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Magneto-quasi-static fields emanated by inductive charging systems can be potentially harmful to the human body. Recent projects, such as TALAKO and MILAS, use the technique of wireless power transfer (WPT) to charge batteries of electrically powered vehicles. To ensure the safety of passengers, the exposing magnetic flux density needs to be measured in situ and compared to reference limit values. However, in the design phase of these systems, numerical simulations of the emanated magnetic flux density are inevitable. This study aims to present a tool along with a workflow, based on the Scaled-Frequency Finite Difference Time-Domain and Co-Simulation Scalar Potential Finite Difference schemes, to determine body-internal magnetic flux densities, electric field strengths and induced voltages into cardiac pacemakers. The simulations should be time efficient, with lower computational costs and minimal human workload.

The numerical assessment of the human exposure to magneto-quasi-static fields is computationally expensive, especially when considering high-resolution discretization models of vehicles and WPT systems. Incorporating human body models into the simulation further enhances the number of mesh cells by multiple millions. Hence, the number of simulations including all components and human models needs to be limited while efficient numerical schemes need to be applied.

This work presents and compares four exposure scenarios using the presented numerical methods. By efficiently combining numerical methods, the simulation time can be reduced by a factor of 3.5 and the required storage space by almost a factor of 4.

This work presents and discusses an efficient way to determine the exposure of human beings in the vicinity of wireless power transfer systems that saves computer simulation resources and human workload.

Inductive charging systems for electrically powered cars produce a magneto-quasistatic field and organism in the vicinity might be exposed to that field. Magneto-quasistatic fields induce electric fields in the human body that should not exceed limits given by the International Commission of Non-Ionizing Radiation protection (ICNIRP) to ensure that no harm is done to the human body. As these electric fields cannot be measured directly, they need to be derived from the measured magnetic flux densities. To get an almost real-time estimation of the harmfulness of the magnetic flux density to the human body, the electric field needs to be calculated within a minimal computing time. The purpose of this study is to identify fast linear equations solver for the discrete Poisson system of the Co-Simulation Scalar Potential Finite Difference scheme on different graphics processing unit systems.

The determination of the exposure requires a fast linear equations solver for the discrete Poisson system of the Co-Simulation Scalar Potential Finite Difference (Co-Sim. SPFD) scheme. Here, the use of the AmgX library on NVIDIA GPUs is presented for this task.

Using the AmgX library enables solving the equation system resulting from an ICNIRP recommended human voxel model resolution of 2 mm in less than 0.5 s on a single NVIDIA Tesla V100 GPU.

This work is one essential advancement to determine the exposure of humans from wireless charging system in near real-time from in situ magnetic flux density measurements.

This study aims to investigate the surface modification on 20CrMnTi gear steel individually treated by diamond-like carbon films and nitride coatings.

For this purpose, the mechanical properties of a-C:H, ta-C and AlCrSiN coatings are characterized by nano-indentation and scratch tests. The friction and wear behaviors of these three coatings are evaluated by ball-on-disc tribological experiments under dry contact conditions.

The results show that the a-C:H coating has the highest coating-substrate adhesion strength (495 mN) and the smoothest surface (Ra is about 0.045 µm) compared with the other two coatings. The AlCrSiN coating shows the highest mean coefficient of friction (COF), whereas the ta-C coating exhibits the lowest one (steady at about 0.16). The carbon-based coatings possess excellent self-lubricating properties compared with nitride ceramic ones, which effectively reduce the COF by about 64%. The major failure mode of carbon-based coatings in dry contact is slight abrasive wear. The damage of AlCrSiN coating is mainly adhesive wear and abrasive wear.

It is suggested that the carbon-based film can effectively improve the friction-reducing and wear resistance performance of the gear steel surface, which has a promising application prospect in the mechanical transmission field.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0129/

Although many scholars have investigated different aspects of the notion of innovation ambidexterity, the conceptualization of examining this concept in a technological setting remained unclear, as no serious attempts have been made to figure out the core concept of innovation ambidexterity in a technological context, which is a critical concept for high-tech firms.

