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This paper aims to investigate whether the establishment of commodity futures can effectively hedge systemic risk in the spot network, given the context of financialization in the commodity futures market.

Utilizing industry association data from the Chinese commodity market, the authors identify systemically important commodities based on their importance in the production process using multiple graph analysis methods. Then the authors analyze the effect of listing futures on the systemic risk in the spot market with the staggered difference-in-differences (DID) method.

The findings suggest that futures contracts help reduce systemic risks in the underlying spot network. Systemic risk for a commodity will decrease by approximately 5.7% with the introduction of each corresponding futures contract, since the hedging function of futures reduces the timing behavior of firms in the spot market. Establishing futures contracts for upstream commodities lowers systemic risks for downstream commodities. Energy commodities, such as crude oil and coal, have higher systemic importance, with the energy sector dominating systemic importance, while some chemical commodities also have considerable systemic importance. Meanwhile, the shortest transmission path for risk propagation is composed of the energy industry, chemical industry, agriculture/metal industry and final products.

The paper provides the following policy insights: (1) The role of futures contracts is still positive, and future contracts should be established upstream and at more systemically important nodes in the spot production chain. (2) More attention should be paid to the chemical industry chain, as some chemical commodities are systemically important but do not have corresponding futures contracts. (3) The risk source of the commodity spot market network is the energy industry, and therefore, energy-related commodities should continue to be closely monitored.

The purpose of this paper is to briefly summarize and review the theories and methods of complex structures’ dynamic reliability. Complex structures are usually assembled from multiple components and subjected to time-varying loads of aerodynamic, structural, thermal and other physical fields; its reliability analysis is of great significance to ensure the safe operation of large-scale equipment such as aviation and machinery.

In this paper for the single-objective dynamic reliability analysis of complex structures, the calculation can be categorized into Monte Carlo (MC), outcrossing rate, envelope functions and extreme value methods. The series-parallel and expansion methods, multi-extremum surrogate models and decomposed-coordinated surrogate models are summarized for the multiobjective dynamic reliability analysis of complex structures.

The numerical complex compound function and turbine blisk are used as examples to illustrate the performance of single-objective and multiobjective dynamic reliability analysis methods. Then the future development direction of dynamic reliability analysis of complex structures is prospected.

The paper provides a useful reference for further theoretical research and engineering application.

The purpose of this paper is to deeply study and compare the dual and single hedging strategy, from the direct and cross hedging perspective.

The authors not only first consider the dual hedge of integrated risks in this oil prices and foreign exchange rates setting but also make a novel comparison between the dual and single hedging strategy from a direct and cross hedging perspective. In total, six econometric models (to conduct one-step-ahead out-of-sample rolling estimation of the optimal hedge ratio) and two hedging performance criteria are employed in two different hedging backgrounds (direct and cross hedging).

Results show that in the direct hedging background, a dual hedge cannot outperform the single hedge. But in the cross dual hedging setting, a dual hedge performs much better, possibly because the dual hedge brings different levels of advantages and disadvantages in the two different settings and the superiority of the dual hedge is more obvious in the cross dual hedging setting.

The existing literature that deals with oil prices and foreign exchange rates mostly concentrates on their relationship and comovements, while the dual hedge of integrated risks in this setting remains underresearched. Besides, the existing literature that deals with dual hedge gets its conclusions only based on a single specific background (direct or cross hedging) and lacks deeper investigation. In this paper, the authors expand the width and depth of the existing literature. Results and implications are revealing.

The purpose of this paper is to study the effect of different parts (predictable and impact) of different types of speculative behavior (intraday speculation, medium-term speculation and long-term speculation) on future fluctuations in the underlying index.

The authors input information about heterogeneous speculative behavior into the HAR-RV model to study the effect of different parts (predictable and impact) of different types of speculative behavior (intraday speculation, medium-term speculation and long-term speculation) on the future fluctuation of the underlying index.

The authors find that the increase in intraday speculation will exacerbate spot market volatility; and the expected increase of long-term value speculation can reduce market volatility, but the shock of speculation will exacerbate market volatility.

The authors suggest that regulators should strictly limit speculative intraday trading, and also focus on the long-term value speculation that decreases market volatility, in order to guide the benign development of the markets that stabilize abnormal market fluctuations.

