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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.

Managing differences is a difficult undertaking, especially considering the difficulties arising from the unconscious functions of our brains. Organisations should strive to counteract the potentially harmful effects of unconscious bias by implementing policies that support bias-aware management and decision-making. Although it is obvious that bias cannot be completely eliminated, there is enough data, as discussed in this work, to demonstrate that unconscious bias and stereotypes can be addressed and decreased with mindfulness-based interventions (MBIs) to some extent. Mindfulness involves the process of bringing non-judgemental awareness to experience by striving for full attention in the present moment. In this context, including mindfulness practises into training programmes for equality, diversity, and inclusion may serve as an accelerator for recognising hidden biases, reducing stereotypes, eliminating discrimination, and encouraging cognitive changes. This chapter explains the ways in which MBIs can be used to promote cognitive changes and comprehend the automatic and unconscious nature of emotions and thoughts in order to remove barriers between all differences in the workplace.

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.

The conceptualization of smart emerged by technological advancements penetrated the tourism industry with the pace of globalization transformed the destinations providing digitalized products. Even though smart tourism destinations are initiated by advanced technologies, the notion evolved in embracing Sustainable Development Goals (SDGs) project economic, social, and environmental proliferation. A tourism destination is counted as “smart” which provides advanced technologies to improve the quality of tourists' experiences and enhance the residents' quality of life. The structure of a smart tourism destination is established on four basic pillars that cover technology, innovation, accessibility, and sustainability issues. Designating the notion of smart into tourism destinations is extremely vital since the shifting paradigm of tourists’ demands concern sustainability. The development of smart in a tourism destination is a crucial concern for destination management organizations (DMOs) integrating key destination components with the dimensions of a smart city to enhance the tourists' satisfaction and competitiveness of the destination. Therefore, one aim of this chapter is to elucidate the association between key destination components with the dimensions of a smart city to reveal the related smart tourism destination applications. Moreover, cultural heritage in smart tourism destinations forms an important part of tourism both with its tangible and intangible resources which have been involved in the emergent era of digitalization inevitably with all parties and processes. Hence, another aim of this chapter is to examine the dimensional shift in cultural heritage tourism within the framework of digitalization. Sharing cases of digitization of cultural heritage from different parts of the world, this chapter also reflects that it is inevitable to benefit from digitization and ICTs in order to reach the SDGs on the scale of smart tourism destinations. Analysis of academic publications and the national and international reports of the related authorities sums the methodology used to conclude the study with suggestions of future research paths to develop the field.

This study investigates when and for whom job crafting may turn into job quitting. The authors hypothesize that approach job crafting relates more positively to turnover intentions and subsequent voluntary job changes among employees with (a) high (vs low) need for career challenges and (b) those with high (vs low) self-esteem.

Data were collected from 575 employees of a large public organization in the Netherlands with two measurement moments three months apart. Hypotheses were tested using cross-lagged regression analyses and path modeling.

Supporting the hypotheses, approach crafting related positively to an increase in turnover intentions only among employees with high need for challenge or high self-esteem. Moreover, via turnover intentions at Time 1, approach crafting related positively to the voluntary job change at Time 2 for employees with (a) high need for challenge, as well as those with (b) high self-esteem. These findings held after controlling for avoidance crafting.

This study has been conducted in a relatively homogenous sample. Future research may test the predictions in a more heterogeneous sample, including participants from different cultural and economic contexts.

The authors advise human resource (HR) professionals to facilitate the job crafting efforts of employees with a high need for challenge and those with high self-esteem because these groups are particularly at risk of voluntarily quitting their jobs. Adopting insights from the wise proactivity model may help ensure that job crafting benefits both employees and employers.

This study brings clarity to the inconsistent relationships between job crafting and job quitting by using the wise proactivity model as an explanatory framework.