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The purpose of this paper is to investigate the relationships between attractiveness of athlete endorsers, match‐up, and consumers' purchase intention embedded in the China context.

The authors used a 3×2×2 between‐subject experimental design. Specifically, in this 12‐scenario study depicting a purchase experience they manipulated endorser attractiveness levels (high/middle/low), endorser‐product match‐up (high/low), and product type (to prevent single product bias).

The results showed that no matter whether the attractiveness is high, middle, or low, the high endorser‐product match‐up could produce higher purchase intention than the low endorser‐product match‐up could. Moreover, the purchase intention generated by the high‐attractive endorser with low match‐up would be higher than that generated by low‐attractive endorser with high match‐up.

This research demonstrates that endorsers' attractiveness, even compared to match‐up factor, and could affect consumers' purchase intention more significantly in China sport market. Practically speaking, the result suggests the companies which are related to sports should try their best to choose a highly attractive athlete endorser with outstanding performance and good morality in order to increase consumers' purchase intention.

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.

This study investigates the different effects of the (mis)alignment between servitization strategies (i.e. product-oriented and customer-oriented services) and inter-organizational information technology (IT) capabilities (i.e. IT reconfiguration and integration) concerning the environmental performance of servitized manufacturing firms.

Using hierarchical regression analysis, this study examines the theoretical model based on multi-respondent survey data from 1,149 senior managers of 383 manufacturers in China.

Product-oriented services have a non-significant effect on environmental performance, whereas customer-oriented services exert a significantly positive effect. The alignment between product-oriented services and IT reconfiguration, and that between customer-oriented services and IT integration, improve environmental performance. In contrast, the misalignment between product-oriented services and IT integration, and that between customer-oriented services and IT reconfiguration, hurt environmental performance.

This study elucidates the different effects of the (mis)alignment between servitization strategies and inter-organizational IT capabilities on environmental performance. It also resolves the inconsistency regarding the implications of servitization on environmental performance.

The purpose of this paper is to demonstrate how crop price insurance premium can be calculated using an option pricing model and how insurers can transfer underwriting risks in the futures market.

Based on data from spot and futures market in China, this paper develops an improved B-S model for the calculation of crop price insurance premium and tests the possibility of hedging underwriting risks by insurance firms in the futures market.

The authors find that spot price of crops in China can be estimated with agricultural commodity futures prices, and can be taken as the insured price for crop price insurance. The authors also find that improved B-S model yields better estimation of crop price insurance premium than traditional B-S model when spot price does not follow geometric Brownian motion. Finally, the authors find that hedging can be one good alternative for insurance firms to manage underwriting risks.

This paper develops an improved B-S model that is data-driven in nature. Insured price of the crop price insurance, or the exercise price used in the B-S model, is estimated from a co-integration model built on spot and futures market price series. Meanwhile, distributional patterns of spot price series, one important factor determining the applicability of B-S model, is factored into the improved B-S model so that the latter is more robust and friendly to data with varied distributions. This paper also verifies the possibility of hedging of underwriting risks by insurance firms in the futures market.

The purpose of this paper is to investigate the responsibility that should be taken by different pork supply chain participants to ensure pork quality and safety, with the aim of providing some guidance for strengthening the supervision of pork quality and safety.

The pig farmer survey and the pork consumer survey were conducted in Funing County, Jiangsu Province, using the best-worst scaling (BWS) and a mixed logit model.

The results showed that the designation of responsibility for ensuring pork quality and safety was of, in descending order, feed producers and suppliers, backyard farmers and farms of designated size, pork processing workshops and companies of and above designated size, slaughterhouses, supermarkets, farmer’s markets, pig transporters, and consumers. Both pig farmers and pork consumers believed that those involved in the initial pork supply chain should take greater responsibility for pork quality and safety.

Allocation of responsibilities across the entire pork industry chain was investigated from the perspective of pig farmers and pork consumers using the BWS and a mixed logit model. The results of this study might explain the unique problems that occur in pork supply chain management in large developing countries like China.

In order to solve the problem that the performance of the existing local feature descriptors in uncontrolled environment is greatly affected by illumination, background, occlusion and other factors, we propose a novel face recognition algorithm in uncontrolled environment which combines the block central symmetry local binary pattern (CS-LBP) and deep residual network (DRN) model.

The algorithm first extracts the block CSP-LBP features of the face image, then incorporates the extracted features into the DRN model, and gives the face recognition results by using a well-trained DRN model. The features obtained by the proposed algorithm have the characteristics of both local texture features and deep features that robust to illumination.

Compared with the direct usage of the original image, the usage of local texture features of the image as the input of DRN model significantly improves the computation efficiency. Experimental results on the face datasets of FERET, YALE-B and CMU-PIE have shown that the recognition rate of the proposed algorithm is significantly higher than that of other compared algorithms.

The proposed algorithm fundamentally solves the problem of face identity recognition in uncontrolled environment, and it is particularly robust to the change of illumination, which proves its superiority.

This study aims to analyze reform path for waste management policy implementation. With reference to the Bayesian theory, this study provides a dynamic policy conversion method through various context settings. Furthermore, this study attempts to present an empirical research paradigm.

Matland’s “ambiguity-conflict model” is applied to explain the problems and reform paths of China’s waste management policy implementation. Integrating structure discovery and bibliometrics into qualitative analysis, this study used search data from literature search engine with specific themes to achieve structure learning of Bayesian network with key factors refined in waste management policy.

