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Servitization of products is becoming increasingly prevalent among manufacturing enterprises. Existing research has primarily focused on exploring whether the direct impact of servitization on manufacturer performance follows a linear or a curvilinear relationship. However, the understanding of the underlying mechanisms between servitization and manufacturer financial performance remains limited. This paper aims to examine the non-linear relationship between servitization and manufacturer performance as well as the mediating process and boundary condition associated with this relationship.

Drawing on resource-advantage theory, this paper proposes a theoretical model of the U-shaped relationship between servitization and the financial performance of equipment manufacturers. Panel data of 248 listed equipment manufacturers in China during the period of 2010–2020 are used to test each hypothesis through the ordinary least square method.

The empirical results indicate that servitization follows a U-shaped relationship with service business focus and the financial performance of equipment manufacturers. Service business focus mediates this U-shaped relationship between servitization and financial performance, and digital technology application moderates this relationship.

This paper pioneers the unraveling of the potential mechanism that can explain the curvilinear relationship between servitization of manufacturers and financial performance. This mechanism is the focus of the service business, which is theoretically delineated and empirically tested. Furthermore, digital technology application enables manufacturers to achieve service business focus more effectively in the process of servitization. Thus, this study addresses the call for research on digital servitization.

This study aims to investigate the impact of supply chain concentration (SCC) on corporate research and development (R&D) investment and determine the moderating roles of industry concentration and financing constraints on the relationship between SCC and R&D investment.

The study collected data from Chinese listed companies, used the fixed effects model to test the research hypotheses and further used the two-stage Heckman test and propensity score matching (PSM) to address potential endogeneity issues.

The result reveals a negative impact of SCC on corporate R&D investment. In addition, industry concentration mitigates the negative impact of SCC on corporate R&D investment, but financing constraints strengthen the negative impact.

This study introduces the concept of SCC and empirically tests its effect on R&D investment, further explaining the lack of corporate innovation. This study inspires companies to strengthen SC management and weigh the level of SCC with environmental factors.

Prior research has produced conflicting results on the relationship between firm-level patenting activity and financial performance. To identify a factor that impacts the results, this study tests whether the level of customer-base concentration (defined as focusing on a small number of major customer sales transactions) changes the relationship between firm-level patenting activity and financial performance (return on assets: ROA).

Using a longitudinal secondary dataset from Japanese manufacturers from 1991 to 2016, this study investigates the interaction effect between firm-level patenting activity and customer-base concentration. With additional analysis using multiple profitability measures, this study provides robust evidence that customer-base concentration is an important factor in changing the relationship between firm-level patenting activity and financial performance.

The analysis results show that there is a positive relationship between firm-level patenting activity and ROA. In addition, this relationship is positively moderated by the customer-base concentration. This means that suppliers can improve the performance of the patenting activity by concentrating on their customer base.

By identifying a moderating factor between patenting activity and financial performance, this study advances the interpretation of conflicting results in patent research. Moreover, this study reveals a situation where customer-base concentration, which has a direct negative impact on financial performance, leads to better financial performance. This also indicates that firm-level patenting activities may compensate for the negative aspects of customer-base concentration.

Digital inclusive finance has a positive promotion effect on the development of the national economy, but little research exists on how digital inclusive finance affects high-quality consumption in economically developed regions. Therefore, to fill the gap, this paper aims to study the impact of digital inclusive finance on high-quality consumption development using the economically developed regions of Jiangsu, Zhejiang and Shanghai as examples.

Firstly, the entropy method is used to construct the index of high-quality consumption among residents. Then, the municipal-level data of Jiangsu, Zhejiang and Shanghai from 2011 to 2020 are used to test the impact. Subsequently, the mechanism of action test and heterogeneity analysis are conducted.

The results show that digital inclusive finance has a positive role in promoting the high-quality consumption of residents in Jiangsu, Zhejiang and Shanghai. At the same time, digital inclusive finance can promote high-quality consumption through its own digital payment and internet insurance channels. There is regional heterogeneity in the impact.

To the best of the authors’ knowledge, this study is the first to examine whether and how digital inclusive finance affects high-quality consumption. The authors consider multiple dimensions, such as consumption level, consumption structure, consumption ability, consumption environment and consumption mode, to measure high-quality consumption. The findings provide valuable insights for policymakers, investors and regulators in planning regulations.

