The outputs of a national economy can be partitioned into three sets of products: tangible goods (due to manufacturing, construction, extraction and agriculture), intangible services (due to an act of useful effort), and an integration of services and goods or, as initially defined by Tien (2012), servgoods. Actually, these products can also be considered in terms of their relation to the first three Industrial Revolutions: the First Industrial Revolution (circa 1800) was primarily focused on the production of goods; the Second Industrial Revolution (circa 1900) was primarily focused on the mass production of goods; and the Third Industrial Revolution (circa 2000) has been primarily focused on the mass customization of goods, services or servgoods. In this follow-up paper, the Third Industrial Revolution of mass customization continues to accelerate in its evolution and, in many respects, is subsuming the earlier Industrial Revolutions of production and mass production. More importantly, with the advent of real-time decision making, artificial intelligence, Internet of Things, mobile networks, and other advanced digital technologies, customization has been extensively enabled, thereby advancing mass customization into a Fourth Industrial Revolution of real-time customization. Moreover, the moral, ethical, security and employment problems associated with both mass and real-time customization must be carefully assessed and mitigated, especially in regard to unintended consequences. Looking ahead and with the advance of artificial general intelligence, this Fourth Industrial Revolution could be forthcoming in about the middle of the 21st Century; it would allow for multiple activities to be simultaneously tackled in real-time and in a customized manner.

Low-carbon economy is gaining growing attention nowadays as global warming intensifies. As a market-based policy, emission trading policy is widely considered an effective means to achieve the doublewin of economic development and environmental protection. Under such circumstances, carbon trading markets are developing rapidly in many countries and regions, demanding more attention to compliance strategy issues for emission-intensive companies. In this study, we build a dynamic programming model in search of the optimal emission trading and technology investment decisions for a make-to-order company faced with a stochastic demand under emission trading policy. After a comprehensive analysis of the proposed model, we find that an optimal emission permit level, which increases in carbon penalty and decreases in carbon price, exists in each period. As for the abatement technology investment decision, the firm should invest only if the investment cost per unit of abatement effort is less than a certain threshold, which increases in carbon penalty and carbon price. On the basis of a two-period dynamic programming model, we further explore the problem of investment timing. Results show how optimal investment decisions are influenced by the speed of technology progress under different parameters. These findings are important for firms to choose the time of investment depending on specific situations.

This paper proposes a systematic approach to creating stories to promote research or business projects and examines its effectiveness through an actual story-making project. This approach can be used to create promotion stories for, not just projects, but also products or services. It originates in a knowledge construction systems methodology, whichisageneral knowledge-building methodologythat systematically supports knowledge construction from validated objective knowledge, information spreading to society, and people’s vivid inspiration. The effectiveness of the proposed approach was verified through a story creation project at a national institute in Thailand. Participants in the project, which lasted three months, and executives of the institute, were happy with the completed promotion stories. Because new ideas for promoting research or projects are often less universal, this paper provides justification principles for judging the practicability of new ideas as well as an evaluation method by people’s sensibility. These were used to evaluate the created stories and confirmed to be effective.

This paper examines the impact of piracy on access pricing strategy of an operating system platform. We study the behavior of users and developers due to an increase in software protection when positive network externalities matter. We show that when piracy cost increases, access demands to the platform vary in the same direction and the magnitude of this variation depends on both the marginal network benefit that a developer derives and a certain threshold of piracy cost. Taking into account the behavior of these two sides when piracy matters, the monopoly platform changes its pricing strategy. We show that, it tends to reduce or to increase access fees. Finally, we show that under certain conditions, the divide-and-conquer pricing strategy can be reversed.

In this paper, we consider the strategic interaction between the normal and sharp traders in a dynamic limit-order security market and its impact on the Chinese security market at different market volatility levels. We find that when the proportion of sharp traders is less than a threshold in an order-driven market, the sharp traders who submit limit orders will get more returns than the normal traders. The participation of sharp traders in the market can increase the total social welfare of all the traders. In addition, we show that:(1) when the market volatility level is generally low, the short-term sharp traders benefit from larger volatility; (2) when the market volatility level is generally high, the insider/cheating sharp traders with high-frequent trading rather than the short-term sharp traders benefit from extreme high volatility; (3) when the market volatility level is moderate, the sharp traders can increase market liquidity.

Data envelopment analysis (DEA) method based on game theory effectively ranks the decision-making units (DMUs) by the view of cooperation or competition. The DEA method based on partial ordered set theory depicts the relationships among DMUs. However, these methods are unable to reveal the complex cooperation and competition relationships among DMUs. In this paper, an optimal model for DMUgroup game strategy isproposed based onthegeneralized DEA method and gametheory. According to this model, we can effectively depict the efficiency change of DMUs. Moreover, the effect of various game relationships on individual and the union of DMUs can be characterized. It is of positive significance for decision makers to find partners and moderate the cooperation and competition situation of their competitors. Finally, the cooperation and competition relationships of 9 express enterprises in a certain area in China are analyzed by using the method proposed in this paper.