective. This paper explores the nature of the avatar concept, including its main characteristics, dimensions, and conditions as well as the attitudinal and behavioural consequences of avatar users.

Adopting the qualitative design, a taxonomy was developed from interviews. In total, 42 interviews were conducted with current university students. 30 participants participated in the exploratory interviews. A total of 12 interviews were conducted during the in-depth stage based on findings in the preceding research.

Based on the qualitative data analysis, a taxonomy was developed. The idea of the taxonomy is summarized in that different dimensions of the avatar are considered the main base (first phase) of the taxonomy. There are consequential three parts: the attitudinal consequences related to the website; the attitudinal consequences related to the brand; the behaviours towards the brand. These behaviours represent the final phase of the taxonomy.

By developing a taxonomy of using avatars on brands' websites, the authors advance the understanding consumer-brands relationships. Using avatars' verbal interactions helps in shaping consumers' cognitive, affective, attitudinal and behavioural responses and add vital empirical evidence to the increasing body of research and practices involving avatar usage in the interactive marketing area.

There are few reports that evolutional topology optimization methods are applied to the conductor geometry design problems. This paper aims to propose an evolutional topology optimization method is applied to the conductor design problems of an on-chip inductor model.

This paper presents a topology optimization method for conductor shape designs. This method is based on the normalized Gaussian network-based evolutional on/off topology optimization method and the covariance matrix adaptation evolution strategy. As a target device, an on-chip planer inductor is used, and single- and multi-objective optimization problems are defined. These optimization problems are solved by the proposed method.

Through the single- and multi-objective optimizations of the on-chip inductor, it is shown that the conductor shapes of the inductor can be optimized based on the proposed methods.

The proposed topology optimization method is applicable to the conductor design problems in that the connectivity of the shapes is strongly required.

In this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate.

The authors hypothesize that empirical error in the interpretation and qualitative assessment of visual content can be minimized by collating the assessments of multiple individuals and through use of repeated trials. Motivated by this problem, the authors developed an experimental approach for semi-automatic extraction of qualitative real estate metadata based on Comparative Judgments and Deep Learning. The authors evaluate the feasibility of our approach with the help of Hedonic Models.

The results show that the collated assessments of qualitative features of interior images show a notable effect on the price models and thus over potential for further research within this paradigm.

To the best of the authors’ knowledge, this is the first approach that combines and collates the subjective ratings of visual features and deep learning for real estate use cases.

The purpose of this paper is to illustrate the new technical demands and reliability challenges to printed circuit board (PCB) designs, materials and processes when the transmission frequency increases from Sub-6 GHz in previous generations to millimeter (mm) wave in fifth-generation (5G) communication technology.

The approach involves theoretical analysis and actual case study by various characterization techniques, such as a stereo microscope, metallographic microscope, scanning electron microscope, energy dispersive spectroscopy, focused ion beam, high-frequency structure simulator, stripline resonator and mechanical test.

To meet PCB signal integrity demands in mm-wave frequency bands, the improving proposals on copper profile, resin system, reinforcement fabric, filler, electromagnetic interference-reducing design, transmission line as well as via layout, surface treatment, drilling, desmear, laminating and electroplating were discussed. And the failure causes and effects of typical reliability issues, including complex permittivity fluctuation at different frequencies or environments, weakening of peel strength, conductive anodic filament, crack on microvias, the effect of solder joint void on signal transmission performance and soldering anomalies at ball grid array location on high-speed PCBs, were demonstrated.

The PCB reliability problem is the leading factor to cause failures of PCB assemblies concluded from statistical results on the failure cases sent to our laboratory. The PCB reliability level is very essential to guarantee the reliability of the entire equipment. In this paper, the summarized technical demands and reliability issues that are rarely reported in existing articles were discussed systematically with new perspectives, which will be very critical to identify potential reliability risks for PCB in 5G mm-wave applications and implement targeted improvements.

With the recent increasing relevance of sustainability, multinational enterprises are faced with divergent stakeholder demands and persistently shifting priorities. This study aims to examine stakeholders’ perceptions of the sustainability performance of a gold mining subsidiary in Ghana.

Using a purposive sampling technique, the authors interviewed managers and employees of the case enterprise, officials of regulatory institutions and host community members on their perceptions of the case enterprise’s sustainability performance. The authors triangulated the opinions expressed by these stakeholders with data from annual reports. The data were analysed through the lens of stakeholder theory.

The authors found that while members of the host community and the regulatory institutions were keenly interested in the case enterprise’s social and environmental activities, they perceived their performance as unimpressive, considering the economic benefits derived from the mining operations. On the contrary, the managers and employees of the case enterprise were satisfied with their environmental compliance and social intervention programmes, even though the company’s economic position had declined. The authors submit that the variations in the sustainability performance perceptions among the stakeholders are due to the lack of a deeper understanding of the other stakeholders’ expectations.

