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This study examines whether auditors’ pricing decisions on managerial ability are affected by auditor litigation risk (financial distress or financial crisis), auditor’s familiarity with their client or regulatory changes in the post-Sarbanes–Oxley Act of 2002 (SOX) era.

Building on the extant audit fee literature, this study constructs an audit fee determinants model to examine how context affects auditors’ pricing of managerial ability.

Auditors offer a larger fee discount to more able client management teams when auditors face lower litigation risks or are more familiar with the client. Furthermore, managerial ability has a more pronounced effect on audit fees in the post-SOX era when managers are mandated to play more active roles in financial reporting (i.e. certification of financial statements required by SOX 302).

Based on the audit risk model (Simunic, 1980), Krishnan and Wang (2015) show that the managerial ability of an audit client is relevant and important to auditors’ pricing decisions. This study demonstrates that managerial ability exhibits a non-linear relationship with audit fees and contextual factors, such as litigation risk, and that auditors’ familiarity with managers can alter the negative association between audit fees and managerial ability. This study extends Krishnan and Wang’s study by offering additional insights into auditors’ use of soft information such as managerial ability. Furthermore, the findings add to the literature on the impact of SOX on audit fees by suggesting that SOX has not only increased overall audit fees (Ghosh and Pawlewicz, 2009; Huang et al., 2009), it has also increased auditors’ price sensitivity to soft information (e.g. managerial ability).

This study provides insights for audit firms and client companies who are interested in understanding audit fee-pricing decisions. The findings also suggest that auditors need to be sensitive and responsive to various contextual factors when making pricing decisions.

Previous studies have not addressed the non-linear relationship between audit fees and soft information about managerial ability.

The emergence of social media as a corporate disclosure channel has caused significant changes in the production and dissemination of corporate information. This review identifies important themes in recent research on the impact of social media on the corporate information environment and provides suggestions for further explorations of this new but fast-growing area of research. Specifically, we first review the evolution of Internet-based corporate disclosure and related regulations, and then focus on three recent streams of research: 1) companies’ use of social media; 2) information produced by non-corporate users and its impact on capital markets; and 3) the credibility of corporate information on social media platforms.

The purpose of this study is to examine how auditors would react when there are exogenous negative shocks to their client portfolios.

Using a sample of 31,256 firm-year observations (2001–2016), the authors investigate whether industry shocks to a subset of an auditor’s clients distract the auditor and affect the professional skepticism applied in the audits of other clients.

The authors find that clients of distracted auditors are more likely to meet or beat analyst consensus forecasts, suggesting that auditors’ professional skepticism is compromised by distractive events. The cross-sectional analyses reveal that the negative impact of the distractive events on audit quality is more pronounced when the distracted auditors audit less important clients, face lower third-party legal liabilities and experience higher growth. Using an alternative measure of audit quality, the additional analysis shows that clients of distracted auditors exhibit a higher probability of restating their earnings in subsequent years. Overall, the empirical evidence suggests that when distracted, auditors render lower quality audit.

The study complements recent work by Cassell et al. (2019), which shows that the 2008–2009 financial crisis affected the quality of the audits of nonbank clients of bank-specialized auditors. While Cassell et al. (2019) focus on one shock (financial crisis) to one industry (i.e. the financial services industry), the study examines more frequent shocks over a wide range of industries to identify the potential effects of distractive events, improving the generalizability of the findings to all industries and all auditors (specialist and nonspecialist) in nonrecession periods.

The current difficulties of distribution network working robots are mainly in the performance and operation mode. On the one hand, high-altitude power operation tasks require high load-carrying capacity and dexterity of the robot; on the other hand, the fully autonomous mode is uncontrollable and the teleoperation mode has a high failure rate. Therefore, this study aims to design a distribution network operation robot named Sky-Worker to solve the above two problems.

The heterogeneous arms of Sky-Worker are driven by hydraulics and electric motors to solve the contradiction between high load-carrying capacity and high flexibility. A human–robot collaborative shared control architecture is built to realize real-time human intervention during autonomous operation, and control weights are dynamically assigned based on energy optimization.

Simulations and tests show that Sky-Worker has good dexterity while having a high load capacity. Based on Sky-Worker, multiuser tests and practical application experiments show that the designed shared-control mode effectively improves the success rate and efficiency of operations compared with other current operation modes.

