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Monascus pigment was widely applied in food processing industry as functional additive, so more attention was paid to the fermentation optimization of pigment production. Therefore, this paper aims to evaluate the best possible fermentative conditions for maximum production of biopigment using submerged fermentation (SFM) and solid state fermentation (SSF) by Monascus purpureus HBSD 08.

The biopigment was produced by using an SMF and an SSF with optimized substrate to achieve higher yield. The antioxidant activity was evaluated by DPPH radical scavenging ability, superoxide anion radical scavenging ability and hydroxyl radical scavenging ability. The pigment composition was analyzed by thin layer chromatography.

Maximum Monascus pigment production (79.6 U/ml and 1,102 U/g) were obtained under an SFM and an SFF. The antioxidant activity of the pigment in an SFM was significantly higher than that in an SFM. The composition of pigment was not different in an SFM and an SFF.

The study developed new conditions, and Monascus strain was a candidate for producing pigment in an SFM and an SFF. To the authors’ best knowledge, this is a first attempt toward comparative evaluation on antioxidant capacity and composition between pigment in an SSF and an SFM. This result will serve for Monascus pigment production.

The purpose of this study is to investigate (1) how female blog users' perceived benefits (i.e. perceived usefulness, perceived enjoyment, community identification and perceived norm of reciprocity) influence their perceived social capital on fashion blogs, (2) the influence of structural social capital and cognitive social capital on users' relational social capital and (3) the influence of relational social capital on blog loyalty.

Structural equation modeling was performed using 530 useable data collected through an online survey.

The result indicated that perceived usefulness and the norm of reciprocity led to the development of cognitive social capital, while community identification and the norm of reciprocity led to the development of structural social capital. Cognitive and structural social capital both led to the development relational social capital, which in turn influenced blog loyalty.

This study provides insights for a fashion brand marketing strategy that uses fashion blogs to target relevant consumers. It helps firms to understand the factors that lead people to embed their resources in a blog and to learn how the different perceived benefits impact blog users' contributions to the community.

The purpose of this paper is to develop a novel multivariate fractional grey model termed GM(a, n) based on the classical GM(1, n) model. The new model can provide accurate prediction with more freedom, and enrich the content of grey theory.

The GM(α, n) model is systematically studied by using the grey modelling technique and the forward difference method. The optimal fractional order a is computed by the genetic algorithm. Meanwhile, a stochastic testing scheme is presented to verify the accuracy of the new GM(a, n) model.

The recursive expressions of the time response function and the restored values of the presented model are deduced. The GM(1, n), GM(a, 1) and GM(1, 1) models are special cases of the model. Computational results illustrate that the GM(a, n) model provides accurate prediction.

The GM(a, n) model is used to predict China’s total energy consumption with the raw data from 2006 to 2016. The superiority of the GM(a, n) model is more freedom and better modelling by fractional derivative, which implies its high potential to be used in energy field.

It is the first time to investigate the multivariate fractional grey GM(α, n) model, apply it to study the effects of China’s economic growth and urbanization on energy consumption.

The purpose of this paper is to model group advertising decisions, which are the collective decisions of every single advertiser within the set of advertisers who are competing in the same auction or vertical industry, and examine resulting market outcomes, via a proposed simulation framework named Experimental Platform for Search Engine Advertising (EXP-SEA) supporting experimental studies of collective behaviors in the context of search engine advertising.

The authors implement the EXP-SEA to validate the proposed simulation framework, also conduct three experimental studies on the aggregate impact of electronic word-of-mouth (eWOM), the competition level and strategic bidding behaviors. EXP-SEA supports heterogeneous participants, various auction mechanisms and also ranking and pricing algorithms.

Findings from the three experiments show that both the market profit and advertising indexes such as number of impressions and number of clicks are larger when the eWOM effect is present, meaning social media certainly has some effect on search engine advertising outcomes, the competition level has a monotonic increasing effect on the market performance, thus search engines have an incentive to encourage both the eWOM among search users and competition among advertisers, and given the market-level effect of the percentage of advertisers employing a dynamic greedy bidding strategy, there is a cut-off point for strategic bidding behaviors.

This is one of the first research works to explore collective group decisions and resulting phenomena in the complex context of search engine advertising via developing and validating a simulation framework that supports assessments of various advertising strategies and estimations of the impact of mechanisms on the search market.

This paper aims to present ball bearings with a composite structure based on the bionics principle and shows the comparison between five types of different structures.

By means of the finite element method, the stress and other parameters between different structures are compared and verified. Finally, the comprehensive parameters of different structures are evaluated by the analytic hierarchy process method.

The evaluation of the comprehensive parameters of five types of structures is shown here.

The value of this paper is calculated and compared to the parameters of five types of different structures, and the parameter score evaluation of each structure is given. Different structures can be selected according to different parameter requirements, which to provide a theoretical basis for the design of ball bearings.

The peer review history for this article is available at: https://publons.com/publon10.1108/ILT-10-2019-0413

This paper examines whether and how customers' annual report tone affects suppliers' innovation decisions.

Using the data from disclosed information on top five customers and annual report tone by Chinese listed firms, this paper used a two-way fixed effect model and intermediary effect model tests to explore the impact of customers' annual report tone on suppliers' innovation decisions.