The results show that China’s waste management policy implementation belongs to symbolic implementation with high ambiguity and high conflict. Four basic conversion paths for the waste management policy are proposed, which are classified by length and stability. Then, it is possible to locate the factors, paths and types of policy implementation through involvement analysis with features of each path and each district of policy implementation. Public education holds direct but unstable impact on waste management. Economic incentives hold continuous but gradually diminishing impact. Perceived policy effectiveness plays the crucial role like a central bridge. Resident conditions have a positive impact, which could be enhanced through economic development of China. The impact of subjective norm on waste management is not significant. But subjective norm has the potential breakthrough for solving stagnation of waste classification policy. However, the impacts from each factor may change along with economy growth and technology innovation.

This study uses the “ambiguity-conflict model” to position China’s waste classification policy and suggests that structure discovery methods help understand feasible reform paths for reform policy. The integration of theoretical analysis and quantitative simulation can achieve a comprehensive analysis of problems and solutions in waste management policy implementation of China. Promotion and education, economic incentives, perceived value, behavior control, subjective norm, perceived policy effectiveness, informal waste recycling system and residential conditions are explored as key factors for waste classification policy implementation as a representative in waste management policy. The role of each key factor and features of each conversion paths are integrated to position reform paths in the ambiguity-conflict model. This work helps to explain the stagnation of waste management policy implementation from the perspective of dynamic structure evolution, and some specific suggestions to get out of stagnation are proposed.

This study aims to synthesise and characterise new reactive dyes based on thiazole derivatives which act as chromophoric moieties. These dyes were applied to cotton fabric, resulting in the dyed fabrics exhibiting good colour strength, light fastness and other fastness properties. The antibacterial activity of the dyed cotton fabric was evaluated against gram-negative and gram-positive bacteria.

The dyes were synthesised in two steps. First, the coupling compound was formed by adding H-acid solution to cyanuric chloride in an ice bath at pH 5 then adding 4-aminobenzenesulphonic acid portion-wise at room temperature and at pH 6-7. Second, different diazonium salts 4-phenylthiazol-2-amine (2a) and 4-(4-methoxyphenyl) thiazol-2-amine (2b) were coupled with the coupling compound at pH 5. The resultant monochlorotriazine (MCT)-reactive dyes (6a, 6b) were formed. The synthesised dyes were applied onto cotton fabric under typical exhaust dyeing conditions and their dyeing properties were investigated.

High antimicrobial activity, dye exhaustion and fixation yield on cotton fabric were recorded for each dye. All dyes showed high stability against washing, rubbing, perspiration and light fastness.

Dyeing of cotton fabric with these dyes which have higher fastness, higher exhaustion and higher antibacterial activity is considered one of the most important reactive dyes species.

The preparation procedure showed the synthesis of the novel MCT-reactive dyes derived from thiazole derivatives followed by the application of these dyes on cotton fabrics.

Use of reactive dyes will bring a number of benefits to society including higher fastness and higher antibacterial activity so, and these dyes can be used for dyeing cotton.

In this work, the new reactive dyes derived from thiazole derivatives were synthesised and their structures were confirmed by the analytical and spectral data. Such compounds are considered to be excellent reactive dyes with different colour shades and higher antibacterial activity.

The purpose of this paper is to classify Chinese word semantic relations, which are synonyms, antonyms, hyponyms and meronymys.

Basically, four simple methods are applied, ontology-based, dictionary-based, pattern-based and morpho-syntactic method. The authors make good use of search engine to build lexical and semantic resources for dictionary-based and pattern-based methods. To improve classification performance with more external resources, they also classify the given word pairs in Chinese and in English at the same time by using machine translation.

Experimental results show that the approach achieved an average F1 score of 50.87 per cent, an average accuracy of 70.36 per cent and an average recall of 40.05 per cent over all classification tasks. Synonym and antonym classification achieved high accuracy, i.e. above 90 per cent. Moreover, dictionary-based and pattern-based approaches work effectively on final data set.

For many natural language processing (NLP) tasks, the step of distinguishing word semantic relation can help to improve system performance, such as information extraction and knowledge graph generation. Currently, common methods for this task rely on large corpora for training or dictionaries and thesauri for inference, where limitation lies in freely data access and keeping built lexical resources up-date. This paper builds a primary system for classifying Chinese word semantic relations by seeking new ways to obtain the external resources efficiently.

This study aims to examine the role of personal and subjective norms in predicting waste sorting, an increasingly relevant pro-environmental behavior.

This study obtained data from a sample of 300 respondents from three Indonesian cities. Purposive sampling was employed to obtain information from specific segments of Indonesian population. The analysis consisted of a two-stage procedure including confirmatory factor analysis and covariance-based structural equation modeling.

Results demonstrated that both subjective and personal norms significantly and directly predict waste sorting behavior (WSB) bypassing intention to behave.

The fact that norms held by individuals are able to single-handedly drive pro-environmental behaviors implies that previous studies and social marketing campaigns may have overstated the role of intention.

In designing marketing communication programs promoting WSB, this paper argues that targeting normative tendencies of the audience may provide a more effective strategy than focusing on explicit pro-environmental intentions and attitudes of the public.

This study provided a new experimental test and confirmation of the role of subjective norms, the normative component of the theory of planned behavior and of personal norms, the normative component of the norm activation theory, in predicting WSB.