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This study aims to take advantage of the unprecedented anti-corruption campaign launched in China in December 2012 and examine the effect of improved public governance on tunneling.

This study uses a sample of Shanghai and Shenzhen Stock Exchange listed companies from 2010 to 2014 and conduct regression analyses to investigate the effect of improved public governance attributed to the anti-corruption campaign on tunneling.

This study finds that the level of tunneling decreased significantly after the anti-corruption campaign, suggesting that increased public governance effectively curbs tunneling. Cross-sectional results show that this mitigating effect is more pronounced for non-SOE firms, especially non-SOE firms with political connections, firms audited by non-Big 8 auditors, firms with a large divergence between control rights and cash flow rights and firms located in areas with lower marketization.

This study highlights the importance of anti-corruption initiatives in improving public governance and in turn reducing tunneling. This study provides important implications for many other emerging economies to improve public governance.

This study contributes to the literature on the role of public governance in constraining corporate agency problems and advances the understanding of the economic consequences of China's anti-corruption campaign in the context of tunneling.

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

This article analyzes the implementation of anti-corruption reforms in Taiwan by two former presidents, Chen Shui-bian (2000-2008) and Ma Ying-jeou (2008-2016).

A three-tier research approach, including in-depth interviews, questionnaire survey, and descriptive and inferential analysis, is adopted. In addition to Chen and Ma, 11 senior anti-corruption officials who served under both presidents were interviewed by the author. The survey questions cover 12 factors which are later grouped into the five dimensions of ethical leadership, considerate leadership, delegating leadership, participatory leadership, and performance to illustrate the causal relationship between these dimensions and performance.

Ma’s personal ethics are distinct from Chen’s in kind but Ma’s overall leadership and performance outshine Chen’s in degree rather than in kind. While the gap of ethical leadership between two Taiwan presidents is significantly wider than other dimensions of leadership, the outcome of the national integrity is not proportionate to the ethical leadership gap. In other words, personal ethics are not automatically transformed into political will for enhancing anti-corruption effectiveness. Three popular forms of corruption, red envelopes (bribing), influence-peddling, and vote-buying are analyzed in the context of changing political culture through national leadership. Unfortunately, both Chen and Ma produce insignificant contributions based on public surveys.

Policy-makers and scholars can use these research findings to further explore how ethical leadership can enhance a country’s anti-corruption performance.

The purpose of this paper is to investigate the value relevance of Research and development (R&D) and free cash flow (FCF) in an efficient investment setup. Most importantly, this paper examines whether the value relevance of R&D and FCF is associated with life cycle stages. Furthermore, this paper reports whether the market response to R&D and FCF is different in competitive market as compared to the concentrated market.

The analysis is based on the Ohlson (1995) model for the determination of value relevance of earnings and book value. Capitalized R&D and FCF data comprising of the Chinese A-listed firms from the year 2008 to 2016 are selected for this study. Following Anthony and Ramesh (1992), the authors divided the firm life cycle into different stages. HHI index is used to measure the product market competition.

The main result shows that R&D and FCF are value relevant in Chinese A-listed firms. The impact of R&D and FCF on the value relevance of earnings and book value is also positive and significant. The findings of the effect of R&D and FCF on the value relevance of accounting information signify that the information content (R²=0.46) of the mature stage is higher than that of the growth and stagnant stage. The explanatory power measured by R² value for competitive industries (0.47) is much higher than the concentrated industries (0.33).

Despite taking into account all the possible available variables, there are few limitations of the study. This study only studies the effect of EPS, BPS, R&D and FCF on the value relevance of accounting information. Other determinant such as size, growth, leverage and firm age is ignored. Since the R&D expenditure is discretionary, therefore the findings cannot be generalized to all the sectors. A sector wise comparative study can be done in future, to understand the differences in the information contents of R&D and FCF. Also, the tax effect of R&D is ignored in this study. For future call, the value relevance of tax effect on R&D can be explored.

