Search results

Identifying the complementary effects of ride-sharing on public transit is critical to understanding the potential value of growing partnerships between public transit agencies and ride-sharing platforms. The purpose of this paper is to investigate whether and how ride-sharing services complement public transit.

Taking advantage of a natural experiment whereby subway Line 2 opened after the entry of ride-sharing services in Xiamen, this study uses a difference-in-differences approach to identify the complementary effects of ride-sharing on public transit based on a proprietary fine-grained trip-level data set from a large ride-sharing platform.

This study obtained the encouraging finding that ride-sharing has a significant complementary effect on the subway, as the number of ride-sharing pickups and drop-offs at subway stations increased by 130% and 117.9%, respectively, after the subway opening. Moreover, mechanism analysis shows that the complementary effect of ride-sharing services is stronger when connection distance is short (i.e. under 6 km) and when the transportation availability is limited (i.e. at night or in the areas with low transit supply and low population density).

The findings provide guidelines for promoting cooperation between public transit agencies and ride-sharing platforms to build an efficient and sustainable urban transport system.

This study is the first to examine the complementary effect of ride-sharing services on public transit via unique fine-grained ride-sharing trips data, and further reveal the underlying mechanism behind this effect.

This study aims to analyze the impact of the source of online word-of-mouth (WOM) on retail sales. Specifically, the authors focus on the relative impact of external and internal WOMs on book sales.

An empirical analysis is conducted with a panel data of sales and WOM for 87 books from Dangdang and Douban over a 14-day period based on two generalized least square regression models.

Results suggest that both internal WOM and external WOM have significant impact on product sales, and the impact of external WOM is relatively more significant.

WOM, especially the external WOM, plays an important role in consumers’ online purchase decisions.

This study is helpful for retailers to better understand the factors influencing the sales and thereby forecast the future sales more precisely. Besides, the research conclusion could also enlighten related decision makers to constantly improve technical platforms.

With the rapid development of web-based ideation platforms, firms are increasingly reaching outside their boundaries to obtain ideas, which makes idea evaluation tricky and ineffective. Numerous studies have investigated the antecedents of idea quality, but few have focused on the fragmented and contradictory conclusions these studies have drawn. Thus, the purpose of this paper is to disentangle conflicting findings regarding factors affecting idea quality.

A total of 41 independent samples from 40 articles published between 2009 and 2020 were retrieved and encoded to conduct a meta-analysis. By using Comprehensive Meta-analysis 3.0 (CMA 3.0) software, the relationship between identified influencing factors and idea quality, and the moderating effects of potential variables were investigated.

Factors affecting idea quality were summarized and divided into three categories: idea-related factors, ideator-related factors and platform-related factors. The results indicated that all proposed factors (idea length, supporting evidence, past success, past submissions, past comments, votes received and comments received) had significant positive effects on idea quality. Moreover, the measurement of idea quality and idea type was the causative factor for the inconsistent findings, whereas the moderating effect of platform type was not significant.

This study systematically synthesized the existing research on the factors influencing idea quality and helped to reconcile the mixed results. The findings serve to enrich current knowledge of idea evaluation in the online context, which could have important implications for both scholars and practitioners.

Quadrotor micro aerial vehicle (MAV) is nonlinear and under actuated plant, and it is difficult to obtain an accurate mathematical model for quadrotor MAV due to uncertainties. The purpose of this paper is to propose one robust control strategy for quadrotor MAV to accommodate system uncertainties, variations, and external disturbances.

The robust control strategy is composed of two self‐organizing interval type‐II fuzzy neural networks (SOIT‐IIFNNs) and one PD controller: the PD controller is adopted to control the attitude and position; one of the SOIT‐IIFNNs is designed to learn the inverse model of quadrotor MAV online; the other SOIT‐IIFNNs is the copy of the former one to compensate for model errors, system uncertainties and external disturbances, both structure and parameters of SOIT‐IIFNNs are tuned online at the same time, and then the stability of the resulting quadrotor MAV closed‐loop control system is proved using Lyapunov stability theory.

The validity of the proposed control method has been verified through real‐time experiments. The experimental results show that the performance of SOIT‐IIFNNs is significantly improved compared with Backstepping‐based controller.

This approach has been used in quadrotor MAV, the controller works well, and it could guarantee quadrotor MAV control system with good performances under uncertainties, variations, and external disturbances.

The proposed SOIT‐IIFNNs controller is interesting for the design of an intelligent control scheme. The main contributions of this paper are: the overall closed‐loop control system is globally stable, demonstrated by Lyapunov stable theory; the tracking error can be asymptotically attenuated to a desired small level around zero by appropriate chosen parameters and learning rates; and the quadrotor MAV control system based on SOIT‐IIFNNs controller can achieve favorable tracking performance.

