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The purpose of this paper is to investigate into the conditions under which founders’ human capital (HC) benefits new venture growth (NVG). One such condition is investigated in this study – initial assets at founding. Specifically, founding assets are hypothesized to moderate the relationship between founders’ HC and NVG.

The longitudinal panel database from the Kauffman Firm Survey for the period 2004–2011 was used to test the hypotheses. The final sample consisted of 4,923 firms, with 34,461 observations made over seven years.

The regression analysis found the effect of founders’ HC on NVG and the moderating role of founding assets in the HC–NVG relationship.

New ventures benefit even more from founders’ education level, industry and startup experiences when the startups have larger assets at founding. The effect of founders’ education and experiences on startup growth is contingent upon the initial assets at founding.

The results of this study can help practitioners and policy makers to understand the drivers of NVG and the interactions among these drivers. Growth-oriented startups may require a large investment in founding assets such as production facilities. Startups with fewer founding assets may find it particularly difficult to negotiate with external stakeholders and may face unusually intense competitive responses from competitors. Policy makers should tailor the support to the founding conditions of new firms.

The prior literature has shown mostly the independent positive effects of various resources on firm growth. This study argues and empirically shows that startups grow faster when founders with high HC have more assets to utilize. The resource-based view literature was expanded by adding important new causal mechanisms, enriching our understanding of how founders’ HC interact with founding assets, jointly affecting NVG. Like a big fish in a small pond, even highly educated and experienced entrepreneurs have limited opportunities to utilize their talents in a startup with a lower initial resource position.

Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.

The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.

The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.

Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.

Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly wholesale price index of green grams in the Chinese market. The index covers a ten-year period, from January 1, 2010, to January 3, 2020, and has significant economic implications.

In order to address the nonlinear patterns present in the price time series, we investigate the nonlinear auto-regressive neural network as the forecast model. This modeling technique is able to combine a variety of basic nonlinear functions to approximate more complex nonlinear characteristics. Specifically, we examine prediction performance that corresponds to several configurations across data splitting ratios, hidden neuron and delay counts, and model estimation approaches.

Our model turns out to be rather simple and yields forecasts with good stability and accuracy. Relative root mean square errors throughout training, validation and testing are specifically 4.34, 4.71 and 3.98%, respectively. The results of benchmark research show that the neural network produces statistically considerably better performance when compared to other machine learning models and classic time-series econometric methods.

Utilizing our findings as independent technical price forecasts would be one use. Alternatively, policy research and fresh insights into price patterns might be achieved by combining them with other (basic) prediction outputs.

This paper aims to review the research on accounting professionalisation in China to develop insights into how the research is developing, offer a critique of the research to date and outline future research directions and opportunities.

This paper adopts a methodological approach of systematic literature review, as suggested by Tranfield et al. (2003) and Denyer and Tranfield (2009), to identify, select and analyse the extant literature on the Chinese public accounting profession. In total, 68 academic works were included in the review process.

This paper finds that the extant literature has produced fruitful insights into the processes and underlying motivation of accounting professionalisation in China, demonstrating that the Chinese experience has differed, to a large extent, from the hitherto mainly Anglo-American-dominated understandings of accounting professionalisation. However, due to the lack of common theoretical vernacular and an agreed upon focus, the extant literature illustrates a fragmented and contradictory picture, making attempts to accumulate prior knowledge in the field increasingly difficult.

This paper focusses only on research published in English. Consequently, the scope of review has been limited as some works published in languages other than English may be excluded.

This paper provides one of the pioneering exercises to systematically review the research on accounting professionalisation in China. It explores significant issues arising from the analysis and provides several suggestions for furthering the research effort in this field.

The purpose of this paper is to incorporate Chinese traditionality (CT) and patriotism (PAT) within the theory of reasoned action (TRA). It tests the moderating effect of gender with the aim to provide a deeper understanding of why Chinese tourists choose to take domestic travels.

Data is collected from 370 Chinese tourists. Convenience sampling is used. Structural equation modelling is used to test the proposed hypotheses.

The results of this paper show that PAT is positively related to tourists’ attitudes (ATs) and Chinese domestic travel intention (CTI). Moreover, CT is found to influence PAT, ATs and subjective norms (SNs) directly, as well as CTI indirectly. However, the positive relationship between PAT and SNs is not supported. Additionally, the influence of PAT on CTI for females is significantly higher than that for males.

