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In large-scale environments and unstructured scenarios, the accuracy and robustness of traditional light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) algorithms are reduced, and the algorithms might even be completely ineffective. To overcome these problems, this study aims to propose a 3D LiDAR SLAM method for ground-based mobile robots, which uses a 3D LiDAR fusion inertial measurement unit (IMU) to establish an environment map and realize real-time localization.

First, we use a normal distributions transform (NDT) algorithm based on a local map with a corresponding motion prediction model for point cloud registration in the front-end. Next, point cloud features are tightly coupled with IMU angle constraints, ground constraints and gravity constraints for graph-based optimization in the back-end. Subsequently, the cumulative error is reduced by adding loop closure detection.

The algorithm is tested using a public data set containing indoor and outdoor scenarios. The results confirm that the proposed algorithm has high accuracy and robustness.

To improve the accuracy and robustness of SLAM, this method proposed in the paper introduced the NDT algorithm in the front-end and designed ground constraints and gravity constraints in the back-end. The proposed method has a satisfactory performance when applied to ground-based mobile robots in complex environments experiments.

The purpose of this paper is to investigate the consequences of two strategies of coordinating the online procurement capability and the online channel management capability on competitive performance.

A research model is presented to examine the performance impacts of these two coordination strategies, namely the balancing strategy (achieving a close match relationship) and the complementing strategy (maintaining the synergy effect), and tested using firm-level data collected from 196 manufacturing firms in China. Garen's two-stage econometric technique was used to identify the impacts of two coordination strategies on competitive performance.

Our study discusses and compares two different coordination strategies of mitigating the operational tensions across processes and deploying resource configurations for improving competitive performance. Our results show that while the balancing strategy can mitigate the risks resulted, the complementing strategy does not create synergistic effects on the focal firms' competitive performance.

The results extend our understanding of the nature of B2B digital process coordination both in IS management and supply chain operations.

The purpose of this study is to investigate the impacts of surface ozone pollution on rice profit, output and variable inputs in China.

This study estimates the rice profit function using county-level rice production data and ozone monitoring data in 2014 and 2015 to capture the impact of ozone pollution on rice profit. Then, it uses dual approach to identify the impacts of ozone on the supply of rice and the demand for variable inputs. The ozone concentration data are obtained from 1,412 monitoring stations established by the National Environmental Monitoring Centre of China.

The results show that surface ozone would significantly reduce rice profits; a 1% increase in (the daily average ozone concentration from 9 am to 4 pm) leads to a 0.1% decrease in profits. In addition, ozone has a negative impact on the levels of inputs and the supply of rice, and the elasticities of rice output, fertilizer input and labour input with respect to are −0.87, −0.86 and −0.78%, respectively. These results suggest that ozone pollution affects rice production via two channels: the direct damage on rice growth and the indirect negative impact of reducing variable inputs.

This study estimates the impacts of surface ozone pollution on rice profit and output, and quantifies its influence on variable inputs in China, which provides a better understanding of farmers' adaptation behaviour.

Escalation in the number of online food ordering platforms, along with extensive junk food marketing, lucrative offers and discounts, innovation in food flavors, and doorstep delivery of food, have triggered the consumption of high-calorie and unhealthy food products which pose serious threats to the health and future well-being of individuals by making them more obese. To date, several public policy frameworks have been developed to confront obesity; however, their efficacy seems debatable. Directionally, the objective of this study is to highlight the potential influence of “digital nudging” which aims at steering individuals in desired directions, at the same time delimiting their freedom of choice. The study also establishes the effectiveness of digital nudges promoting a healthy lifestyle by steering individuals toward healthier food choices. The author strongly believes that this conceptual perusal will offer immense inputs to healthy food marketers and researchers alike in addressing the matters of obesity. Addressing the menace of obesity calls for joint efforts of the government, the public, researchers, and more specifically food product manufacturers/marketers who should incorporate healthier food options into their portfolios. E-tailers are also urged to adopt such practices in virtual markets and promote healthier food options to effectively tackle obesity.

Although a substantial body of literature investigates the determinants of audit report lag (ARL), scant empirical evidence exists on the consequences of ARL. The purpose of this paper is to examine the association between abnormally long ARL and future stock price crash risk.

This quantitative study employed a large scale (14,445 firm-year observations) of annual financials, audit and ownership information for the Chinese listed companies during 2002–2013 which were retrieved from the China Stock Market and Accounting Research database.

This study finds evidence that abnormally long ARL increases the risk of a future stock price crash. Furthermore, the study finds that this adverse consequence is more pronounced for firms with a poor internal control environment.

