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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.

This study aims to investigate the impact of supply chain concentration (SCC) on corporate research and development (R&D) investment and determine the moderating roles of industry concentration and financing constraints on the relationship between SCC and R&D investment.

The study collected data from Chinese listed companies, used the fixed effects model to test the research hypotheses and further used the two-stage Heckman test and propensity score matching (PSM) to address potential endogeneity issues.

The result reveals a negative impact of SCC on corporate R&D investment. In addition, industry concentration mitigates the negative impact of SCC on corporate R&D investment, but financing constraints strengthen the negative impact.

This study introduces the concept of SCC and empirically tests its effect on R&D investment, further explaining the lack of corporate innovation. This study inspires companies to strengthen SC management and weigh the level of SCC with environmental factors.

This study aims to provide students an opportunity to analyze the financial performance of a publicly listed real estate company and estimate its instinct value by applying appropriate financial models and approaches.

Three major valuation models/approaches generated by financial theory and practice to estimate the intrinsic value of a security: discounting cash-flows valuation (DCF and NPV) – valuation through adjusted net asset and liquidation value (NAV) – relative valuation through price and value multiples (valuation multiple analysis and precedent transactions analysis). Wholly owned subsidiaries versus and joint venture ones.

Analyze financial information of all segments in a multiple-business firm, and apply suitable financial models and approaches among net asset value model (NAV), discounted cash flow (DCF) or net present value (NPV) model, valuation multiple analysis and precedent transactions analysis to estimate the intrinsic value of the whole firm.

This decision-based case allows students to explore the business valuation process for a public listed real estate company, Alexander & Baldwin, Inc. (NYSE: ALEX). Based on financial statements analysis and forward-looking financial expectation on ALEX, this case elevates students' understanding and practice of valuating this multiple-business firms by applying appropriate financial models and approaches among NAV, DCF or NPV, valuation multiple analysis and precedent transactions analysis and enable students to make their investment decisions of buying, holding or selling the company’s stocks.

This case is most appropriate for graduate courses such as corporate finance, investments, personal finance, real estate finance and financial markets and institutes.

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 research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

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.