Search results

This paper aims to chart the breadth and acceleration of organic markets domestic and international and discuss the obstacles and possible ways that confront enterprises who engage in organic exports from and imports to China.

There is much extant research that investigates the organic certification and its market development in the developed world. However, little emphasis is given to China, the highest growing organic market. This research aims to narrow this gap in the literature by reviewing organic certification and the market in China.

China's organic products are mainly exported to developed countries, but the growing affluence of Chinese consumers and expanding foreign expatriate community in China is developing a domestic market for organic food. Organic products are increasingly being imported. Organic standards and certification system in China have been established and under the implementation, with all stages of the organic marketing chain regulated by law and guaranteed. The lack of an equivalent or compliant system forces Chinese organic exports to enter the international market through multi‐certification, and foreign organic imports to the China market possibly through certification by a CNAS‐ACB.

This paper provides a unique insight into a wide range of China organic certification systems and the mechanism for organic exports from and imports to China.

In response to food scares related to high levels of agro-chemical residues sometimes found on foods, consumers in China increasingly demand for organic foods. As little is known on consumer perceptions and attitudes toward organic food products, the purpose of this paper is to gain insight into the purchase of organic food products by consumers and to explore the main factors driving this process.

Mixed (quantitative and qualitative) market survey approaches were used to provide a potentially deeper insight into consumer’s perspective and could help get a better picture of the complex factors involved.

The main trigger for purchasing organic food products is that consumers expect them to be healthier and safer. The respondents who have bought organic food products tend to have a higher education level and disposable incomes, be families with children and be older than those who have not bought them. The main barriers to increasing the market share of organic food products are the consumers’ lack of knowledge, the relatively high price premium and the lack of availability of organic food products. Informing consumers about unique characteristics of organic production methods, the decline in the prices of and increasing the availability of organic food products to its customers might be a promising strategy to develop the market for organic food products.

This paper provides a unique insight into buying behavior and attitudes of organic consumers in China. The results of the research could provide information for the organic food industry to expand its market and improve its profitability and reliability.

The purpose of this paper is to establish a combined forecasting model to predict regional logistics demand, which is an important procedure on decision making of regional logistics planning.

There are several kinds of mathematical models often used in forecasting regional logistics demand. Trend extrapolation method extrapolates the future development trends bases on the hypothesis that the regional logistics will develop steadily. Grey system method predicts the change of logistics demand by the generation and development of original data sequence and excavation of inherent rules of the original data. Regression method obtains the change rules through the analysis between explained variable and explanatory variables. Each method has unique characteristics. In order to improve the accuracy of the prediction, combined methods are established. Genetic algorithm is used to determine the weights of different single models.

The results show that the combined forecasting model optimised by genetic algorithm can improve the accuracy.

Combined forecasting model can integrate the advantages of different single forecasting models. The key of improving the accuracy is to determine the weights of single forecasting models. Genetic algorithm can do well in finding suitable weights of each single forecasting model.

The paper succeeds in providing a combined forecasting model using genetic algorithm to determine the weights of each single prediction model, which helps to the decision making of regional logistics demand.

This paper aims to study and compare the friction stability of wet paper-based clutches with regard to the radial grooves (RG) and waffle grooves (WG).

This paper presents an experimental study of a wet clutch concerning the effect of groove patterns on the friction torque and surface temperature. The friction stabilities of RG and WG are investigated with the applied pressure, rotating speed and automatic transmission fluid (ATF) temperature taken into consideration.

The friction torque and surface temperature of WG are larger than those of RG under the same operating condition. The friction torque difference between RG and WG grows with the increase of applied pressure and narrows with the increase of ATF temperature. Additionally, their temperature difference expands via increasing the rotating speed and ATF temperature or reducing the applied pressure; in this way, not only the variable coefficient difference between RG and WG can be narrowed, but also the friction stability of the clutch can be improved dramatically.

This paper explains the thermodynamic differences between RG and WG; moreover, it is verified experimentally that WG has a better friction stability than RG.

The purpose of this paper is to investigate the relationship between customer’s electronic word-of-mouth (eWOM) regarding their direct service experiences with firms and these firms’ company value. The authors drew on the marketing-finance interface research approach to demonstrate how interactive social media adopted by individual customer relate to important firms’ financial performances.

The authors used seven American airline companies’ customers’ tweets collected during a 52-week observation period and paired with their corresponding financial data using stock returns and volatilities. Sentiment analysis algorithm and a vector autoregressive (VAR) model quantified the strong association between customer’s eWOM and these firms’ stock returns and volatilities.

The results show that customer’s eWOM regarding a firm positively associate with the firm’s stock return but negatively associate with its stock volatility; as negative valence of customer’s eWOM increases, the positive effect of eWOM on firm’s stock return decreases; the negative eWOM impacts on the stock market more profoundly compared with when both positive and negative sensitivities are considered; and eWOM’s wear-out effect is much shorter than that of traditional WOM.

The authors address a literature gap where little is known for how customer’s eWOM, that is evaluating firm services, can ultimately impact on firms’ long-term financial performances. The authors discuss how findings from this study offer implications for marketing management as well as strategic insights for practitioners and investment analysts alike.

This paper aims to evaluate the influence of molybdenum disulfide (MoS₂) concentrations (5, 7.5, 10, 12.5 and 15 Wt.%) on the microstructure and tribological property of the self-lubrication cubic boron nitride (CBN) abrasive composites.