Recently literature started to explore the consequences of abnormal ARL such as going concern audit opinion and restatements in the subsequent periods. This paper reveals that abnormal ARL has consequences for investor wealth losses as well. This is relevant in China, where the ongoing economic growth has attracted, and will continue to attract, a growing body of domestic and international investors. Understanding what factors could expose investors to wealth losses is of paramount importance for allocating their scarce capital.

This study extends the scant literature on the consequences of ARL, and provides useful insights for the Chinese regulatory authorities when considering the appropriateness of the current filing deadline for listed firms.

The purpose of this paper is to present and develop an ontology-based approach for automatic generation of assembly sequences.

In this approach, an assembly sequence planning ontology is constructed to represent the structure and interrelationship of product geometry information and assembly process information. In the constructed ontology, certain reasoning rules are defined to describe the knowledge and experience. Based on the ontology with reasoning rules, the algorithm for automatically generating assembly sequences is designed and implemented.

The effectiveness of this approach is verified via applying it to generate the assembly sequences of a gear reducer.

The main contribution of the paper is presenting and developing an ontology-based approach for automatically generating assembly sequences. This approach can provide a feasible solution for the issue that mathematics-based assembly sequence generation approaches have great difficulty in explicitly representing assembly experience and knowledge.

The paper aims to know about energy condition’s impacts on inflation comprehensively.

This paper constructs China’s energy condition index (ECI) by bringing in three variables (China’s energy price, consumption and production) based on the financial condition index.

The result of empirical analysis shows that the index can predict China’s inflation well.

China’s ECI can predict China’s inflation well.

The purpose of this paper is to examine CEO wealth changes around seasoned equity offerings (SEOs) to explore the shareholder-manager incentive alignment in major corporate equity financing decisions.

The authors decompose CEO wealth into three major components: price effect, board compensation grant, and CEO’s own portfolio adjustment. The authors then compare SEO-event sample vs non-event samples; and evaluate the dynamic and long-run CEO wealth effect.

The authors find when market reacts negatively to SEO announcement leading to losses in CEO’s existing firm-related wealth, CEO gets additional grants to offset the losses. Although this appears to be a rent-seeking activity, the authors find that the additional grants are mainly in the form of stock options which would have no value if stock price failed to pick up in the future. In this sense, the additional grants align the interests between shareholders and managers. Consistent with this argument, the authors show that the additional grants motivate CEOs to promote the stock performance, benefiting themselves as well as shareholders in the long-run.

The study explicitly calculates the contribution of each wealth component to CEO total wealth effect. The results improve the understanding of CEO compensation policy change after major corporate event and contribute to the literature of the optimality explanation of prevailing compensation policy.

IT-based supply chain performance is co-created through inter-organizational business processes. This research is motivated to explore how business value of IT in supply chain is co-created in downstream process and probe into the possible complementary effect of relational resources from retailers and customers during the cooperative process. The paper aims to discuss these issues.

A model is proposed to conceptualize the process with three dimensions and six constructs, which emerges a causal link between organization resources application, e-supply chain capability (ESCC) and process performance. And then the research model was validated using partial least squares with data collected from 128 manufacturing firms in China.

The results provide broad support for the following: the casual relationship among inter-organizational resources interaction, ESCC and process performance; the mediating role of ESCC in the e-CRM process is more significant than that in e-ordering process; and there is the moderating effect between relational resources and internal resources in e-CRM process.

It offers guidelines for managers to plan the roles played by resource, capabilities and performance for e-supply chain success in multi-firm environments.

This study provides a novel perspective and offers important implications for e-supply chain research and practice, by exploring intermediate factors and shedding light on the process of co-creating business value of IT in supply chain.

The purpose of this paper is to obtain the characteristic parameters of dynamic trend for hydro turbine governors, and take these as the inputs of the neural network to realize the diagnosis of the system.

Computer simulation technique has become an important tool in the science research and development. Because of the different degree defaults of the traditional modeling method, a distributed bond graph modeling (BGD) method is presented in this paper. Fault diagnosis and identification have been widely developed in recent years, while many kinds of diagnosis methods have been used in this area. Since it is difficult to get the characteristic parameters of dynamic trend, a new methodology is proposed which integrates BGD and neural network. It gets the characteristic parameters by simulation to the system, and takes these as the inputs of the neural network to realize the diagnosis of the system.

The paper presents the need for application of two models – conventional procedure and bond graph model approaches.

The paper is a very useful diagnosis tool for operators.

A new methodology is proposed which integrates BGD and neural network. The paper is aimed at operational researches and engineers, the results from simulations are reported and commented in the paper.