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The incentive cost of enterprises increases significantly with the rapid growth of the social commerce (SC) market. In this context, enterprises need to develop the optimal strategy to improve incentive effectiveness and reduce cost. Different types of consumers’ responses to incentives bring different values to enterprises. Hence, this paper proposes the social commerce value network (SCVN) to help enterprises study the contributions of different types of consumers to the network.

Based on the graphical evaluation and review technique (GERT), the authors construct the social commerce value GERT (i.e. SCV-GERT) network and design three progressive experiments for estimating the value contributions of “network stage”, “consumer type”, and “resource type” to the SCVN under the same incentives. The authors initialize the SCV-GERT model with consumer data in SC and distinguish the most valuable consumers by adjusting the incentive parameters.

The results show that the SCV-GERT model can well describe the value flow of SCVN. The incentive on forwarding consumers brings the greatest value gain to the SCVN, and social trust contributes the most to forwarding consumers.

Under the guidance of the results, platforms and enterprises in SC can select the optimal type of consumers who bring the maximum network value so as to improve the effectiveness of incentive strategy and reduce marketing costs. A four-level incentive system should be established according to the ranking of the corresponding value gains: forwarding consumers > agent consumers > commenting consumers > potential consumers. Enterprises also need to find ways to improve the social resource investments of consumers participating in SC.

This paper investigates the incentive problem in SC grounded in the SCVN and uses the GERT method to construct the SCV-GERT model, which is the first attempt to introduce GERT into the SC context. This study also makes up for the lack of comparative research on different types of consumers in SC and can provide support for enterprises’ customer relationship management and marketing decisions.

Using typical structure of asphalt pavement in Harbin area of China, and the formula of generalized friction coefficient between base and surface layers of asphalt pavement in cold area is established.

Through structural characteristics analysis of asphalt pavement in cold area, the generalized formula of friction coefficient between base and surface layers of asphalt pavement in cold area is derived. The formula can quickly calculate the friction coefficient between layers of asphalt pavement.

Based on quantitative analysis to the contacting state between layers of asphalt pavement in cold area, the relationships between generalized friction coefficient and resilient modulus of asphalt mixtures, temperature shrinkage coefficient and temperature have been established.

The findings can enrich the description methods about the contacting state between layers of asphalt pavement, and have a certain theoretical and practical value. Through the application of the formula of generalized friction coefficient between layers, it can provide a technical basis for the asphalt pavement design, construction and maintenance in cold area.

This paper aims to present a method of optimal singularity-free motion planning under multiple objectives and multiple constrains for the 6-DOF parallel manipulator, which is used as an execution mechanism for the automated docking of components.

First, the distribution characteristics of the Jacobian matrix determinant in local workspace are studied based on the kinematics and a sufficient and necessary condition of singularity-free path planning in local workspace is proposed. Then, a singularity-free motion path of the end-effector is generated by a fifth-order B-spline curve and the corresponding trajectories of each actuator are obtained via the inverse kinematics. Finally, several objective functions are defined to evaluate the motion path and an improved multi-objective particle swarm optimization algorithm-based on the Pareto archive evolution is developed to obtain the optimal singularity-free motion trajectories.

If the initial pose and the target pose of the end-effector are both singularity-free, a singularity-free motion path can be planned in the local workspace as long as all the values of each pose elements in their own directions are monotonous. The improved multi-objective particle swarm optimization (IMPSO) algorithm is effective and efficient in the optimization of multi-objective motion planning model. The optimal singularity-free motion path of the end-effector is verified in the component docking test. The docking result is that the movable component is in alignment with the fixed one, which proves the feasibility and practicability of the proposed motion path method to some extent.

The proposed method has a certain novelty value in kinematic multi-objective motion planning of parallel manipulators; it also increases the application prospect of parallel manipulators and provides attractive solutions to component assembly for those organizations with limited cost and that want to find an option that is effective to be implemented.