First, in view of the correlation between the futures and spot markets, the authors put forward a new proxy for the speculation degree. Second, the authors input heterogeneous speculative behavior into the HAR-RV model to study the effects of different parts (predictable and impact) on different types of speculative behavior (intraday speculation, medium-term speculation and long-term speculation) on the future fluctuation of the underlying index.

This paper considers that a public department under specialized TQM manpower constraints have to implement multiple total quality management (TQM) policies to promote its service performance (fundamental goal) by adopting a centralized sequential advancement strategy (CSAS). Under CSAS, the decision‐makers (DMs) start off by focusing specialized TQM manpower on a single policy, then transfer the specialized TQM manpower to the next policy when the first policy reaches the predetermined implementation time limit (in terms of education and training). Suppose that each TQM policy has a different desirous education and training goal. When the desirous goals for all TQM policies are acheived, we say that the fundamental goal will be satisfied. Within the limitation of total implementation period of time for all policies, assume the desirous goals for all TQM policies cannot be achieved completely. Under this premise, the optimal implementation sequence for all TQM policies must be calculated to maximize the weighted achievement of the desirous goal. We call this optimization problem a TQM case of “centralized sequential decision‐making problem (CSDMP)”. The achievement of the desirous goal for each TQM policy is usually affected by the experience in prior implemented policies, which makes solving CSDMP quite difficult. As a result, this paper introduces the concepts of sequential effectiveness and path effectiveness. The structural properties are then studied to propose theoretical methods for solving CSDMP. Finally, a numerical example is proposed to demonstrate CSDMP’s usability.

The purpose of this paper is intended to create a model to measure quality of service, using fuzzy linguistics to analyze the quality of service of medical tourism in Taiwan so as to find the direction for improvement of service quality in medical tourism.

The study developed fuzzy questionnaires based on the characteristics of medical tourism quality of service in Taiwan. Questionnaires were delivered and recovered from February to April 2014, using random sampling according to the proportion of medical tourism companies in each region, and 150 effective samples were obtained. The critical quality of service level is found through the fuzzy gap analysis using questionnaires examining expectations and perceptions of customers, as the direction for continuous improvement.

From the study, the primary five critical service items that improve the quality of service for medical tourism in Taiwan include, in order: the capability of the service provider to provide committed medical tourism services reliably and accurately, facility service providers in conjunction with the services provided, the cordial and polite attitude of the service provider eliciting a sense of trust from the customer, professional ability of medical (nursing) personnel in hospital and reliability of service provider.

The contribution of this study is to create a fuzzy gap analysis to assess the performance of medical tourism service quality, identify key quality characteristics and provide a direction for improvement and development for medical tourism service quality in Taiwan.

The purpose of this article is to provide an interview Charles-Edouard Bouée, Chief Operating Officer, Roland Berger Strategy Consultants, and author of Light Footprint Management.

Provides an interview Charles-Edouard Bouée, Chief Operating Officer, Roland Berger Strategy Consultants, and author of Light Footprint Management.

Discusses the Light Footprint (LFP) approach to management, which is prevalent in Chinese businesses as a response to the volatile, uncertain, complex and ambiguous (VUCA) environment they operate in. Originality/value

Outlines the etymological origins of strategy, the differences between Chinese and western management styles. Opines that the LFP management style, which grew out of American military doctrine, will allow organizations to adapt and thrive during times of uncertainty.

Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.

The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.

The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.

Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.

The purpose of this paper is to present a CAD‐based human‐robot interface that allows non‐expert users to teach a robot in a manner similar to that used by human beings to teach each other.

Intuitive robot programming is achieved by using CAD drawings to generate robot programs off‐line. Sensory feedback allows minimization of the effects of uncertainty, providing information to adjust the robot paths during robot operation.

It was found that it is possible to generate a robot program from a common CAD drawing and run it without any major concerns about calibration or CAD model accuracy.

A limitation of the proposed system has to do with the fact that it was designed to be used for particular technological applications.

Since most manufacturing companies have CAD packages in their facilities today, CAD‐based robot programming may be a good option to program robots without the need for skilled robot programmers.

The paper proposes a new CAD‐based robot programming system. Robot programs are directly generated from a CAD drawing “running” on a commonly available 3D CAD package (Autodesk Inventor) and not from a commercial, computer aided robotics (CAR) software, making it a simple CAD integrated solution. This is a low‐cost and low‐setup time system where no advanced robot programming skills are required to operate it. In summary, robot programs are generated with a high‐level of abstraction from the robot language.