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The purpose of this study is to examine whether corporate tax avoidance behavior increases firm value in Chinese context. A large number of studies conduct their designs on the consumption that tax avoidance represents wealth transfer from government to enterprises and therefore enhances firm value. This study argues that, contrast to developed countries, tax avoidance does not necessarily add value to opaque Chinese firms relative to transparent counterparts due to higher agency costs.

Using a large sample of Chinese listed-firms data for the period 2001-2009 and fixed effects regression model, this study examines the relation between tax avoidance and firm value. A series of robustness checks are conducted to alleviate the concern of endogeneity.

The authors find that tax avoidance behavior increases agency costs and reduces firm value. The authors further find that information transparency interacts with corporate tax avoidance, moderating the relation between tax avoidance and firm value. Investors in China react negatively to corporate tax avoidance behavior, but this negative reaction could be mitigated by information transparency. The results are robust to a series of alternative treatments, including varied measures, first-order differential approach and 2SLS.

The results suggest that tax avoidance does not necessarily increase firm value, part of gains are encroached by self-serving managers. Moreover, investors in China downplay the significance of tax avoidance, although corporate information transparency could soften their negative tone.

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 paper is to study enterprise innovation in the perspective of external supplier relationship. On this purpose, this paper examines the impact of supplier change on enterprise innovation with the moderating role of market competition.

Using 2012–2020 empirical data of Chinese listed manufacturing enterprises, this paper investigates the relationship among supplier change, market competition and enterprise innovation through a two-way interaction model.

The results show that supplier change has a negative impact on enterprise innovation. And market competition intensifies the negative relationship between supplier change and enterprise innovation. Additional analyses indicate that the main effect and the moderating effect are more significant when the enterprise is non-state-owned or has lower ownership concentration.

This paper studies enterprise innovation from the perspective of external stakeholders. It focuses on supplier relationship in a dynamic variation view, instead of the traditional static ones. Moreover, this paper explores the contingency effect of market competition and gives practical implications for managers to adjust innovation strategy flexibly.

This paper aims to demonstrate a cloud-based version of the improved Monte Carlo localization algorithm with robust orientation estimation (IMCLROE). The purpose of this system is to increase the accuracy and efficiency of indoor robot localization.

The cloud-based IMCLROE is constructed with a cloud–client architecture that distributes computation between servers and a client robot. The system operates in two phases: in the offline phase, two maps are built under the MapReduce framework. This framework allows parallel and even distribution of map information to a cloud database in pre-described formats. In the online phase, an Apache HBase is adopted to calculate a pose in-memory and promptly send the result to the client robot. To demonstrate the efficiency of the cloud-based IMCLROE, a two-step experiment is conducted: first, a mobile robot implemented with a non-cloud IMCLROE and a UDOO single-board computer is tested for its efficiency on pose-estimation accuracy. Then, a cloud-based IMCLROE is implemented on a cloud–client architecture to demonstrate its efficiency on both pose-estimation accuracy and computation ability.

For indoor localization, the cloud-based IMCLROE is much more effective in acquiring pose-estimation accuracy and relieving computation burden than the non-cloud system.

The cloud-based IMCLROE achieves efficiency of indoor localization by using three innovative strategies: firstly, with the help of orientation estimation and weight calculation (OEWC), the system can sort out the best orientation. Secondly, the system reduces computation burden with map pre-caching. Thirdly, the cloud–client architecture distributes computation between the servers and client robot. Finally, the similar energy region (SER) technique provides a high-possibility region to the system, allowing the client robot to locate itself in a short time.

The purpose of this paper is to investigate how to determine optimal investing stopping time in a stochastic environment, such as with stochastic returns, stochastic interest rate and stochastic expected growth rate.

Transformation method was used for solving optimal stopping problem by providing a way to transform path‐dependent problem into a path‐independent one. Based on option pricing theory, optimal investing stopping time was thought of as an optimal executed timing problem of American‐style option.

First, the authors transform a path‐dependent stop timing problem to a path‐independent one with transformation under very general conditions, to directly use the existing conclusion of optimal stopping time literature. Second, when dynamics of capital growth is homogeneous, the authors changed the two dimensional optimal stop timing problem into a single dimension problem based on the assumption of zero exercise costs. Third, the authors investigated the comparative dynamics about asset selling boundary on asset value, state variable and return predictability. With constant discount rate and growth rate, the optimal selling timing depends on the simple comparison between capital cost and growth rate.

The paper's contributions to analysis method may be as follows. The authors demonstrate how to transform a path‐dependent stopping problem into a path‐independent one under general conditions. The transform method in this article can be applied to other path‐dependent optimal stopping problems. In particular, a Riccati ordinary differential equation for the transformation is set up. In most examples commonly met in finance, the equation can be solved explicitly.

The paper aims to study realization requirements for the flexible enactment of artifact-centric business processes in a dynamic, collaborative environment and to develop a workflow execution framework that can effectively address those requirements.

