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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.

This paper aims to introduce a heteroskedastic hidden truncation normal (HTN) model that allows for conditional volatilities, skewness and kurtosis, which evolve over time and are linked to economic dynamics and have economic interpretations.

The model consists of the HTN distribution introduced by Arnold et al. (1993) coupled with the NGARCH type (Engle and Ng, 1993). The HTN distribution nests two well-known distributions: the skew-normal family (Azzalini, 1985) and the normal distributions. The HTN family of distributions depends on a hidden truncation and has four parameters having economic interpretations in terms of conditional volatilities, kurtosis and correlations between the observed variable and the hidden truncated variable.

The model parameters are estimated using the maximum likelihood estimator. An empirical application to market data indicates the HTN-NGARCH model captures stylized facts manifested in financial market data, specifically volatility clustering, leverage effect, conditional skewness and kurtosis. The authors also compare the performance of the HTN-NGARCH model to the mixed normal (MN) heteroskedastic MN-NGARCH model.

The paper presents a structure dynamic, allowing us to explore the volatility spillover between the observed and the hidden truncated variable. The conditional volatilities and skewness have the ability at modeling persistence in volatilities and the leverage effects as well as conditional kurtosis of the S&P 500 index.

The purpose of this study is to investigate the influencing mechanism of consumers' continuous purchase intention toward the subscriber-based knowledge payment platforms (SBKPPs).

This study obtained 226 valid samples through questionnaire surveys and used partial least square structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) methods to elucidate the complex causal patterns of consumers' continuous purchase intention toward the SBKPPs.

The findings revealed that perceived utilitarian value, perceived hedonic value and perceived social value directly affected consumers' continuous purchase intention, while content quality and service quality indirectly affected consumers' continuous purchase intention. In addition, this study also demonstrated that all factors must be combined to play a role, and there exist four configurations resulting in consumers' continuous purchase intention toward the SBKPPs.

The results can help researchers and practitioners better understand the causal patterns of consumers' continuous purchase intention toward the SBKPPs.

This study contributes to the knowledge payment literature by investigating consumers' continuous purchase intention toward the SBKPPs. This study also provides practical enlightenment for the SBKPPs' marketing.

Racial stigma and racial criminalization have been centralizing pillars of the construction of Blackness in the United States. Taking such systemic injustice and racism as a given, then question then becomes how these macro-level arrangements are reflected in micro-level processes. This work uses radical interactionism and stigma theory to explore the potential implications for racialized identity construction and the development of “criminalized subjectivity” among Black undergraduate students at a predominately white university in the Midwest. I use semistructured interviews to explore the implications of racial stigma and criminalization on micro-level identity construction and how understandings of these issues can change across space and over the course of one's life. Findings demonstrate that Black university students are keenly aware of this particular stigma and its consequences in increasingly complex ways from the time they are school-aged children. They were aware of this stigma as a social fact but did not internalize it as a true reflection of themselves; said internalization was thwarted through strong self-concept and racial socialization. This increasingly complex awareness is also informed by an intersectional lens for some interviewees. I argue not only that the concept of stigma must be explicitly placed within these larger systems but also that understanding and identity-building are both rooted in ever-evolving processes of interaction and meaning-making. This research contributes to scholarship that applies a critical lens to Goffmanian stigma rooted in Black sociology and criminology and from the perspectives of the stigmatized themselves.

With the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components.

We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function.

First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components.

Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.

This study aims to examine the impact of brand ethical behavior, specifically perceived brand ethicality, on corporate brand legitimacy in the context of halal cosmetics, by considering perceived brand integrity as a mediating factor.

The study used a quantitative cross-sectional research design to gather data from 341 fast-moving consumer goods (FMCG) in Tanzania. The data was analyzed by using AMOS 21, using structural equation modeling techniques.

The findings indicated that perceived brand ethicality has a significant influence on corporate brand legitimacy through the mediation of perceived brand integrity.

The study emphasizes the significance of incorporating and clarifying Islamic laws as integral components of marketing strategies aimed at attracting conscientious customers of halal products. It recommends defining Islamic laws as societal values and norms and integrating them into various brand practices to showcase professionalism, ultimately fostering social acceptance and approval. The study presents valuable practical implications for managers and marketers of FMCG, assisting them in formulating policies and strategies that reflect societal values and norms.

This study represents a novel endeavor that explores the interplay between perceived brand ethicality, corporate brand legitimacy and perceived brand integrity in the context of halal products. It extends theoretical understanding by shedding light on the significance of Islamic laws as a foundation for establishing a competitive advantage. By offering and designing ethical practices, businesses can enhance their legitimacy among halal consumers, particularly in the domain of halal cosmetics.

This paper aims to provide an objective and comprehensive evaluation of the understanding of the professional code of ethics of Indian Professional Management Accountants in Business (PMAIBs). It further delves into their individual, job and organizational characteristics as determinants of their understanding of the code.

This study relies on data from 247 responses to a survey-based questionnaire. Overall scores and sub-scores of the level of understanding of the code were calculated based on questions grounded in IESBA Code and ethical dilemmas. The drivers of these scores were then examined using one-way ANOVA, OLS, Probit and ordered probit regressions.

This study found considerable heterogeneity in Indian PMAIBs' understanding of their professional code of ethics and substantial scope for improvements. PMAIBs were stronger in Application, Resolution and Threats but weaker in Theory and Principles. Further, PMAIBs who had ranked themselves higher on code-familiarity, had higher moral maturity, hailed from western India and worked for foreign-listed, foreign-owned firms were found to have a higher level of understanding of the code. Highly educated elderly professionals and professionals with more responsibility areas exhibited a lower level of understanding of the code.

Insights from the study can help professional bodies, employers and academics identify and segment PMAIBs based on their ethics-training needs and customize interventions, which can benefit businesses and society through reduced corporate ethical failures. Considering the risk implications of Indian PMAIBs' inadequacies in understanding their code of ethics, the Indian professional accounting organization (ICAI-CMA) should mandate ethics in continuing professional development and expedite its long pending convergence with the IESBA code, a global benchmark for professional accountants.

This paper assesses the understanding of the professional code of ethics of PMAIBs, which is crucial yet amiss in the accounting ethics literature. While ethical decision-making is extensively researched, how well the professionals understand their code is yet unexplored. Research on PMAIBs, despite their unique ethical vulnerabilities and increasingly vital role in organizations, is still dormant. This study aims to fill these gaps by examining PMAIBs from India, an emerging economy under-represented in accounting ethics literature. India offers an important and rich setting for the study due to its large size, fast growth, deep integration with the global economy, high perceived corruption levels and poor ethical behavior of its firms.

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.