Drawing on the reasoned action theory, this study aims to examine the impact of environmental knowledge (EK) and environmental sustainability performance (EP) on environmental behavior (EB) mediated by environmental attitude (ATT). Furthermore, to examine the moderating effect of environmental advertising (ADD) on the indirect relationship between EP and EB, mediated by ATT on the one hand, and EK on EB, on the other hand, mediated by ATT.

The data were gathered within an international context for passengers from North African countries (NAC) (Egypt, Algeria, Tunisia, Libya, Morocco and Sudan) using primary quantitative data from online and self-administered questionnaires. A total of 1,052 questionnaires were collected from passengers who traveled through Egyptian airports. The collected data were analyzed through covariance-based structural equation modeling.

The findings indicated that ATT moderates the relationship between environmental knowledge and behavior. In addition, ATT mediates the airports' environmental behavior and environmental sustainability performance. Moreover, ADD moderates the indirect association between EP and individuals' environmental knowledge and behavior through the mediated effect of ATT.

This research output will help extend the theory’s scope by conceptualizing its abstract ideas using research variables and applying them in NAC countries. This can be a milestone for altering individuals' behavior toward the environment in airports.

This study aims to assist airport authorities in the development of standards for enhancing environmental performance. Enhancing environmental issues is of utmost importance, especially in the context of airports, which have been a subject of significant environmental concern. This study examined the environmental practices of airport passengers in NAC, given their significant role as the primary source of greenhouse gas emissions on the African continent. The present approach has the potential to be utilized in modifying airport conduct and enhancing stakeholder engagement, specifically within the context of NAC.

The objective of this study is to enhance the relationship between nature and humans by endeavoring to modify human attitudes toward the environment. The objective of this initiative is to bridge the current disparity in the socio-environmental connection by fostering environmental consciousness among individuals who utilize airport facilities. The objective will be accomplished by the construction of a theoretical framework that integrates crucial elements acknowledged for their substantial influence on altering human attitudes, thus fostering a greater sense of environmental consciousness and ultimately improving societal well-being.

Since the global supply chain prioritizes environmental transportation systems, this study provides a conceptual framework for airport authorities to develop and create policies to push air passengers' behavior toward environmental practices in NAC.

This study provide an in-depth review on the knowledge structure of green information technology (GIT) adoption and behavior. Environmental degradation has escalated even further with information and digital technology development. Researchers have come up with a new concept of GIT to dampen the carbon emission due to the excessive use of IT in today’s everyday usage. A similar terminology, green information system (GIS), is a rather broad understanding of GIT, which relates to the environmental management system to improve operations in the organization and will be included in the scope of the study.

This study presents a science mapping analysis through a bibliometric review to explore emerging trends and predict future trends based on 293 publications in the Web of Science.

The bibliographic coupling analysis discovered five themes related to the theoretical foundation of GIT and the determinants of their adoption. The five themes are (1) theoretical foundation in GIT, (2) determinants of green IT and IS adoption, (3) fundamental of GIT and information science, (4) green technologies and green computing and (5) determinants of managers green IT adoption behavior. While co-word analysis presents the impact of GIT, driving performance and energy efficiency through the adoption of GIT producing four themes, (1) GIT acceptance through the theory of planned behavior, (2) impact of GIT’s: strategies for sustainable implementation, (3) driving sustainable performance through green innovation in information systems and technology and (4) energy efficiency and sustainability in green computing and cloud computing.

The finding is relevant to managers, researchers and stakeholders bounded by environmental responsibilities to mitigate its impact on the socioeconomic and environment through GIT adoption.

The contribution of this study is presenting an in-depth analysis of the knowledge structure through bibliometric analysis by providing network visualization on one of the crucial pro-environmental behavior.

Docking technology plays a crucial role in enabling long-duration operations of autonomous underwater vehicles (AUVs). Visual positioning solutions alone are susceptible to abnormal drift values due to the challenging underwater optical imaging environment. When an AUV approaches the docking station, the absolute positioning method fails if the AUV captures an insufficient number of tracers. This study aims to to provide a more stable absolute position visual positioning method for underwater terminal visual docking.

This paper presents a six-degree-of-freedom positioning method for AUV terminal visual docking, which uses lights and triangle codes. The authors use an extended Kalman filter to fuse the visual calculation results with inertial measurement unit data. Moreover, this paper proposes a triangle code recognition and positioning algorithm.