This study proposed a framework and contract-based, event-driven architecture design and implementation that can directly realize collaborative artifact-centric business processes in service-oriented architecture (SOA) without any model conversion.

The results show that the approach is feasible in presenting several key benefits over the use of existing workflow systems to run artifact-centric processes.

Most of the existing approaches require an artifact-centric model to be transformed into executable workflow languages to run on existing workflow management systems. This study argues that the model conversion can incur losses of information and affect traceability and monitoring ability of workflows, especially in an SOA where a workflow can span across multiple inter-business entities.

This study examines corporate governance and ethics (CGE) education by conducting a survey of academicians and practitioners in the United States. Results indicate that the demand for, and interest in, CGE continues to increase. More universities are planning to provide CGE education and many CGE topics are considered important for integration into the curriculum, although the degree of importance varies between academicians and practitioners. The two prevailing methods of CGE education integration are offering a stand-alone course in CGE or infusion of CGE topics into accounting courses. Results pertaining to the importance, delivery, and topical content of CGE education may be useful to universities that are, or are considering, integrating CGE into their curricula or redesigning their CGE courses. The CGE educational issues addressed in this study should help business schools design curricula to prepare students for the challenges awaiting them in the area of CGE.

This study aims to examine the effect of the COVID-19 pandemic in comparison to the global financial crisis (GFC) on the gross domestic product (GDP) growth rate of China.

Empirical analyses are conducted through alternative methods such as ordinary least squares, Markov regime switching (MRS) and mixed data sampling (MIDAS) regressions. The flexibility of MIDAS regression enables us to use different variables with quarterly (GDP), monthly (export sales and foreign-exchange reserves) and daily frequencies (foreign exchange rates and Brent oil price).

The results indicate that the COVID-19 pandemic has had a considerable negative effect on China’s GDP growth, while the dummy variables used for the GFC are found to be insignificant. Further, the forecast accuracy test statistics exhibited a superior performance from MIDAS regression compared to the alternative models, such as MRS regression analysis. According to the forecast results, the authors expect a recovery in China’s economic growth in the second quarter of 2020.

This is one of the earliest studies to examine the effect of the COVID-19 pandemic on the Chinese economy, and to compare the impact of COVID-19 with the GFC. The authors provide further evidence regarding the performance of MIDAS regression analysis vs alternative methods. Findings obtained shed light on policymakers, corporations and households to update their consumption, saving and investment decisions in the chaotic environment of this pandemic.

The escalating volume of electronic waste (e-waste) presents a significant environmental and health hazard, emphasizing the importance of promoting e-waste recycling. Therefore, this study aims to utilize a valence theory approach to comprehensively understand the factors influencing individuals' intention to recycle e-waste.

A survey-based research approach was employed to examine the factors influencing consumers' e-waste recycling intention. Data were collected through an online survey questionnaire from Malaysian individuals aged 18 and above. The hypotheses were tested using a sample of 300 respondents, employing partial least squares structural equation modeling as a symmetric analysis technique. Additionally, fuzzy-set Qualitative Comparative Analysis (fsQCA), an asymmetric analysis approach, was used to gain deeper insights. Non-probability purposive sampling was utilized in the sampling process.

The PLS-SEM analysis revealed that subjective norms and willingness to change significantly impact e-waste recycling intention. Furthermore, perceived convenience, environmental concerns and social media usage were found to support the intention to recycle e-waste. The fsQCA results enhanced the interpretation by uncovering intricate relationships among the antecedents and identifying specific configurations that accurately predict consumers' recycling intentions.

The practical implications of this study emphasize the need for policymakers and practitioners to raise awareness regarding the benefits of e-waste recycling, enhance convenience in the recycling process and strengthen personal and subjective norms to encourage individuals to recycle their e-waste.

This study's originality lies in its adoption of a valence theory framework to comprehend the intentions behind e-waste recycling, as well as its inclusion of control variables during the analysis. This unique approach enhances the understanding of factors influencing e-waste recycling intention and provides valuable insights for policymakers and practitioners in developing effective strategies to promote e-waste recycling behavior.

Despite concerns about the effect of internet addiction, little is known about how psychological suzhi impacts the internet addiction of college students. This paper aims to investigate the relationship between psychological suzhi and internet addiction among college students.

Using the college student psychological suzhi scale and internet addiction test, 2,070 college students from 11 universities in North China, East China, South China and Southwest China were tested.

The detection rate of internet addiction in this college sample of students was 18.8%. There was a significant negative correlation between students’ psychological suzhi and internet addiction (r = −0.408, p < 0.01). Hierarchical regression analysis showed that adaptability and individuality in psychological suzhi significantly negatively predicted college students’ internet addiction tendency (p < 0.001).

This study is the first to show a relationship between psychological suzhi and internet addiction in college students. In detail, the adaptability and individuality of college students’ psychological suzhi are protective factors related to internet addiction. The results also suggested that the authors can prevent and intervene in internet addiction by modifying college students’ adaptability and individuality.