To fabricate a selective laser melting (SLM)-processed AlSi10Mg part with almost full density and free of any apparent pores, this study aims to investigate the effect of ambient argon pressure and laser scanning speed on the particles splash during the AlSi10Mg powder bed laser melting.

Based on the discrete element method (DEM), a 3D model of random distribution of powder particles was established, and the 3D free surface of SLM forming process was dynamically tracked by the volume of fluid, where a Gaussian laser beam acts as the energy source melting the powder bed. Through the numerical simulation and process experimental research, the effect of the applied laser power and scanning speed on the operating laser melting temperature was studied.

The process stability has a fundamental role in the porosity formation, which is process-dependent. The effect of the processing conditions on the process stability and the resultant forming defects were clarified.

The results shows that the pores were the main defects present in the SLM-processed AlSi10Mg sample, which decreases the densification level of the sample.

The optimal processing parameters (argon pressure of 1,000 Pa, laser power of 180 W, scan speed of 1,000 mm/s, powder layer thickness of 35 µm and hatch spacing of 50 µm ) applied during laser melting can improve the quality of selective laser melting of AlSi10Mg,

It can provide a technological support for 3D printing.

Based on the analysis of the pore and balling formation mechanisms, the optimal processing parameters have been obtained, which were argon pressure of 1,000 Pa, laser power of 180 W, scan speed of 1,000 mm/s, powder layer thickness of 35 µm and hatch spacing of 50 µm. Then, a near-fully dense sample free of any apparent pores on the cross-sectional microstructure was produced by SLM, wherein the relative density of the as-built samples is larger than 97.5%.

Smart contracts using blockchain technology (BCT) is a tool that decentralizes authority and makes it easier to upgrade the contract administration process by providing an efficient system. Current literature provides a good overview of contracts in the construction industry; however, the specific details of BCT's smart contracts applications in the three categories have not been addressed adequately: (1) information quality, (2) enhancing project schedule and progress payment time and (3) reducing conflicts among project stakeholders. Thus, this study aims to analyze smart contracts using BCT by creating a computerized contract model, specifically evaluating its impact on the three identified categories.

In this paper BCT-SmContract was developed through an automated program that utilizes blockchain to define the contractual agreements between different parties in a construction project. BCT-SmContract model provides a new technique to overcome the current challenges associated with factors identified in this study, i.e. (1) information quality, (2) enhancing project schedule and progress payment time and (3) reducing conflicts among project stakeholders. Afterward, the model was tested to ensure validity and reliability through a construction project.

The findings indicated that BCT-SmContract was approximately 90% faster to execute the contract and 100% accurate in reflecting the correct information about the project status, resulting in reduced conflicts.

This study has contributed in upgrading the traditional contracting method in construction by developing an automated smart contract model to enhance the processes and achieve higher accuracy.

Online retailers have become gradually popular to offer consumers installment payment services in the past few years. This paper aims to study how to determine the duration and rate of installment payment services, as well as the price of products to increase online retailers’ profits.

By modeling the utility functions, the behavior of consumers for strategic choosing the payment method and payment timing is analyzed. Thus, the market segments are obtained through the comparison of the consumer’s utilities. Combined with the given assumptions, the installment payment strategies for online retailers is investigated. This paper focuses on the impact of installment payment services on consumers’ purchasing behavior and online retailers’ profits by modeling and comparative analysis. No installment payment service as a benchmark, it is demonstrated whether online retailers can obtain more profits by offering installment payment services or what are the applicable conditions for installment payments.

If the installment payment service is offered, online retailers can gain more profits and need to adopt appropriate strategies based on different market conditions. During the depression or the peak shopping season, online retailers should take the strategy of free installment rate, and moderately increasing the product price of no installment service. When market demand is stable or during non-peak season, online retailers need to set a higher installment rate and maintain the product price without installment service. Finally, online retailers should determine the maximum duration of installments they can afford based on own risk control cost and allow consumers to freely choose the length of the installment within the duration limit.