The results indicate that the more positive the tone of customer annual reports is, the higher the suppliers' technological innovation level. The customers' annual report tone affects suppliers' innovation decisions through alleviating financing constraints and reducing the bullwhip effect. In addition, the authors find that the worse the supplier's bargaining power and the higher the customer's media coverage, the more significant the impact of positive customer annual report tone on the level of corporate technological innovation.

For downstream customers, to improve the quality of their text information disclosure. For upstream suppliers, the tone of customers' annual reports has incremental information, so the attention to customers' text information should be strengthened. As far as the market is concerned, it is recommended that regulators should strictly require the quality of text information disclosure and introduce relevant penalty mechanisms better to regulate the quality of corporate text information disclosure.

To the best of the author's knowledge, this paper is the first to expand the research related to textual information from a supply chain innovation perspective. The textual information can provide incremental information, and spillover effects may occur among supply chains, affecting suppliers' innovation decisions. And it clarifies the specific mechanism by which the supply chain tone spillover effect affects corporate innovation, enriching the relevant research on supply chain influence mechanisms.

Previous studies focused on the influence of outsourcing (labor division) on productivity, especially in the industrial economy. However, few studies have focused on how labor division in agriculture affects agricultural productivity. To bridge this gap, this study uses survey data from 4864 farmer households in China to explore the impacts of outsourcing on agricultural productivity.

This study employs an endogenous switching regression to account for selection bias and a counterfactual framework to measure the degree of influence. Thus, this study analyzes determinants of outsourcing and the impacts of outsourcing on agricultural productivity under the same framework.

The results revealed the following. (1) Farmer households with the below average productivity tended to outsource; conversely, farmer households with the above average productivity tended to cultivate the land by themselves. (2) Productivity increased by 25.61% for farmer households who choose to outsource. Moreover, if nonoutsourcing farmer households would choose to outsource, their productivity would increase by 10.86%.

This study furthers one’s understanding of how outsourcing affects agricultural productivity among farmer households.

A firm's inventions provide technical information for product planning and technical support for new product development (NPD). In the knowledge-based theory, inventing is regarded as a process of knowledge combination. This paper aims to classify the firm's inventive capabilities based on the combinatorial view and investigate the effects of inventive capabilities on NPD performance.

Four types of inventive capabilities are identified concerned with the knowledge used to combine in the inventive activities. By utilizing a dataset of 572 firms from China's automotive manufacturing industry, the roles of different inventive activities in the generation of new inventions are compared. Then the effects of different inventive capabilities on NPD performance are empirically examined by using negative binomial regression analysis.

The time series for the number of patented inventions derived from different types of combinations generally exhibits a steady upward trend, and the number of patents derived from recombination is much higher. The empirical results demonstrate that the inventive capabilities associated with reused recombination and creative recombination exhibit positive effects on NPD performance, and the inventive capabilities associated with novel combination and original combination exhibit non-linear effects on NPD performance.

The findings contribute to NPD literature by investigating the effects of different inventive capabilities on NPD performance. This study also provides guidelines for manufacturing managers to improve NPD performance by building appropriate inventive capabilities.

The purpose of this paper is to study a fractional grey model FAGM(1,1,t^α) based on the GM(1,1,t^α) model and the fractional accumulated generating operation, and then predict the national health expenditure, the government health expenditure and the out-of-pocket health expenditure of China.

The presented univariate grey model is systematically studied by using the grey modelling technique, the fractional accumulated generating operation and the trapezoid approximation formula of definite integral. The optimal system parameters r and α are evaluated by the particle swarm optimisation algorithm.

The expressions of the time response function and the restored values of this model are derived. The GM(1,1), NGM(1,1,k,c) and GM(1,1,t^α) models are particular cases of the FAGM(1,1,t^α) model with deterministic r and α. Compared with other forecasting models, the results of the FAGM(1,1,t^α) model have higher precision.

The superiority of the new model has high potential to be used in the medicine and health fields and others. Results can provide a guideline for government decision making.

The univariate fractional grey model FAGM (1,1,t^α) successfully studies the China’s health expenditure.

PM10 is one of the most dangerous air pollutants which is harmful to the ecological system and human health. Accurate forecasting of PM10 concentration makes it easier for the government to make efficient decisions and policies. However, the PM10 concentration, particularly, the emerging short-term concentration has high uncertainties as it is often impacted by many factors and also time varying. Above all, a new methodology which can overcome such difficulties is needed.

The grey system theory is used to build the short-term PM10 forecasting model. The Euler polynomial is used as a driving term of the proposed grey model, and then the convolutional solution is applied to make the new model computationally feasible. The grey wolf optimizer is used to select the optimal nonlinear parameters of the proposed model.

The introduction of the Euler polynomial makes the new model more flexible and more general as it can yield several other conventional grey models under certain conditions. The new model presents significantly higher performance, is more accurate and also more stable, than the six existing grey models in three real-world cases and the case of short-term PM10 forecasting in Tianjin China.

With high performance in the real-world case in Tianjin China, the proposed model appears to have high potential to accurately forecast the PM10 concentration in big cities of China. Therefore, it can be considered as a decision-making support tool in the near future.

This is the first work introducing the Euler polynomial to the grey system models, and a more general formulation of existing grey models is also obtained. The modelling pattern used in this paper can be used as an example for building other similar nonlinear grey models. The practical example of short-term PM10 forecasting in Tianjin China is also presented for the first time.