The designed heterogeneous dual-arm distribution robot aims to better serve distribution line operation tasks.

For the first time, the integration of hydraulic and motor drives into a distribution network operation robot has achieved better overall performance. A human–robot cooperative shared control framework is proposed for remote live-line working robots, which provides better operation results than other current operation modes.

Constructing porous wind barriers is one of the most effective approaches to increase the running safety of trains on viaducts in crosswinds. This paper aims to further improve the wind-sheltering performance of the porous wind barriers.

Improved delayed detached eddy simulations based on the k-ω turbulence model were carried out, and the results were validated with wind tunnel tests. The effects of the hole diameter on the flow characteristics and wind-sheltering performance were studied by comparing the wind barriers with the porosity of 21.6% and the hole diameters of 60 mm–360 mm. The flow characteristics above the windward and leeward tracks were analyzed, and the wind-sheltering performance of the wind barriers was assessed using the wind speed reduction coefficients.

The hole diameters affected the jet behind the wind barriers and the recirculation region above the tracks. Below the top of the wind barriers, the time-averaged velocity first decreased and then increased with the increase in the hole diameter. The wind barrier with the hole diameter of 120 mm had the best wind-sheltering performance for the windward track, but such barrier might lead to overprotection on the leeward track. The wind-sheltering performance of the wind barriers with the hole diameters of 240 mm and 360 mm was significantly degraded, especially above the windward track.

The effects of the hole diameters on the wake and wind-sheltering performance of the wind barriers were studied, by which the theoretical basis is provided for a better design of the porous wind barrier.

The purpose of this study is to process the wettability surface of the ZrO₂ ceramics to improve their surface friction performance.

Microtexture was processed on the surface of ZrO₂ ceramics using a femtosecond laser. The three-dimensional texture morphology, surface contact angle, friction curve and wear morphology were measured by the laser confocal microscope, the contact angle meter, the reciprocating friction and wear tester and the scanning electron microscope, respectively. Based on Wenzel and partial impalement models, a geometric model of micro pits is established to study the influence mechanism of micro pit depth, diameter and distribution density on wettability and to analyze the relationship between surface wettability and tribological properties.

The results show that changing the geometric characteristics of the texture will lead to a change in the solid-liquid contact mode, and then lead to a change of in the surface contact angle. Wettability is an essential factor that affects the reduction of surface friction. The construction of a reasonable texture can enhance the surface hydrophilicity, which is conducive to the formation of a lubricating film on the ceramic surface, thereby reducing abrasive and adhesive wear, and improving the wear resistance of the ZrO₂ ceramic surface.

The results provide a theoretical reference for femtosecond laser surface texture wettability regulation and tribological performance improvement.

The purpose of this paper is to present a novel numerical approach to analyze the static performance of aerostatic thrust bearings by adopting a general finite element method calculation program.

The characteristics of a gas film are described by the Reynolds equation and the pressure distribution is solved using the finite element method. A root iterative method is proposed to meet the requirement of the mass-conservation law because multiple pocketed orifice-type restrictors are treated as a series of special boundary conditions.

The static performance of a rotary table using aerostatic thrust bearings, including load carrying capacity and stiffness, can be predicted by the method; moreover, it can be further confirmed through experiments on the designed rotary table.

The method combining the finite element and root iterative methods is highly accurate and has a low time-cost for analyzing aerostatic thrust bearings with multiple pocketed orifice-type restrictors.

The purpose of this paper is twofold: first, to present a bibliometric analysis and systematic literature review of industry convergence and value innovation to understand the current research status; second, to provide a coherent theoretical research framework for future research.

This study adopts a two-step analysis approach by combining bibliometric analysis and systematic literature review to explore the research topic of industry convergence and value innovation. Besides, two bibliometric tools, HistCite and VOSviewer, were applied to this study.

This study found that Stefanie Bröring and Fredrik Hacklin are the top two most influential authors among all authors in the sample publications. Technological Forecasting and Social Change is one of the top-ranking journal that often publishes this topic of articles. Germany and the University of Munster are the most influential country and institutions, respectively. Besides, five core research themes were identified based on keywords co-occurrence map, theoretical lenses, factors promoting industry convergence, indicators of industry convergence, the impact of industry convergence and emerging research directions. Based on the above analysis, this paper constructed a theoretical research framework of industry convergence and value innovation.

