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This study aims to empirically examine the effect of supply chain innovation (SCI) announcements on shareholder value within the context of Industry 4.0 and Industry 5.0.

This study uses an event study method to examine the effect of SCI announcements on shareholder value of the 156 listed companies in China.

First, SCI announcements have a positive effect on shareholder value. Second, SCI with an integrated form more positively affects shareholder value than SCI with an independent form. SCI at the strategy level more positively affects shareholder value than SCI at the operation level. Technology-type SCI more positively affects shareholder value than process-type SCI. Third, this study finds that investors pay more attention to the SCI of companies in the service industry than that of in the manufacturing industry. Finally, the post-hoc analysis finds that digital SCI more positively affects shareholder value than intelligent SCI.

First, most scholars use questionnaire data rather than second-hand data to conduct empirical research to explore the impact of SCI on performance. Second, although scholars focus on performance comprehensively, including operational, financial, relational and environmental performance, no scholars use an event study to explore the impact of SCI on the stock market. Third, no scholars have explored the differential impact of SCI in different industries. Forth, few scholars have classified SCI according to the characteristics to explore the differential impact of SCI. Finally, the differences between SCI of Industry 4.0 and SCI of Industry 5.0 have been described, but no scholars have used empirical research to explore the differences.

The purpose of this paper is to analyze the influencing factors of new logistics service product design (NLSPD) in China to establish a theoretical framework for the future development of the logistics industry.

The paper adopts the multi-case study method based on a sample of four Chinese logistics enterprises, in which the authors consider the logistics service maturity (LSM), a distinct characteristic of logistics enterprises.

NLSPD is directly related to the degree of supply–demand matching (SDM) and LSM. Customer demand, service capability and peer competition influence the performance of NLSPD through the SDM degree, whereas LSM moderates these influencing mechanisms. Moreover, the degree of SDM has a positive impact on LSM.

The findings can help the managers of logistics enterprises and practitioners in the logistics industry understand the complexity of NLSPD. First, they should broaden and deepen their service offering to enhance the degree of LSM. Second, they should pay attention to the factors that affect SDM systematically. Finally, it is vital to balance the relationship between LSM and SDM.

NLSPD has become an important tool affecting the competitiveness and sustainability of logistics service enterprises. This is the first paper to propose a theoretical framework for NLSPD that considers the characteristic of the logistics industry. It clarifies the mechanisms of influencing factors, and contributes to the literature by filling the research gap.

The literature review aims to facilitate a broader understanding of on-demand service platform operations management and proposes potential research directions for scholars.

This study searches four databases for relevant literature on on-demand service platform operations management and selects 72 papers for this review. According to the research context, the literature can be divided into research on “a single platform” and research on “multiple platforms”. According to the research methods, the literature can be classified into “Mathematical Models”, “Empirical Studies”, “Multiple Methods” and “Literature Review”. Through comparative analysis, we identify research gaps and propose five future research agendas.

This paper proposes five research agendas for future research on on-demand service platform operations management. First, research can be done to combine classic research problems in the field of operations management with platform characteristics. Second, both the dynamic and steady-state issues of on-demand service platforms can be further explored. Third, research employing mathematical models and empirical analysis simultaneously can be more fruitful. Fourth, more research efforts on the various interactions among two or more platforms can be pursued. Last but not least, it is worthwhile to examine new models and paths that have emerged during the latest development of the platform economy.

Through categorizing the literature into two research contexts as well as classifying it according to four research methods, this article clearly shows the research progresses made so far in on-demand service platform operations management and provides future research directions.

The assessment of fuel tank flammability exposure time for transport aircraft is one of the indispensable links in the airworthiness certification process. According to published literature, many factors can affect the flammability exposure time, while systematic analysis and calculations addressing these factors are in shortage.

Based on the requirements for airworthiness certification of domestic large aircraft, the fuel tank flammability exposure time of transport aircraft is calculated with the Monte Carlo evaluation model specified by Federal Aviation Administration. Meanwhile, the influence of each input parameter on the flammability exposure time is obtained by taking user input parameters in the model as independent variables and freezing other factors at the same time. The significance degree of the influence of each factor is discussed by the orthogonal test method. Subsequently, the interaction between the input parameters is studied by response surface method, and a multiple linear regression method is used to establish the functional relationship between the flammability exposure time and the influence parameters.

Research studies show that among the many factors that affect the flammability exposure time, the cruising Mach number, the equilibrium temperature difference and the maximum range are more significant and much attention should be paid to in the airworthiness certification; although there are interactions among various factors, they have different influence on the flammability exposure time, among which the interactions between maximum range and equilibrium temperature difference are the most significant compared with others; established by applying multiple linear regression equation and based on the test data of response surface method, the functional relationship between flammability exposure time and influence parameters is of sufficient reliability and can be used for preliminary prediction of fuel tank flammability exposure time for transport aircraft.

The research achievements of this paper can provide much useful reference for the certification of domestic large aircraft.

This study explores the influencing factors of smart logistics ecological chain's (SLEC's) organizational collaboration and designs a corresponding conceptual framework.

The multi-case study is applied to this paper. Specifically, this study is a combination of exploratory and explanatory case studies.

The findings are threefold. First, empowerment capability and the information-sharing level are unique factors that affect SLEC's organizational collaboration. Second, greater empowerment capability stimulates the increase of information-sharing level. Third, emerging digital technology, personalized demand and peer competition affect the degree of SLEC's organizational collaboration through an intermediary variable – empowerment capability. Specifically, the emerging digital technology application and peer competition degrees have positive effects on empowerment capability, while the demand personalization degree negatively (positively) affects empowerment capability in the short (long) term.