The current paper adopts convenience sampling; data is collected using an online questionnaire which may cause sample bias and even reduce the reliability of the data. Future studies may adopt quota sampling based on the population of each province to gain more reliable data. Further research can consider including more constructs to better understand why Chinese people choose to travel domestically.

This paper is one of the first attempts to include PAT and CT within the TRA and contributes to the pool of literature on the TRA. It provides a comprehensive understanding of CTI. Second, PAT and CT are linked to the TRA, which expands the application of PAT and CT to the context of hospitality and tourism. Finally, the moderating role of gender contributes to the knowledge regarding the moderating effect between their respective relationships.

性别在中国传统与爱国主义对中国国内旅游意愿影响中的调节作用

摘要

本研究将中国传统性与爱国主义引入理性行为理论, 同时将性别作为调节变量, 目的在于探究中国游客选择国内游的原因。

通过分析便利抽样所收集的370份中国游客样本, 运用结构方程模型验证本研究的假设。

中国游客爱国主义能够正向显著影响其国内游的态度和旅游意向; 此外, 中国传统性也直接影响游客的爱国主义、态度和主观规范, 并且分别通过爱国主义、态度和主观规范间接影响旅游意向; 然而, 爱国主义和主观规范之间的关系却并没有得到验证; 最后, 女性游客的爱国主义对于旅游意向的影响作用显著高于男性游客。

首先, 本研究运用网络调研的方式进行便利抽样, 这一点有可能产生样本偏差, 甚至降低了样本的可信度, 未来研究可以根据各省人口数量采用配额抽样的方式进行抽样, 以期进一步提高数据的可信度; 其次, 更多的变量应当被引入研究, 以进一步探究中国游客选择国内游的原因。

首先, 本研究是为数不多的将爱国主义和中国传统性引入理性行为理论, 这一点进一步拓展了关于理性行为理论的研究范围, 也进一步加深了对于国内游原因的认识; 其次, 将爱国主义和中国传统性这一概念引入旅游领域, 进一步拓展了关于两者研究的边界; 最后, 在中国国内游的研究领域中, 将性别作为调节变量引入本研究一定程度上填补了在该领域研究中的不足。

La influencia de la moderación de género en la tradición China y el patriotismo en la intención de viajar dentro de China

Este research incorpora los conceptos a de la tradicionalidad China (TC) y el patriotismo (PAT) a la teoría de La Acción razonada (TAR), teniendo en cuenta el efecto moderador de género, con el objetivo de profundizar en la comprensión de porqué los turistas chinos eligen realizar viajes domésticos/nacionales.

A partir de los datos recolectados de 370 turistas chinos utilizando las muestras de cuestionarios realizados de manera on-line, éste estudio usa un modelado de ecuaciones estructurales para probar las hipótesis propuestas.

Los resultados demuestran que el PAT está positivamente relacionado con las actitudes del viajero y la intención de viaje nacional chino (IVNC).Es más, la tradicionalidad China (TC) influye en el Patriotismo (PAT), las actitudes del viajero chino (AVC) y también en las normas subjetivas (NS) directamente.Adicionalmente, la influencia del PAT en la intención de viaje del viajero doméstico chino, especialmente en mujeres, es significativamente mayor que en hombres.

Primero, el estudio adopta un muestreo de conveniencia y recopila cuestionarios on-line, lo que puede causar un sesgo en la muestra e incluso reducir la confiabilidad de los datos obtenidos.Los futuros estudios pueden adoptar un muestreo por cuotas basado en el número de población de cada una de las provincias de China, para obtener datos más relevantes.

Este estudio es uno de los primeros en incluir el PAT y el TC dentro de la TAR, que amplía la literatura sobre la TAR y proporciona una comprensión más completa de las actitudes del viajero chino.Segundo, el PAT y la TC están vinculados al TAR, el cuál expande la aplicación del PAT y la TC en el contexto del turismo en todas sus ramas.Por último, el rol moderador de género contribuye al conocimiento, sobre el efecto moderador entre sus respectivas relaciones.

Porous implant surface is shown to facilitate bone in-growth and cell attachment, improving overall osteointegration, while providing adequate mechanical integrity. Recently, biodegradable material possessing such superior properties has been the focus with an aim of revolutionizing implant’s design, material and performance. This paper aims to present a comprehensive investigation into the design and development of low elastic modulus porous biodegradable Mg-3Si-5HA composite by mechanical alloying and spark plasma sintering (MA-SPS) technique.