This paper only draw data from one database – Web of Science – which cannot provide broad coverage of the research topic. Besides, the bibliometric method of this paper is based on high local citation score and high-frequency words, articles in the skirting subjects’ area may not be analyzed.

With the rapid development of technology, such as nanotechnology, radio - frequency identification (RFID), etc., the iterative upgrading of products also comes. As a result, the boundary between industries is gradually blurred, and the phenomenon of industry convergence appears. Therefore, managerial decision-makers are facing challenges of how to respond to the convergence phenomena. From the firm level, firms are facing the problem of value innovation of the existing product, new product development and core competence improvement. Industries are facing the problem of transformation and upgrading. This paper provides certain theoretical insights for both firms and industries to guide the practice accordingly.

This paper is the first to use a bibliometric method to examine the topic of industry convergence and value innovation. In addition, this paper presents an in-depth analysis of this topic and provides a comprehensive theoretical research framework for future study.

The aerodynamic differences between the head car (HC) and tail car (TC) of a high-speed maglev train are significant, resulting in control difficulties and safety challenges in operation. The arch structure has a significant effect on the improvement of the aerodynamic lift of the HC and TC of the maglev train. Therefore, this study aims to investigate the effect of a streamlined arch structure on the aerodynamic performance of a 600 km/h maglev train.

Three typical streamlined arch structures for maglev trains are selected, i.e. single-arch, double-arch and triple-arch maglev trains. The vortex structure, pressure of train surface, boundary layer, slipstream and aerodynamic forces of the maglev trains with different arch structures are compared by adopting improved delayed detached eddy simulation numerical calculation method. The effects of the arch structures on the aerodynamic performance of the maglev train are analyzed.

The dynamic topological structure of the wake flow shows that a change in arch structure can reduce the vortex size in the wake region; the vortex size with double-arch and triple-arch maglev trains is reduced by 15.9% and 23%, respectively, compared with a single-arch maglev train. The peak slipstream decreases with an increase in arch structures; double-arch and triple-arch maglev trains reduce it by 8.89% and 16.67%, respectively, compared with a single-arch maglev train. The aerodynamic force indicates that arch structures improve the lift imbalance between the HC and TC of a maglev train; double-arch and triple-arch maglev trains improve it by 22.4% and 36.8%, respectively, compared to a single-arch maglev train.

This study compares the effects of a streamlined arch structure on a maglev train and its surrounding flow field. The results of the study provide data support for the design and safe operation of high-speed maglev trains.

Although phone calls are widely used by debt collection services to persuade delinquent customers to repay, few financial services studies have analyzed the unstructured voice and text data to investigate how debt collection call strategies drive customers to repay. Moreover, extant research opens the “black box” mainly through psychological theories without hard behavioral data of customers. The purpose of our study is to address this research gap.

The authors randomly sampled 3,204 debt collection calls from a large consumer finance company in East Asia. To rule out alternative explanations for the findings, such as consumers' previous experience of being persuaded by debt collectors or repeated calls, the authors selected calls made to delinquent customers who had not been delinquent before and were being called by the company for the first time. The authors transformed the unstructured voice and textual data into structured data through automatic speech recognition (ASR), voice mining, natural language processing (NLP) and machine learning analyses.

The findings revealed that (1) both moral appeal (carrot) and social warning (stick) strategies decrease repayment time because they arouse mainly happy emotion and fear emotion, respectively; (2) the legal warning (stick) strategy backfires because of decreasing the happy emotion and triggering the anger emotion, which impedes customers' compliance; and (3) in contrast to traditional wisdom, the combination of carrot and stick fails to decrease the repayment time.

The findings provide a valuable and systematic understanding of the effect of carrot strategies, stick strategies and the combinations of them on repayment time. This study is among the first to empirically analyze the effectiveness of carrot strategies, stick strategies and their joint strategies on repayment time through unstructured vocal and textual data analysis. What's more, the previous studies open the “black box” through psychological mechanism. The authors firstly elucidate a behavioral mechanism for why consumers behave differently under varying debt collection strategies by utilizing ASR, NLP and vocal emotion analyses.