The purpose of this paper is to examine the role family identity and reputational concerns plays when private family firms engage in earnings management.

The paper is conducted as an archival study using data from private limited liability firms in Norway over the period from 2002 to 2015. The dataset includes financial accounting data and data on family relationships between shareholders, board members and CEOs, where family relationships are determined through bloodlines, adoption and marriage, tracing back four generations and extending out to third cousins. To investigate the incidence of earnings management, the authors employ a measure of accrual-based earnings management (AEM) (Dechow and Dichev, 2002; McNichols, 2002) and a measure of real earnings management (REM) (Roychowdhury, 2006). They use whether or not the family name is included in the firm name (i.e. family name congruence) as a proxy for family members' identification with the family firm and their sensitivity to reputational concerns.

The authors’ results show that AEM is lower for family-named family firms. Moreover, their findings also indicate that family-named family firms are more likely to select REM over AEM, compared to nonfamily named family firms. This is even more pronounced when detection risk is high (high quality audit proxied by Big 4).

The quality of the authors’ findings is limited to the validity of their proxy for family firm identification and reputational concerns (the family name included in the firm name). Even though findings from prior research suggest that family name congruence is a valid proxy for identity and reputational concerns (e.g. Kashmiri and Mahajan, 2010, 2014; Rousseau et al., 2018; Zellweger et al., 2013), future research should investigate the validity of these results using alternative proxies for family firm identification. Future research should also investigate whether the authors’ findings are generalizable to public family firms.

The authors’ results suggest that the risk of AEM is lower for family-named family firms, whereas the risk of REM is somewhat higher, compared to nonfamily named family firms. These results might be relevant for financial accounting users, auditors and supervisory and monitoring bodies when assessing the risk of earnings management.

The paper is, as far as the authors are aware of, the first to investigate the role of family name congruence and detection risk when private family firms select between AEM and REM.

This chapter examines the main methodological issues involved in the comprehension of the cost structure of the airport industry and suggests considerations for future airport cost analyses. Such understanding has become a crucial concern for policy makers, regional planners, and managers in order to deal with optimal market design (e.g., regulation and market configuration) and airport strategies (e.g., pricing, investments, and alliances). An in-depth analysis of the economics of cost functions is presented, together with a description of the relevant multi-output cost economies measures (average incremental costs, scale and scope economies, and cost complementarities). We also discuss the assumptions underlying estimates of total versus variable cost functions and the importance of estimating a sufficiently flexible functional form. Moreover, we provide a critical survey of the international empirical literature on the cost structure of the airport industry, which highlights how econometric estimates strongly depend on the sample choice and the empirical model considered. Indeed, while econometric studies on international samples based on long-run cost function estimates show that long-run scale economies are never exhausted, single country studies mostly estimate variable cost functions and find lower values for scale economies at median sample points that tend to decrease with size. We discuss why we believe that studies based on the estimation of short-run variable cost functions offer more reliable results, given the reasonable assumption of airport overcapitalization in the short run. We conclude our work by noting that underlying policy issues related to planning and regulation, as well as to the optimal market structure of the airport sector, need to take into account the role played by vertical relationships between airports and airlines.

Creativity and innovation have been buzzwords of managerial discourse over the last few decades as they contribute to the long-term survival and competitiveness of firms. Given the non-linear, causally ambiguous, and intangible nature of all innovation-related phenomena, management scholars have been trying to uncover factors that contribute to creativity and innovation from multiple lenses ranging from organizational behavior at the micro-level to strategic management at the macro-level. Along with important and insightful developments in these research streams that evolved independently from one another, human resource management (HRM) research – especially from a strategic perspective – has only recently started to contribute to a better understanding of both creativity and innovation. The goal of this chapter is to review the contributions of strategic HRM research to an improved understanding of creativity at the individual-level and innovation at the firm-level. In organizing this review, the authors rely on the open innovation funnel as a metaphor to review research on both HRM practices and HRM systems that contribute to creativity and innovation. In the last section, the authors focus on more recent developments in HRM research that focus on ambidexterity – as a way for HRM to simultaneously facilitate exploration and exploitation. This chapter concludes with a discussion of future research directions.