First, the authors deeply analyze consumers’ payment and purchase behavior when the online retailer offers the installment payment service. Then, it is theoretically proved why many online retailers have offered installment payment services to consumers from a profit perspective. Finally, this paper proposes the optimal duration of installments, installment rate and product price in different market environments for online retailers, to provide theoretical basis and managerial insights for the development of installment payment service in online shopping.

The purpose of this paper is to present a new approach for selecting the good heavy oil reservoirs to develop preferentially, which can avoid the huge economical loss resulted from wrong decision.

A new method of ranking the development priority of heavy oil reservoir is present, in which the neural network is applied for the first time to acquire reservoir parameters' weights through training samples and the genetic algorithm is used to optimize the joint weighs of neurons in case that neural network falling into local minimum. Additionally, the paper establishes subordinate function of every parameter. Eventually, comprehensive evaluation values of all heavy oil reservoirs are obtained.

The method can ensure the veracity and creditability of the parameters' weights, avoid the randomicity brought by experts.

Accessibility of the data of many heavy oil reservoirs is the main limitation.

A very useful and new method for the decision makers of heavy oil reservoirs development.

The new approach of ranking the development priority of heavy oil reservoir based on the neural network and the genetic algorithm. The paper is aimed at the leaders who manage the development of heavy oil reservoirs.

Nested within the industrial organization and corporate finance literature, this paper aims to analyze the market for cross-border mergers and acquisitions (M&A) in the world economy, developed economies, developing economies and transition economies. As multinational companies hold a large proportion of cash reserves and expand into diverse geographic markets, the paper aims to examine market patterns of high-valuation cross-border acquisition transactions. Specifically, it proposes a framework explaining the influential factors, motives and effects of high-valuation transactions by discussing some case evidences.

Drawing upon inductive and deductive logic, the paper discusses market trends and market patterns of cross-border M&A transactions by triangulating archival data analyses and accessible M&A literature. Some case examples are derived from news archive and official source sites. Regarding sample period, it considers the past two decades 1994-2013 to show market trends in various institutional settings and the past decade 2004-2013 to present market patterns of 62 high-valuation cross-border deals.

The transaction analysis indicates four cycles in the market trend, namely, growing period (1994-2000); declining, but promising period (2001-2006); financial crisis period (2007-2008); and recovering, but reversing period (2009-2013). A number of acquisitions undertaken by firms from emerging economies around the 2007-2008 global financial crisis have exemplified geographic (product) diversification as a primary motive of firm’s global strategy. In particular, a large proportion of sample high-valuation deals are spotted in developed economies such as the USA and the UK. In case of industry pattern, a good number of high-valuation deals are noticed in banking and finance, telecommunications and oil and gas sector.

Although several scholars have examined cross-border acquisitions in economics, corporate finance, strategy and international business literature, there is hardly any study that analyzes high-profile cross-border M&A deals. An exclusive market analysis of high-valuation international deals is important for several reasons. This paper fills this knowledge gap by showing both market trends and market patterns of cross-border M&A transactions. Importantly, to date, this paper is the first to propose a framework explaining the influential factors, motives and effects of high-valuation M&A transactions.

Despite the growing research regarding consumer luxury value perception and their influence on luxury consumption behavior in different cultural contexts, there is little research investigating the cultural variation toward luxury within different generations in a given society. The purpose of this paper is to assess the relationships among Confucian propriety, luxury value perception, and purchase intention of luxury brands, and especially how these relationships differ between young and older consumers in a Chinese context.

Data were collected through a questionnaire survey in China. A multi-group structural equation model was used to test the conceptual model and research hypotheses.

The results show that the effects of functional value and social value on purchase intention of luxury brands are stronger for older generations than younger ones, while the effects of self-identity and hedonic value on purchase intention are stronger for younger generations than older ones. The Confucian propriety relates positively to the functional value and social value; however, these effects are more salient for older consumers.

The results of this study reveal the evolution of luxury consumption values and behaviors of Chinese consumers, suggesting that marketers should no longer label Chinese luxury consumers with common behaviors. It is also recommended that marketers of luxury brands in China should adapt this shifting attitude and respond actively to the expectations of different generations.