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This paper aims to optimize the stiffness coefficient of the elastic element for a passive waist assistive exoskeleton (WAE). There is a tradeoff between stiffness coefficient of elastic element of the exoskeleton and work efficiency of the wearer, because elastic element affects original bending motion of the wearer and the force requirement of erector spinae is compensated by the other muscles. However, there is no accepted conclusion on how to determine the proper stiffness coefficient, especially with respected to the effort of groups of muscles, not only erector spinae.

In this study, a consumption indicator based on muscle fatigue of seven muscles is proposed and a Bayesian-based human-in-the-loop optimization approach is adopted to optimize the stiffness coefficient. Pneumatic artificial muscles are used to replace the mechanical elastic part to adjust the assistive force automatically. The proposed optimization method is verified by the way of load-lifting experiments with three different conditions: without exoskeleton, with fixed air pressure and with optimized air pressure. Six subjects participated in the experiment and each experiment is performed in different day.

Compared with No-Exo condition and static assistance condition, the parameter-optimized waist exoskeleton averagely reduces muscle fatigue of the six subjects by 45.30 ± 29.14% and 30.94 ± 30.29%, respectively. The experimental results indicate that the proposed method is effective to reduce muscle fatigue during stoop lifting task.

This paper provides a novel cost function construction method based on muscle fatigue and muscle synergy for passive WAE stiffness optimization.

Teaching venues are playing an important role in the filed of open and distance education (ODL). In China's ODL system over 70% enrolled students are from Radio and TV Universities (RTVUs). Many off-campus teaching venues of e-colleges in 67 conventional universities have been established in RTVUs at prefecture and city level. In this article, the authors have done a direct survey on the data of distance education cost over the past consecutive 4 years in 21 RTVUs at prefecture and city level from 3 provinces (Xinjiang, Hunan and Fujian) in China's western, central and eastern areas, and empirically studied the scale effect in teaching venues at prefecture and city level under the hypothesis condition-teaching effect of ODL and conventional education is the same. The study result illustrates that the average student cost of RTVUs at prefecture and city level demonstrates a scale economy feature, that is, with the expansion of enrolled students scale, there is a fall in the average student cost. The study indicates large differences between average student variable cost and average student cost, which shows a possible average cost reduction in RTVUs at prefecture and city level. In terms of geographical and economic differences, some imbalances of development have been found among RTVUs at prefecture and city level. A quadratic form regression model has been established for doing this research in the perspective of education economics. The results of the regression show that the optimal enrolled student number of RTVUs nationwide at prefecture and city level is around 7,800. For provinces, the most optimal enrolled student numbers are as follows: 9,100 for Fujian, 3,800 for Hunan, and 2,200for Xianjiang, which can serve as the reference for expanding scale economy in ODL. The research finding also indicate the changes in student average cost resulting from the changes in scale, the problem of determining investment direction. It is suggested that more input which benefit the quality improvement of distance education should be made.

In recent years, the rapid growth of big data has presented immense potential for business applications as well as raised great interest from academia. In response to this emerging phenomenon, the purpose of this paper is to provide a comprehensive literature review of big data.

A bibliometric method was used to analyze the articles obtained from the Scopus database published between 2013 and 2018. A sample size of 4,070 articles was evaluated using SciVal metrics.

The analysis revealed an array of interesting findings as follows: the number of publications related to big data increased steadily over the past six years, though the rate of increase has slowed since 2014; the scope of big data research is quite broad in regards to both research domains and countries; despite a large volume of publications, the overall performance of big data research is not well presented as measured by the field-weighted citation impact metric; collaboration between different institutions, particularly in the form of international collaboration and academic–corporate collaboration, has played an important role in improving the performance of big data research.

To the best of the authors’ knowledge, this is the first study to provide a holistic view of the big data research. The insights obtained from the analysis are instrumental for both academics and practitioners.

Organisational learning plays a critical role for firms to keep abreast of a supply chain environment filled with volatility, uncertainty, complexity and ambiguity (VUCA). This study investigates the extent to which supply chain learning (SCL) affects operational resilience under such circumstances.

This study developed a research framework and underlying hypotheses based on SCL and information processing theory (IPT). An empirical test was carried out using secondary data derived from the “Supply Chain Policy” launched by the Chinese government and two large related conferences.

SCL positively relates to operational resilience, and several moderators influence the relationship between them. The authors argue that digital-technological diversity could weaken the role of SCL in operational resilience, whereas customer concentration, and participating in a pilot programme could enhance the effect of SCL.

Firms should embrace the power of SCL in building resilience in the VUCA era. Meanwhile, they should be cautious of a digital-technological diversification strategy, appraise the customer base profile and proactively engage in pilot programmes.

This research develops the SCL construct further in the context of China and empirically measures its power on operational resilience using a unique dataset. This contributes to the theorisation of SCL.