The purpose of this paper is to investigate the anisotropic characteristics of the special structure of a columnar jointed rock masses and provide reference to forecast the behavioral characteristics of real samples.

This study used FLAC3D numerical software to simulate the mechanical behavior of columnar jointed rock masses with different columns angles (ß) under different stress conditions. The peak strength, elastic modulus and Poisson’s ratio were obtained to investigate the strength, deformation characteristics and failure modes of the rock masses under conventional and true triaxial compression.

The results showed that the compressive strength of the specimens presents a U-shape under different joint inclinations. The strength of the specimens reaches a maximum value when ß = 90°, and the value for ß = 0° is slightly lower and reaches a minimum value when ß = 50°. The elastic modulus and Poisson’s ratio of the samples are obviously anisotropic, the anisotropic coefficient decreases with increasing confining pressure. When σ₂ ≠ σ₃, the peak strengths of the samples are related to the direction of the minor principal stress, and the failure modes of the samples are related to the confining pressure and joint inclination.

The present paper uses a numerical simulation method to examine the strength and deformation characteristics of a columnar jointed rock mass under conventional and true triaxial compression. The aim is to provide a reference to forecast the mechanical characteristics of test samples in the laboratory.

Shows how the banking world too is adjusting to the needs of the socialist market economy. As a valuable adjunct to and tool for internal auditing, demonstrates the development of a bank surveillance system, ideally suited to the needs of bank management and internal audit. Such a system has required extensive development, necessitating probing into all aspects of banking activities. Details the approach taken to project control and reports that the bank concerned is now in a much more favourable position to determine risk assessment.

Autonomous ports and digital ports are a modern trend of global commercial ports that are established to develop toward smart ports in many ports. Smart port indicators (SPIs) are used as important tools for measuring, encouraging, and indicating smart port performance. These are the main indicators to operate smart port management as the practical direction and port development planning are enclosed. This research aims to identify the SPIs and to develop a conceptual model of smart port performance in a case study of The Eastern Economic Corridor (EEC) in Thailand. Triangulation data are used in the data collection with three sources: the reviewed literature of five international databases in 2016–2021, participant observations, and in-depth interviews. Content analysis is utilized to analyze these data to develop a conceptual model approach. The findings of this research are shown in three main domains classified as smart port operation, smart port environment/energy, and smart port safety/security. These indicators represent 29 SPIs for developing smart port performance, which can be explained with a conceptual model. This information will exist as the foundation framework guiding Thai smart ports towards international standards of smart port efficiency.

Agricultural science and technology (AST) often need the form of industry-university-research cooperation in successfully completing breakthrough agricultural technology innovations. Therefore, AST industry-university-research cooperation is not only the need of the AST development strategy in China but also the only way for the development of agricultural colleges and universities, agricultural scientific research institutions and agricultural enterprises. Among them, in the process of cooperative breakthrough agricultural technology innovation, the correct selection of partners is the basis for ensuring its effective operation.

Aiming at the time-series characteristics and information ambiguity of decision information in the dynamic selection process of AST industry-university-research partners, this research introduces the dynamic intuitionistic fuzzy multi-criteria decision-making method of time degree and orthogonal projection. On this basis, field theory is used to construct the cooperative innovation capability field model of the partners, and the threshold for the partners to enter or exit the system is designed to dynamically select and eliminate the partners.

Results show that this method fully considers the situation of cooperative innovation resources within the AST industry-university-research system and the resource complementarity of candidate partners.

Combined with examples from agricultural scientific research institutions, the applicability and superiority of the model are verified.

This study explores the impact of carbon neutrality policies on Chinese stock market from a supply chain perspective. Specifically, the carbon policy refers to the Action Plan for Carbon Dioxide Peaking Before 2030 (the Plan) in China.

This paper is based on the resource dependence theory (RDT) and applies the event study methodology to explore the impact. It uses the cross-sectional regression model to reveal the moderating effect of supply chain characteristics on the stock market reaction with a data set of 354 listed companies in A-shares (excluding ChiNext and SME board).

The promulgation of the Plan shows a significant negative stock market reaction. Customer concentration, out-degree centrality and smart supply chains (SSCs) have a significant negative moderating effect. In-degree centrality and supplier concentration have a significant positive moderating effect. Furthermore, the conclusions concerning out-degree centrality, supplier concentration and SSCs are counterintuitive.

For policymakers, the study results provide a reference for evaluating the carbon neutrality policy. For managers, this study provides theoretical support for strategically adjusting and designing supply chain structures in the context of advocating peak carbon dioxide emissions and carbon neutrality.

This paper is the first attempt that includes the supply chain structure factors into the impact of carbon neutrality policies on the stock market.