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Using a sample of 9,898 firm-year observations from 1,821 unique Chinese listed firms over the period from 2004 to 2019, this study aims to investigate whether the market rewards meeting or beating analyst earnings expectations (MBE).

The authors use an event study methodology to capture market reactions to MBE.

The authors document a stock return premium for beating analyst forecasts by a wide margin. However, there is no stock return premium for firms that meet or just beat analyst forecasts, suggesting that the market is skeptical of earnings management by these firms. This market underreaction is more pronounced for firms with weak external monitoring. Further analysis shows that meeting or just beating analyst forecasts is indicative of superior future financial performance. The authors do not find firms using earnings management to meet or just beat analyst forecasts.

The authors provide evidence of market underreaction to meeting or just beating analyst forecasts, with the market's over-skepticism of earnings management being a plausible mechanism for this phenomenon.

The findings of this study are informative to researchers, market participants and regulators concerned about the impact of analysts and earnings management and interested in detecting and constraining managers' earnings management.

The authors provide new insights into how the market reacts to MBE by showing that the market appears to focus on using meeting or just beating analyst forecasts as an indicator of earnings management, while it does not detect managed MBE. Meeting or just beating analyst forecasts is commonly used as a proxy for earnings management in the literature. However, the findings suggest that it is a noisy proxy for earnings management.

This chapter examines the impacts of scheduled announcements of 14 widely followed macroeconomic news on the corporate bond market from July 2002 to June 2017 and documents several new findings. First, good (bad) macroeconomic news tends to have a negative (positive) effect on IG bond returns and a positive (negative) effect on high-yield (HY) bond returns. Second, nonfarm payroll (NFP) appears to be the “King of announcements” for the corporate bond market. Third, while information about revisions of prior releases is incorporated into bond prices on announcement days, future revisions fail to be priced in. Fourth, the news information is thoroughly and quickly reflected in bond prices on the announcement day. Finally, corporate bond volatility increases on announcement days, whereas the Zero Lower Bound (ZLB) policy has little effect on conditional volatility.

This paper aims to investigate the correlation between banking sector non-performing loans (NPLs) and the level of sustainable development.

Pearson correlation test statistic was used to assess the correlation between bank NPLs and sustainable development.

There is a significant positive correlation between banking sector NPLs and the level of sustainable development measured by the sustainable development index (SDI). The significant positive correlation is evident in European countries and in countries in the region of the Americas. There is a significant negative correlation between banking sector NPLs and achieving SDG3 and SDG7 in African countries and European countries. There is also a significant negative correlation between NPLs and achieving SDG10 in European countries. There is a significant positive correlation between banking sector NPLs and achieving SDG4 and SDG7 in the region of the Americas. There is also a significant positive correlation between NPLs and achieving SDG10 in African countries and in countries in the region of the Americas.

The present study is unique and different from other studies because it used a unique SDI to capture the level of sustainable development. The analysis is also unique because it covers several regions, which have not been covered in previous studies.

There has been limited research that has explored the connection between digital supply chain (DSC) and SC innovation and SC dynamic capabilities. This paper aims to examine the mediating effect of SC innovation on the relationship between DSC and SC dynamic capabilities.

The research model and hypotheses were tested, employing (Statistical Package of Social Sciences) SPSS 25.0 and (Analysis of Moment Structures) AMOS 24.0 on data drawn from the Chinese manufacturing enterprises.

The study reveals that DSC has a significant positive effect on SC innovation and SC dynamic capabilities. SC innovation also has a significant positive effect on SC dynamic capabilities. Besides, the authors' research illustrates that SC innovation partially mediates the relationship between DSC and SC dynamic capabilities.

Since the results are derived from the data collected from China, it may not, therefore, be generalized to other settings. Moreover, future research could consider other contextual variables such as “environmental uncertainty” and “Government's Reward-Penalty Mechanism,” which may influence SC dynamic capabilities.

The study provides practical insights for senior executives and managers in the manufacturing industry. Managers should emphasize the investment of advanced digital technologies and tools (DTTs) and improvement of SC visibility and collaboration. In the digital age, companies should pay attention to the introduction of advanced technologies, tools and processes and focus on cultivating an innovative spirit to promote SC dynamic capabilities, thereby enhancing competitive advantages.

The paper illustrates that DSC is of great significance to improving SC dynamic capabilities. This study reveals compelling insights for firms to enhance SC innovation and dynamic capabilities by using DSC as an enabler.

The purpose of the study is to shed light on how to implement Industry 4.0 effectively across companies in buyer–supplier relationships.

The study follows an exploratory research design and analyzes qualitative empirical data of eight case companies from the German automotive industry. The data are inductively categorized to uncover patterns and structures in a qualitative content analysis, whereupon a deeper data structure is developed.

