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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.

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.

With the rapid development and stable operated application of lithium-ion batteries used in uninterruptible power supply (UPS), the prediction of remaining useful life (RUL) for lithium-ion battery played an important role. More and more researchers paid more attentions on the reliability and safety for lithium-ion batteries based on prediction of RUL. The purpose of this paper is to predict the life of lithium-ion battery based on auto regression and particle filter method.

In this paper, a simple and effective RUL prediction method based on the combination method of auto-regression (AR) time-series model and particle filter (PF) was proposed for lithium-ion battery. The proposed method deformed the double-exponential empirical degradation model and reduced the number of parameters for such model to improve the efficiency of training. By using the PF algorithm to track the process of lithium-ion battery capacity decline and modified observations of the state space equations, the proposed PF + AR model fully considered the declined process of batteries to meet more accurate prediction of RUL.

Experiments on CALCE dataset have fully compared the conventional PF algorithm and the AR + PF algorithm both on original exponential empirical degradation model and the deformed double-exponential one. Experimental results have shown that the proposed PF + AR method improved the prediction accuracy, decreases the error rate and reduces the uncertainty ranges of RUL, which was more suitable for the deformed double-exponential empirical degradation model.

In the running of UPS device based on lithium-ion battery, the proposed AR + PF combination algorithm will quickly, accurately and robustly predict the RUL of lithium-ion batteries, which had a strong application value in the stable operation of laboratory and other application scenarios.

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.

Concerning that limited explanation exists examining the function of corporate governance in trust processing within entrepreneurial network development, the purpose of this paper is to explore trust evolution and the role of corporate governance in an entrepreneurial network.

This paper makes an innovative exploration based on the case study of NVC Lighting Holding Limited.

It proposes that in the initial period of network relationship which is based on entrepreneur’s individual social network and embodies sole social network embeddness, entrepreneurial network relies more on affective trust than contractual trust. When stepping into extending period of network relationship which reflects separate embeddedness of social and market network, however, entrepreneurial network has an equal reliance on both affective trust and contractual trust. With further development, when ushering in the phase of maturity which undergoes superimposing embeddedness of both social and market network, entrepreneur network inclines to rely more heavily on affective trust than contractual trust. During the whole process, it can be found that the reliance of entrepreneurial network on trust has the tendency to transfer from affective trust to contractual trust. Furthermore, decreasing of equity ratio of founders and strengthening of controlling right heterogeneity in the corporate governance have facilitated the transfer process and the entrepreneurs’ authority has restraining effect on the evolution of the process.

Through case study, this paper presents the trust evolution process in different stages of entrepreneurial network. Another important theoretic contribution of this paper is that it reveals the function of corporate governance in trust processing within entrepreneurial network development.

The purpose of this paper is to examine the purchase intention in the case of smartphone advertising, which is unlike any other advertising media.

This study examines the characteristics of recent mobile advertisements such as brand attitude and context awareness value, which have not been considered in studies on non-mobile advertisements, to address purchase intention through smartphone advertisements using structural equation modeling.

The results are as follows. Together with entertainment, information, irritation, and personalization in non-mobile advertisements, timing and location in mobile advertisements are the main factors for establishing consumers’ purchase intention. Further, although mobile advertisements’ context awareness value strongly impacts consumers’ advertising attitude and brand attitude, purchase intention receives greater impact from brand attitude than from advertising attitude because the products/services lack feel and touch.

These results imply that contextual advertising and new technology enabling feel and touch for products/services can maximize the effect of mobile advertisements.

This study aims to propose an electronic waste collection and classification system to enhance social, environmental and economic sustainability by integrating data-driven technologies in emerging economies.

GM (1, 1) model under grey prediction is used in this study in order to estimate the trend of the amount of collected electronic waste in emerging economies.

It is revealed that the amount of collected electronic waste is increasing day by day, and within the framework of sustainability in the process of collecting and classification of electronic waste, digital technologies were found to be lacking. It has been determined that this deficiency, together with the increasing amount of electronic waste, has caused environmental, social and economic damage to emerging economies.

The main originality of this study is integrating electronic waste collection and classification processes with data-driven technologies and sustainability, which is a relatively new subject.