To equitably satisfy diverse stakeholder expectations, the study highlights the role of stakeholder collaborations in understanding the expectations of more salient stakeholder groups such as community members and employees, as well as the lesser salient groups such as academics. It also demonstrates the fluidity of sustainability and its benefits in designing a consensual sustainable management strategy. This implies that managers of the case mining enterprise make the necessary efforts to meet the diverse stakeholder needs while attaining their primary objective of creating wealth for shareholders.

Compared to advanced economies, studies on sustainability performance in emerging economies are limited. Nonetheless, these limited studies leave out stakeholder perceptions, focusing more on quantitative performance indicators. Using thematic and content analyses, the authors investigate stakeholder perceptions on the sustainability performance of a case mining subsidiary operating in Ghana. The study focused on Ghana because it is ranked with South Africa as the top two producers of gold in Africa. Nonetheless, unlike South Africa, Ghana faces more sustainability challenges from the mining sector due to weak institutions in enforcing sustainability standards.

The purpose of this study is to explore whether immersive virtual reality (VR) can complement e-participation and help alleviate some major obstacles that hinder effective communication and collaboration. Immersive virtual reality (VR) can complement e-participation and help alleviate some major obstacles hindering effective communication and collaboration. VR technologies boost discussion participants' sense of presence and immersion; however, studying emerging VR technologies for their applicability to e-participation is challenging because of the lack of affordable and accessible infrastructures. In this paper, the authors present a novel framework for analyzing serious social VR engagements in the context of e-participation.

The authors propose a novel approach for artificial intelligence (AI)-supported, data-driven analysis of group engagements in immersive VR environments as an enabler for next-gen e-participation research. The authors propose a machine-learning-based VR interactions log analytics infrastructure to identify behavioral patterns. This paper includes features engineering to classify VR collaboration scenarios in four simulated e-participation engagements and a quantitative evaluation of the proposed approach performance.

The authors link theoretical dimensions of e-participation online interactions with specific user-behavioral patterns in VR engagements. The AI-powered immersive VR analytics infrastructure demonstrated good performance in automatically classifying behavioral scenarios in simulated e-participation engagements and the authors showed novel insights into the importance of specific features to perform this classification. The authors argue that our framework can be extended with more features and can cover additional patterns to enable future e-participation immersive VR research.

This research emphasizes technical means of supporting future e-participation research with a focus on immersive VR technologies as an enabler. This is the very first use-case for using this AI and data-driven infrastructure for real-time analytics in e-participation, and the authors plan to conduct more comprehensive studies using the same infrastructure.

The authors’ platform is ready to be used by researchers around the world. The authors have already received interest from researchers in the USA (Harvard University) and Israel and run collaborative online sessions.

The authors enable easy cloud access and simultaneous research session hosting 24/7 anywhere in the world at a very limited cost to e-participation researchers.

To the best of the authors’ knowledge, this is the very first attempt at building a dedicated AI-driven VR analytics infrastructure to study online e-participation engagements.

Research has shown that young adults face strong economic burdens when it comes to establishing their intimate relationships in times of labor market deregulation and economic recession. However, little is known about possible protective effects of the transition to cohabitation on subjective worries. Based on economic and gender-specific assumptions, the present paper uses data from the German Socio-economic Panel (GSOEP) from 1991 to 2020. Longitudinal analyses show that the transition into cohabitation reduces the economic worries of German women, especially in times of macroeconomic crisis. For men, cohabitation is only protective against economic worries if they or their partner have high economic resources. The latter may indicate that young men in precarious living situations perceive the male breadwinner model as a subjective burden in the context of cohabitation.

Past research has established a relationship between the perceptions of fairness in the division of household labor and relationship satisfaction. Varying according to gender and time, this relationship has been found with differing outcomes, including relationship satisfaction, relationship happiness, divorce, and sexual frequency. Although this relationship has been well studied, little research has focused on how this relationship is moderated by relationship status. According to the Second Demographic Transition Theory (SDT), as societies become more “modern,” cohabitation will become more prevalent, eventually becoming socially and culturally equivalent to marriage. As such, it is vital to ask how cohabitation and marriage differ, or if they differ at all. Therefore, this gap is explored by asking, “How do perceptions of the division of household labor affect married and cohabitating heterosexual couples’ relationship happiness and chance of separation?” In order to answer this question, the National Survey of Families and Households (Wave III) is analyzed, with outcomes focusing on relationship happiness and chance of separation. Results indicate that when married and cohabitating individuals experience similar levels of happiness with their partner’s housework, they also experience similar levels of relationship happiness and chance of separation, with relationship status not affecting the impact happiness with partner’s housework has on these relationship outcomes. This suggests that cohabitation and marriage may continue to become more similar overall.