This paper presents a comprehensive investigation into the design and development of low elastic modulus porous biodegradable Mg-3Si-5HA composite by MA-SPS technique. As the key alloying elements, HA powders with an appropriate proportion weight 5 and 10 are mixed with the base elemental magnesium (Mg) particles to form the composites of potentially variable porosity and mechanical property. The aim is to investigate the performance of the synthesized composites of Mg-3Si together with HA in terms of mechanical integrity hardness and Young’s moduli corrosion resistance and in-vitro bioactivity.

Mechanical and surface characterization results indicate that alloying of Si leads to the formation of fine Mg2 Si eutectic dense structure, hence increasing hardness while reducing the ductility of the composite. On the other hand, the allying of HA in Mg-3Si matrix leads to the formation of structural porosity (5-13 per cent), thus resulting in low Young’s moduli. It is hypothesized that biocompatible phases formed within the composite enhanced the corrosion performance and bio-mechanical integrity of the composite. The degradation rate of Mg-3Si composite was reduced from 2.05 mm/year to 1.19 mm/year by the alloying of HA elements. Moreover, the fabricated composites showed an excellent bioactivity and offered a channel/interface to MG-63 cells for attachment, proliferation and differentiation.

Overall, the findings suggest that the Mg-3Si-HA composite fabricated by MA and plasma sintering may be considered as a potential biodegradable material for orthopedic application.

This paper aims to propose a medium-term forecast model for the daily passenger volume of High Speed Railway (HSR) systems to predict the daily the Origin-Destination (OD) daily volume for multiple consecutive days (e.g. 120 days).

By analyzing the characteristics of the historical data on daily passenger volume of HSR systems, the date and holiday labels were designed with determined value ranges. In accordance to the autoregressive characteristics of the daily passenger volume of HSR, the Double Layer Parallel Wavelet Neural Network (DLP-WNN) model suitable for the medium-term (about 120 d) forecast of the daily passenger volume of HSR was established. The DLP-WNN model obtains the daily forecast result by weighed summation of the daily output values of the two subnets. Subnet 1 reflects the overall trend of daily passenger volumes in the recent period, and subnet 2 the daily fluctuation of the daily passenger volume to ensure the accuracy of medium-term forecast.

According to the example application, in which the DLP-WNN model was used for the medium-term forecast of the daily passenger volumes for 120 days for typical O-D pairs at 4 different distances, the average absolute percentage error is 7%-12%, obviously lower than the results measured by the Back Propagation (BP) neural network, the ELM (extreme learning machine), the ELMAN neural network, the GRNN (generalized regression neural network) and the VMD-GA-BP. The DLP-WNN model was verified to be suitable for the medium-term forecast of the daily passenger volume of HSR.

This study proposed a Double Layer Parallel structure forecast model for medium-term daily passenger volume (about 120 days) of HSR systems by using the date and holiday labels and Wavelet Neural Network. The predict results are important input data for supporting the line planning, scheduling and other decisions in operation and management in HSR systems.

Political factors play a crucial role in China's initial public offering (IPO) market due to its distinctive institutional context (i.e. “economic decentralization” and “political centralization”). Given the significant level of IPO underpricing in China, we examine the impact of local political uncertainty (measured by prefecture-level city official turnover rate) on IPO underpricing.

Using 2,259 IPOs of A-share listed companies from 2001 to 2019, we employ a structural equation model (SEM) to examine the channel (voluntarily lower the issuance price vs aftermarket trading) through which political uncertainty affects IPO underpricing. We check the robustness of the results using bootstrap tests, adopting alternative proxies for political uncertainty and IPO underpricing and employing subsample analysis.

Local official turnover-induced political uncertainty increases IPO underpricing by IPO firms voluntarily reducing the issuance price rather than by affecting investor sentiment in aftermarket trading. These relations are stronger in firms with pre-IPO political connections. The effect of political uncertainty on IPO underpricing is also contingent upon the industry and the growth phase of an IPO firm, more pronounced in politically sensitive industries and firms listed on the growth enterprise market board.

Local government officials in China usually have a short tenure and Chinese firms witness significantly severe IPO underpricing. By introducing the SEM model in studying China IPO underpricing, this study identifies the channel through which local government official turnover to political uncertainty on IPO underpricing.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.