The investors can now determine the present value of all the future cash flows of investing activities. The results of the study are significant for the Chinese investors who should incorporate the R&D and FCF along with investment efficiency. The investors should keep in mind the life cycle stage while investing in a certain stock. The competitive markets have more information content than the concentrated markets. The corporate managers can benefit from this study while issuing new shares. The market responds positively to the stock having investment efficient R&D and FCF investment. For the policy implication perspective, the security market regulator should devise the effective pro-effective product market regulations.

The contribution of this study is manifold. First, according to the authors’ knowledge, this is the first study that incorporates investment efficiency with R&D and FCF and explores its effect on the value relevance of accounting information. Second, the impact of R&D on the value relevance is studied by numerous researchers (Lev and Sougiannis, 1996; Han and Manry, 2004). Similarly, FCF-agency cost effect has also been investigated by (Rahman and Mohd-Saleh, 2008; Chen et al., 2012) but the value relevance of R&D and FCF during different life cycle stages still needs to be answered. Finally, this study also tries to answers the question if the market response to R&D and FCF is different in a competitive market as compared to the concentrated market.

This paper aims to examine the effect of dividend regulation on cost stickiness (i.e. the asymmetric change in firm expense between sales increase and sales decrease) and explore the underlying mechanism.

Based on the quasi-natural experiment of the Guideline for Dividend Policy of Listed Companies issued by the Shanghai Stock Exchange (SSE) in 2013, the authors employ a difference-in-difference model to investigate the impact of dividend regulation on cost stickiness.

The authors find that the cost stickiness of treatment group firms has decreased significantly when compared with control group firms after the dividend regulation. Moreover, this effect is more pronounced among firms in lower marketization regions, in lower competition industries and those with less analyst coverage and lower cash flow levels. Further analyses show that dividend regulation reduces the cost stickiness of firms by mitigating agency problems. Finally, the conclusion holds after several robust tests, including controlling for firm fixed effect, propensity score matching (PSM), placebo test and reconstruction of expense variable.

This paper confirms that dividend regulation serves an important role in corporate governance, which reduces firms' agency costs and thereby decreases cost stickiness. The conclusions shed light on the dividend policies of listed companies and capital market regulation in the future.

Poor medication adherence leads to high hospital admission rate and heavy amount of health-care cost. To cope with this problem, various electronic pillboxes have been proposed to improve the medication adherence rate. However, most of the existing electronic pillboxes use time-based reminders which may often lead to ineffective reminding if the reminders are triggered at inopportune moments, e.g. user is sleeping or eating.

In this paper, the authors propose an AI-empowered context-aware smart pillbox system. The pillbox system collects real-time sensor data from a smart home environment and analyzes the user’s contextual information through a computational abstract argumentation-based activity classifier.

Based on user’s different contextual states, the smart pillbox will generate reminders at appropriate time and on appropriate devices.

This paper presents a novel context-aware smart pillbox system that uses argumentation-based activity recognition and reminder generation.

The purpose of this study is to sort out the potential dark sides of shared leadership so as to promote a more comprehensive and balanced views of the impact of shared leadership and provide directions for future research.

Through extensive database and manual searches, 766 literature records were obtained. After three rounds of literature screening, 17 studies were retained. On this basis, the 17 studies were coded and analyzed.

From the perspectives of individual motivation, hierarchical functionalism and leadership role configuration, the existing studies have explored the negative impacts of shared leadership on team members, formal team leaders and the overall work teams. Specifically, for team members, shared leadership may cause negative consequences like power struggle, role stress and knowledge hiding. For formal team leaders, shared leadership may cause negative consequences like psychological territorial loss, leadership motivation declines and the dualistic paradox of self and group. For the overall work teams, shared leadership may cause negative consequences like team performance inhibition, low decision-making efficiency, team responsibility dispersion and team creativity decline. Meanwhile, contextual factors play a key role in determining the effects of shared leadership.