As an important part of supply chain performance, organizational collaboration is receiving more attention. However, in the smart economy context, no theoretical framework exists for analyzing factors that affect the organizational collaboration degree of SLEC. This study fills this gap.

This study aims to explore the impact of blockchain announcements on enterprises' stock market value.

Based on resource-based theory, this study constructs a complete framework of the impact mechanism of blockchain announcements on the stock price of the announcing firm using the data of 143 blockchain announcements. An event study methodology is used in this research, and the market model, market-adjusted model and Carhart four-factor model are used to estimate stock abnormal returns after the blockchain announcement; and the cross-sectional regression model is used to test the influencing factors.

Blockchain announcements elicit a significantly positive market reaction on the release day. Compared to announcements not pertaining to technical innovation, blockchain technical innovation announcements exhibit a more positive market reaction towards the announcing companies. Strategic-level announcements exhibit a more positive market reaction than operational-level announcements. Enterprise characteristics, such as enterprise-scale and enterprise innovation ability, do not affect stock market reactions to blockchain announcements.

The findings reveal the economic value of conducting blockchain activities in the Chinese stock market. Findings of this study can help managers understand the value of implementing blockchain activities in a different market environment and guide them on how to improve the market value of their enterprises through the active implementation of blockchain activities.

To the best of the authors’ knowledge, this is the first event study to focus solely on the value of pure blockchain announcements in an emerging market. This study considers multiple resource and capability factors that would influence blockchain technology adoption, improve the current understanding of how blockchain announcements affect corporate stock prices and provide directions for future comparative studies of market reactions to blockchain announcements in different stock markets.

The purpose of this study is to establish a method for accurately extracting torch and seam features. This will improve the quality of narrow gap welding. An adaptive deflection correction system based on passive light vision sensors was designed using the Halcon software from MVtec Germany as a platform.

This paper proposes an adaptive correction system for welding guns and seams divided into image calibration and feature extraction. In the image calibration method, the field of view distortion because of the position of the camera is resolved using image calibration techniques. In the feature extraction method, clear features of the weld gun and weld seam are accurately extracted after processing using algorithms such as impact filtering, subpixel (XLD), Gaussian Laplacian and sense region for the weld gun and weld seam. The gun and weld seam centers are accurately fitted using least squares. After calculating the deviation values, the error values are monitored, and error correction is achieved by programmable logic controller (PLC) control. Finally, experimental verification and analysis of the tracking errors are carried out.

The results show that the system achieves great results in dealing with camera aberrations. Weld gun features can be effectively and accurately identified. The difference between a scratch and a weld is effectively distinguished. The system accurately detects the center features of the torch and weld and controls the correction error to within 0.3mm.

An adaptive correction system based on a passive light vision sensor is designed which corrects the field-of-view distortion caused by the camera’s position deviation. Differences in features between scratches and welds are distinguished, and image features are effectively extracted. The final system weld error is controlled to 0.3 mm.

This study empirically examines the impact of announcements on supply chain strategic collaboration (SCSC) on companies' shareholder value.

This study analyzes changes in shareholder value of companies listed in China based on data of 208 SCSC announcements. The signaling theory is applied to determine correlation among SCSC announcements and the market. An event study is used to estimate the stock market reaction to SCSC announcements. The common market model estimates stock abnormal returns after the event. The least squares method and regression model calculate the model parameter value.

There is a positive and statistically significant relationship between SCSC announcement and shareholder value. Market reaction to product development collaboration is significantly higher than to technology-sharing collaboration, market collaboration, and other SCSC types. The market reacts more positively to suppliers and companies with greater supply chain control power than to buyers and companies with lower control power. Announcements from the service supply chain can lead to stronger market reactions than those from manufacturing supply chains.

The findings provide a systematic assessment of how SCSC announcements contribute to firms' shareholder value. The result provides a benchmark of value promotion that can be expected from SCSC announcements.

This study fills the research gap that using secondary data to assess changes in companies’ shareholder value caused by SCSC announcements and firstly examines these changes by constructing the signaler–signal–receiver progress based on signaling theory. The research results provide a new reference and inspiration for deeper understanding of the impact mechanism of SCSC. Furthermore, this study contributes to the development of the signaling theory using an empirical study in an emerging market, China.

This study explores the influencing factors affecting smart supply chain innovation (SSCI) performance of commodity distribution enterprises, and proposes the corresponding framework from the perspective of the application of technology to improve the SSCI performance and make up the research gap in this field.

A multi-case study method is adopted in this study. Four distribution commodity distribution enterprises A, B, C and D in China are chosen as case enterprises. The interviews with senior management team members are used to collect data. The combination of open coding and axial coding are used to process the data. By testing the reliability and validity, the theoretical framework is summarized.

First, we find that the technology application cost inhibits SSCI and that the level of technology suitable for enterprise development will promote SSCI. Second, SSCI in structure, management and services can improve the performance and innovation ability of enterprises. Third, the quality of multi-channel integration and degree of customization around customer demand can significantly modify the above effects.

Compared with previous studies, this study reveals for the first time the correlation between the SSCI performance and technology application, SSCI in structure, management and service, providing new ideas for relevant researches on SSCI, and providing new theoretical support for managers' decision-making related to SSCI.