The authors conducted a simulation experiment to compare the underwater positioning performance of triangle codes, AprilTag and Aruco. The results demonstrate that the implemented triangular code reduces the running time by over 70% compared to the other two codes, and also exhibits a longer recognition distance in turbid environments. Subsequent experiments were carried out in Qingjiang Lake, Hubei Province, China, which further confirmed the effectiveness of the proposed positioning algorithm.

This fusion approach effectively mitigates abnormal drift errors stemming from visual positioning and cumulative errors resulting from inertial navigation. The authors also propose a triangle code recognition and positioning algorithm as a supplementary approach to overcome the limitations of tracer light positioning beacons.

Autonomous mobile robots (AMRs) play a crucial role in industrial and service fields. The paper aims to build a LiDAR-based simultaneous localization and mapping (SLAM) system used by AMRs to overcome challenges in dynamic and changing environments.

This research introduces SLAM-RAMU, a lifelong SLAM system that addresses these challenges by providing precise and consistent relocalization and autonomous map updating (RAMU). During the mapping process, local odometry is obtained using iterative error state Kalman filtering, while back-end loop detection and global pose graph optimization are used for accurate trajectory correction. In addition, a fast point cloud segmentation module is incorporated to robustly distinguish between floor, walls and roof in the environment. The segmented point clouds are then used to generate a 2.5D grid map, with particular emphasis on floor detection to filter the prior map and eliminate dynamic artifacts. In the positioning process, an initial pose alignment method is designed, which combines 2D branch-and-bound search with 3D iterative closest point registration. This method ensures high accuracy even in scenes with similar characteristics. Subsequently, scan-to-map registration is performed using the segmented point cloud on the prior map. The system also includes a map updating module that takes into account historical point cloud segmentation results. It selectively incorporates or excludes new point cloud data to ensure consistent reflection of the real environment in the map.

The performance of the SLAM-RAMU system was evaluated in real-world environments and compared against state-of-the-art (SOTA) methods. The results demonstrate that SLAM-RAMU achieves higher mapping quality and relocalization accuracy and exhibits robustness against dynamic obstacles and environmental changes.

Compared to other SOTA methods in simulation and real environments, SLAM-RAMU showed higher mapping quality, faster initial aligning speed and higher repeated localization accuracy.

Studies on developed economies showed that imposing taxes on animal-based foods could effectively reduce agricultural greenhouse gas emissions (AGHGEs), while this taxation may not be appropriate in developing countries due to the complex nutritional status across income classes. Hence, this study aims to explore optimal tax rate levels considering both emission reduction and nutrient intake, and examine the heterogenous effects of taxation across various income classes in urban and rural China.

The authors estimated the Quadratic Almost Ideal Demand System model to calculate the price elasticities for eight food groups, and performed three simulations to explore the relative optimal tax regions via the relationships between effective animal protein intake loss and AGHGE reduction by taxes.

The results showed that the optimal tax rate bands can be found, depending on the reference levels of animal protein intake. Designing taxes on beef, mutton and pork could be a preliminary option for reducing AGHGEs in China, but subsidy policy should be designed for low-income populations at the same time. Generally, urban residents have more potential to reduce AGHGEs than rural residents, and higher income classes reduce more AGHGEs than lower income classes.

This study fills the gap in the literature by developing the methods to design taxes on animal-based foods from the perspectives of both nutrient intake and emission reduction. This methodology can also be applied to analyze food taxes and GHGE issues in other developing countries.

This paper aims to study a neural network-based fault-tolerant controller to improve the tracking control performance of an unmanned autonomous helicopter with system uncertainty, external disturbances and sensor faults, using the prescribed performance method.

To ensure that the tracking error satisfies the prescribed performance, the authors adopt an error transformation function method. A control scheme based on the neural network and high-order disturbance observer is designed to guarantee the boundedness of the closed-loop system. A simulation is performed to prove the validity of the control scheme.

The developed adaptive fault-tolerant control method makes the system with sensor fault realize tracking control. The error transformation function method can effectively handle the prescribed performance requirements. Sensor fault can be regarded as a type of system uncertainty. The uncertainty can be approximated accurately using neural networks. A high-order disturbance observer can effectively suppress compound disturbances.

The tracking performance requirements of unmanned autonomous helicopter system are considered in the design of sensor fault-tolerant control. The inequality constraint that the output tracking error must satisfy is transformed into an unconstrained problem by introducing an error transformation function. The fault state of the velocity sensor is considered as the system uncertainty, and a neural network is used to approach the total uncertainty. Neural network estimation errors and external disturbances are treated as compound disturbances, and a high-order disturbance observer is constructed to compensate for them.