Three point bending method and rotating sliding test are used to evaluate the flexural strength and tribological property of self-lubricating CBN abrasive composites. Microstructure, wear morphology of the ball and scratch are supported by scanning electron microscopy, optical microscope and three-dimensional confocal microscopy, etc.

The MoS₂ concentration has a significant influence on the interface microstructure between CBN abrasives and matrix alloys, and thus, affects the flexural strength of CBN abrasive composites. The grain fracture modes of CBN abrasive composites are transformed from the transgranular fracture into intergranular fracture as the MoS₂ concentrations increase. Additionally, the friction coefficient of as-sintered samples decreases with the MoS₂ concentrations. The MoS₂ concentrations of 10 Wt.% are final determined to fabricate self-lubricating composites in basis of the mechanical and lubricating property.

The ball is fabricated under vacuum sintering process. The tribological property of self-lubricating CBN abrasive composites is evaluated in terms of the friction coefficient and morphologies of the ball and scratches after rotating sliding tests.

Assembly variation analysis generally demands probability distributions of variation sources. However, due to small production volume in aircraft manufacturing, especially prototype manufacturing, the probability distributions are hard to obtain, and only the small-sample data of variation sources can be consulted. Thus, this paper aims to propose a variation analysis method driven by small-sample data for compliant aero-structure assembly.

First, a hybrid assembly variation model, integrating rigid effects with flexibility, is constructed based on the homogeneous transformation and elasticity mechanics. Then, the bootstrap approach is introduced to estimate a variation source based on small-sample data. The influences of bootstrap parameters on the estimation accuracy are analyzed to select suitable parameters for acceptable estimation performance. Finally, the process of assembly variation analysis driven by small-sample data is demonstrated.

A variation analysis method driven by small-sample data, considering both rigid effects and flexibility, is proposed for aero-structure assembly. The method provides a good complement to traditional variation analysis methods based on probability distributions of variation sources.

With the proposed method, even if probability distribution information of variation sources cannot be obtained, accurate estimation of the assembly variation could be achieved. The method is well suited for aircraft assembly, especially in the stage of prototype manufacturing.

A variation analysis method driven by small-sample data is proposed for aero-structure assembly, which can be extended to deal with other similar applications.

This paper seeks to discuss the genealogical sources for Chinese immigrants as well as the settlement of Chinese in the USA and the historical evolution of Chinese names, their origins, arrangement and development. It aims to cover the origins of various classes of Chinese surnames, followed by the content description of a traditional genealogical book for jiapu.

The paper researches the various ways that a Chinese person can find out about their ancestry.

The paper reveals the roles of libraries, including serving the needs of patrons interested in genealogical research, preserving and interpreting information through oral and family history projects and collaborating with other libraries through interlibrary loan, document delivery, library consortia, collection management and international resource‐sharing.

The study provides information on where and how to locate the genealogical resources for researching the genealogy of a Chinese family.

The paper analyzes the value of genealogical research as a documentary source for population history, life expectancy in a clan, marriages and family connections, as well as lineage organizations and inter‐lineage relations.

This paper aim to take the ship shaft stern bearing as the research object, and studies the influence of journal axial vibration on bearing dynamic characteristics under different misaligned angles and rotation speeds.

Computational fluid dynamics (CFD) and harmonic excitation method were used to build bearing unstable lubrication model, and the dynamic mesh technology was used in calculation.

The results indicate that journal axial vibration has a significant effect on bearing dynamic characteristics, like maximum oil film pressure, bearing stiffness and damping coefficients, and the effect is positively correlated with journal misaligned angle. The effect of shaft rotation speed and journal axial vibration on bearing dynamics characteristics are independent; they have no coupling. Bearing axial stiffness is mainly affected by the journal axial displacement, bearing axial damping is mainly affected by journal axial velocity and they are positively correlated with the misaligned angle. The influence of rotational speed on bearing axial stiffness and axial damping is not obvious.

This paper establishes the bearing dynamic model by CFD and harmonic excitation method with consideration of cavitation effect and analyzing the influence of journal axial vibration on the dynamic characteristics. The results are benefit to the design of ship propulsion shaft and the selection of stern bearing. Also, they are of great significance to improve the operation stability of the shaft bearing system and the vitality of the ship.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2022-0337/

The purpose of constructing a degradation index (DI) is to better characterize the degradation degree of mechanical transmission compared with relying solely on spectral oil data, which leads to an accurate estimation of the failure time when the transmission no longer fulfills its function.

The DI is modeled using a weighted average function with two desirable properties: maximizing the monotonic trend and minimizing the variance of failure threshold between different transmissions. The method includes concentration modification, data selection and data fusion steps that lead to a reasonable mechanical transmission degradation model. The proposed methodology was verified through a case study involving multispectral oil data sampled from several power-shift steering transmissions.

The results show that the DI outperforms all spectral oil data. Compared with the existing spectral oil data-based degradation modeling approach for mechanical transmissions, the present methodology provides an accurate RUL prediction.

There are several important directions for future research: First, more degradation data (i.e. ferrography) that are tailored to the degradation modeling of mechanical transmission need to be involved. Second, more effective degradation data selection methodologies that are applicable for multiple data types need to be developed. Third, kernel methods that can fuse the nonlinear degradation data need to be investigated.

The novelty of this methodology lies in integrating the multiple degradation data in a unified DI. And the main contribution of this paper is to establish a new direction in degradation modeling and RUL prediction of mechanical transmission.