The purpose of this paper is to study the performance of the X‐bar chart on the basis of average run lengths (ARLs) for the positively correlated data. The ARLs at various sets of parameters of the X‐bar chart are computed by simulation. The performance of the chart at the various shifts in the process mean is compared with the X‐bar chart suggested by Zang and residual chart proposed by Zang. The optimal schemes suggested in this paper are also compared with variable parameters (VP) chart and double sampling (DS) X‐bar chart suggested by Costa and Machado.

Positively correlated observations having normal distribution are generated with the help of the MATLAB software. The performance of the X‐bar chart in terms of ARLs at the various shifts in the process mean is compared with the X‐bar chart suggested by Zang and residual chart proposed by Zang. The optimal schemes are also compared with VP X‐bar chart and DS X‐bar chart suggested by Costa and Machado.

The suggested optimal schemes of X‐bar chart perform better at the various shifts in the process mean than the X‐bar chart suggested by Zang and residual chart suggested by Zang. It was concluded that, although the suggested schemes for X‐bar chart detect shifts later than the VP and DS X‐bar charts proposed by Costa and Machado, they involved a much smaller number of parameters that are to be adjusted. So the time required for adjustment in case of optimal scheme is very small compared to the VP and DS charts.

The optimal schemes of X‐bar chart are developed for the normally distributed autocorrelated data. But this assumption may also be relaxed to design these schemes for autocorrelated data. Moreover, the optimal schemes for chart can be developed for variable sample size and for variable sampling intervals.

Although it is the extension of previous work, it can be applied to various manufacturing industries as well as service industries where the data is positively correlated and normally distributed.

This study is based on a web-based advertising value model, adding emotional appeal, advertising credibility, advertising clicks, product evaluation and incentive to examine the impact on consumers' product evaluation and purchase intention.

In total, 313 valid online questionnaires were collected from those who had browsed the social media advertisement.

The results show that advertising credibility and emotional appeal have a higher impact on advertising attitude than informativeness and irritation in the original web-based advertising value model.

The findings strengthen the literature on the antecedents of advertising attitude in social media context, confirming advertising clicks as a predictor of product evaluation, and determining that advertising attitude, product evaluation and incentive play key roles as predictors of consumer purchase intention.

The findings are particularly relevant to advertising marketing managers. In the context of social media advertising, the advertising credibility of consumers is the key to increasing consumers' willingness to purchase. Advertisers must establish a good advertising reputation to consumers in the social media context.

This study combines the web-based advertising value model, advertising clicks, product evaluation and incentive to investigate the factors that influence customers' purchase decisions in the context of social media.

The purpose of the paper is to advance a framework that can analyze the impact of the egocentric alliance network on firm ambidextrous innovation holistically. On this purpose, the framework involves and integrates structural holes (SH), alliance functional diversity (AFD) and alliance partner geographical diversity (APGD) that measure network characteristics from structural, relational and nodal perspectives, respectively.

The authors collected multi-source matching panel data including alliance deals, technical patents and financial information during 2000–2017 of the 106 top high-tech firms in the computer, communications, electronics and biopharmaceutical industries and conducted a three-way interaction model to uncover the complex mechanisms from a contingency perspective.

Empirical results show that SH as structural capital is positive to both exploitative and exploratory innovation. Both AFD as relational capital and APGD as cognitive capital positively moderate the SH-exploitative innovation nexus rather than the SH-exploratory innovation nexus. APGD and AFD co-moderate the relationship between SH and firm ambidextrous innovation in the way that when APGD and AFD are both high, SH has the strongest positive impacts on firm exploitative and exploratory innovation.

This research provides new insights into the benefit-cost paradox of the structural brokerage position (SH) by uncovering relational (AFD) and nodal (APGD) network characteristics that impact the trade-off. Also, it contributes to social capital theory by differentiating three dimensions of network capital (structural, relational and cognitive capital) and integrating them into ambidextrous innovation research. Finally, the findings give firms enlightenment to configure their egocentric alliance network for innovation ambidexterity.