Through a systematic review of the negative impact of shared leadership, this study responds to the research calls for exploring the dark sides of shared leadership, provides the academic community with a more comprehensive and balanced view of the impact of shared leadership and identifies several directions for future research.

The purpose of this paper is to examine the psychological influence that the presence of music has on consumers’ evaluations of the service environment. Specifically, it investigates how emotion regulation processes and the impact of emotions/mood are linked to consumers’ evaluation of service and product quality.

An exploratory study was conducted using industry professionals in order to garner insight about the value of music and its benefits in the service environment. A field experiment was then conducted to test hypotheses.

Industry professionals offer implicit theories about the value of music. Specifically, they propose that music can be used to help customers regulate emotions and improve mood, enhance the customer experience and help in attracting new consumer segments. Results from the field experiment found that those exposed to music were likely to improve mood, express more favorable evaluations of the service and product quality of the establishment, as well as exhibit stronger intentions to continue to patronize the establishment.

Using live music in the service environment can be beneficial to organizations by improving customers’ emotional/psychological status as well as their evaluation of the consumption experience.

This research contributes to the existing literature by demonstrating how emotion regulation processes and the impact of emotions/mood are linked to consumers’ evaluation of service and product quality. Also, support for mood congruency judgment is found. Participants in the field study who had been exposed to music indicated that they made efforts to improve their mood and subsequently had more favorable judgments of service and product quality.

The disability datasets are the datasets that contain the information of disabled populations. By analyzing these datasets, professionals who work with disabled populations can have a better understanding of the inherent characteristics of the disabled populations, so that working plans and policies, which can effectively help the disabled populations, can be made accordingly.

In this paper, the authors proposed a big data management and analytic approach for disability datasets.

By using a set of data mining algorithms, the proposed approach can provide the following services. The data management scheme in the approach can improve the quality of disability data by estimating miss attribute values and detecting anomaly and low-quality data instances. The data mining scheme in the approach can explore useful patterns which reflect the correlation, association and interactional between the disability data attributes. Experiments based on real-world dataset are conducted at the end to prove the effectiveness of the approach.

The proposed approach can enable data-driven decision-making for professionals who work with disabled populations.

The purpose of this paper is to propose a design of online-merge-offline (OMO) classroom for open education with design principles related to practical issues of teachers’ teaching, students’ learning and schools’ management.

Three stages were covered: drafted an OMO classroom framework, built a sample classroom and explored end-users’ experience. First, authors searched for and reviewed previous studies and related cases to draft an OMO framework. Second, a classroom, consisted of wireless devices, cloud-based services, Internet of Things terminals, ergonomics furniture, and comprehensive data management and analysis services, was built in Shanghai Open University. Third, invited 11 students’, 18 teachers’ and 9 school managers’ perspectives were collected and analysed by surveys and interviews.

All student participants responded positively in terms of learning experience in the classroom. They not only engaged in classroom activities such, but also accessed needed learning materials and interacted with teachers and peers anytime anywhere via mobile devices. Similarly, most teachers (90 per cent) made positive responses because of flexibility of teaching strategies and learning activities and expressed willingness to use the classroom in the future (94.4 per cent). In addition, more than 78 per cent of managers positively commented on the design of classroom, interaction effects and effective management. Visualised data allowed them to timely monitor status of facilities, comprehensively understand users’ behaviour and issues, make necessary decision with scientific evidence.

The framework and classroom not only provide teachers, students, school managers and researcher with a better understanding of innovative open education, but also indicate the key role of objective-oriented and data-driven issues for further work.

To meet needs of teachers, students, managers and researchers in today’s open education, an OMO classroom was built in Shanghai Open University based on the proposed Objective-Oriented Pedagogy-Space-Technology (OPST) framework. The framework provides readers (especially teachers and administrators of open-education institutes, staff of information centres and ed-tech researchers) with a better understanding of innovative instruction and effective management, and the originally designed classroom can be a practical and illuminating example.