The research reveals that a comprehensive implementation approach is required to pave the way for digitalized and interconnected supply chains. Several challenges occur during the implementation, such as system heterogeneity and resource scarcity. Prerequisites and fundamentals for a successful implementation include a vision and strategy, management involvement, and sufficient resources. Lastly, indications on how to conduct the implementations were found.

The study is based on an exploratory methodology, analyzing data from the German automotive industry. The methodology entails some limitations, and caution must be given when transferring the results to different industries and national contexts. Future studies could complement the findings by studying different contexts and including further supply chain levels.

Managers and practitioners can study the recurring themes in the implementation approaches and the best practices and subsequently learn from the experiences. This knowledge could aid to shape the strategy of companies accordingly.

The study empirically sheds light on the Industry 4.0 implementation approach across companies in buyer–supplier relationships and helps to understand the success factors and underlying mechanisms.

This paper aims to empirically investigate the evidence of the transmission of monetary policy impulses to firm profitability via manufacturing firms’ short-term and long-term corporate financing decisions.

This study decomposes the receptiveness of firm profitability to monetary policy shock under circumstances of financial flexibility. Additionally, the study extends its scope to undertake a sector-wise analysis of manufacturing firms from 2008 to 2020. Generalized methods of moments (GMM) and quantile regression models are employed.

The profitability of firms in the chemical, food and machinery sector are positively impacted by short-term financing, whereas the metal sector is positively impacted. But during the tight monetary policy, short-term financing does not appear to be a significant parameter while explaining the firms’ profitability. Secondly, the profitability of firms in the consumer goods and metal sector is positively impacted by long-term financing. Therefore, debt financing of assets could be more appropriate to maximize profitability in these sectors.

Analyzing the transmission of monetary policy impulses to firm profitability by clustering firms with financial flexibility across six key manufacturing sectors makes the study unique.

Building information modelling (BIM), lean construction (LC) and prefabricated housing construction (PHC) have individually aroused great attention from academia and industry. However, the integration of LC and BIM in PHC projects has not been sufficiently explored. This study aims to assess the current status of the implementation of BIM and LC in China’s PHC sector given, firstly, that China is a developing country characterised by the world’s largest population and a huge housing market, and secondly, that although China’s PHC is strongly supported by the government, the adoption of BIM and LC in PHC varies.

A mixed approach (questionnaire survey and interviews) is adopted in this study. A total of 127 valid questionnaires were collected. This is followed by interviewing 12 interviewees who are key stakeholders in PHC and hold managerial positions.

The findings of the questionnaire survey show that BIM is more prevalent than LC in PHC projects in China. In addition, the adoption of LC exhibits more maturity in stages associated with production and manufacturing, and logistics and transportation, whereas BIM has seen wider adoption in design and construction. The interviews validated the factors that influence the implementation of BIM and LC in PHC projects in China.

The study uses a strengths, weaknesses, opportunities and threats analysis framework to clarify the opportunities, threats, strengths and weaknesses of BIM and LC in China’s PHC and proposes strategies.

This study investigates the enablers and challenges of digital supply chains (DSCs) adoption and develops a digital supply chain maturity (DSCM) model as a basis for developing guidelines for DSC adoption in the digital transformation journey.

The research involves a systematic literature review (SLR) of Industry 4.0 (I4) adoption in supply chain (SC) practices to identify key enablers and associated maturity levels. The literature search of published articles during the 1997–2020 period and subsequent screening resulted in 64 articles. A DSCM model was developed using the categorization of important enablers and associated levels transitioning from the traditional SC to the DSC ecosystem.

Four broader categories of DSC enablers and challenges were identified from the content analysis of SLR. Digital strategy alongside I4 technologies and human capital were prominent in DSC adoption as I4 technologies and human capital depend on other enablers such as dynamic capabilities (DCs). Lack of infrastructure and financial constraints to implementing I4 were significant challenges in the DSC adoption.

The proposed DSCM model provides a holistic view of enablers and maturity levels from traditional SC to DSC adoption. However, the DSCM model needs to be empirically validated and streamlined further using inputs from practitioners.

The proposed DSCM model can be used as a framework to guide practitioners in assessing maturity and developing implementation plans for successful DSC adoption.

This research introduces a novel DSC maturity model through a holistic view of enablers and maturity levels from traditional SC to DSC adoption.

This paper aims to use redundant manipulators to solve the challenge of collision avoidance in construction operations such as welding and painting.

In this paper, a null-space-based task-priority adjustment approach is developed to avoid collisions. The method establishes the relative position of the obstacle and the robot arm by defining the “link space,” and then the priority of the collision avoidance task and the end-effector task is adjusted according to the relative position by introducing the null space task conversion factors.

Numerical simulations demonstrate that the proposed method can realize collision-free maneuvers for redundant manipulators and guarantee the tracking precision of the end-effector task. The experimental results show that the method can avoid dynamic obstacles in redundant manipulator welding tasks.

A new formula for task priority adjustment for collision avoidance of redundant manipulators is proposed, and the original task tracking accuracy is guaranteed under the premise of safety.