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The purpose of this paper is to study the extensive method of grey target based on multi‐stage linguistic label, which is a hypothesis of incomplete information of the weight of stage and decision maker.

For the incomplete weight information case, the weight model for the stage and decision maker is put forward based on the requirement of maximum difference among the alternatives. Also, the weight of the decision maker is estimated by the grey relationship method and the Euclid distance method.

As a result, the method of multiple stage grey target decision making based on linguistic label is suggested. In the incomplete information case, the weight model is suggested and the aggregation is put forward. The suggested method is clear and simple, which can be used in multi‐criteria decision making fields.

This paper offers a very useful result for multi‐attribute decision making.

This paper succeeds in studying the extensive method of grey target based on multi‐stage linguistic label, which is a hypothesis of incomplete information of the weight of stage and the decision maker.

The purpose of this paper is to develop and test a model of the uncertainties and benefits influencing the repurchase intentions of buyers in cross-border e-commerce (CBEC).

The authors draw on the valence framework to hypothesize effects of positive valences (utilitarian benefits) along with negative valences (pre- and post-contractual uncertainties) on buyers’ repeat purchase intentions. Data were collected using an online survey from 378 international B2C buyers on a CBEC platform in China.

Results explain 51.4 percent of the variance and reveal that overall value, as determined by monetary saving, convenience and product offerings as positive valences, exerts the strongest effect on repeat purchase intention. However, negative valences remain significant, and are particularly salient for female shoppers.

The authors extend the valence theory into the study of repeat purchase behavior and contribute to much needed literature on why consumers return to repurchase from a CBEC platform.

Repeat purchase and loyalty of online consumers is essential for success of e-commerce providers. The results help online providers competing in international markets understand how buyers form repurchase intentions based on their evaluations of both value and uncertainty.

Buyer behavior in CBEC has received relatively less attention than domestic e-commerce. This paper is among the first to examine how both positive and negative valences combine to effect repurchase intention of international buyers in CBEC.

The purpose of this paper is to present an investigation of the effect of different gravity conditions on the penetration mechanism using the two-dimensional Distinct Element Method (DEM), which ranges from high gravity used in centrifuge model tests to low gravity incurred by serial parabolic flight, with the aim of efficiently analyzing cone penetration tests on the lunar surface.

Seven penetration tests were numerically simulated on loose granular ground under different gravity conditions, i.e. one-sixth, one-half, one, five, ten, 15 and 20 terrestrial gravities. The effect of gravity on the mechanisms is examined with aspect to the tip resistance, deformation pattern, displacement paths, stress fields, stress paths, strain and rotation paths, and velocity fields during the penetration process.

First, under both low and high gravities, the penetration leads to high gradients of the value and direction of stresses in addition to high gradients in the velocity field near the penetrometer. In addition, the soil near the penetrometer undergoes large rotations of the principal stresses. Second, high gravity leads to a larger rotation of principal stresses and more downward particle motions than low gravity. Third, the tip resistance increases with penetration depth and gravity. Both the maximum (steady) normalized cone tip resistance and the maximum normalized mean (deviatoric) stress can be uniquely expressed by a linear equation in terms of the reciprocal of gravity.

This study investigates the effect of different gravity conditions on penetration mechanisms by using DEM.

The purpose of this paper is to propose a new generic hybrid Petri Net (PN) model combined with the lowest makespan cut (LMC) for job shop scheduling problems in mold manufacturing to minimize the makespan of the mold part manufacture schedule.

The LMC algorithm finds a solution close to the optimal solution. The searching of the LMC algorithm starts from the lowest estimated makespan (lowest makespan). Almost all of the lowest makespans (LM) are infeasible makespans. A shifting percentage (SP) is added to the LM to obtain the shifting makespan (SM). The SM is compared with the completion time computed from the reachability tree of the Petri Net (PN) model. If the completion time is greater than the SM, the corresponding branch is cut from the reachability graph, and the SM will be compared with another branch from the reachability tree. There are two scenarios. In the first scenario, there is no feasible solution resulting from the comparison of the completion time and the SM, because the SM is lower than all of the feasible solutions. Therefore, the SP is used to increase the SM. On the contrary, in the second scenario, there is a feasible solution: the SP is used to reduce the SM. In the first scenario, a makespan that is lower than the optimal makespan is found. In the second scenario, a makespan that is greater than the optimal makespan is found. After getting close to bounds of the optimal makespan, the least makespan found in the bounds is the best solution.

The integration of the Petri Net (PN) model and the LMC algorithm can help to improve the production efficiency. In a case study, the proposed algorithm is being compared with other heuristical methods which are practical examples of mold makespans based on the shortest and the longest processing times. The schedule or the sequence obtained by the proposed algorithm is 30% less than the other methods.

This research will consider scheduling multiple mold. The mold design and the mold testing phase are not considered.

The time to produce a mold is very important. Reducing the mold production time will provide more time for mold assembly and testing. The aim of LMC algorithm is minimize the makespan. The time to produce a mold is reduced by finding the best sequence of the jobs and machines.

This paper proposes the new generic hybrid Petri Net model combined with LMC for job shop scheduling problem in the case of mold making shop to optimize the makespan of mold parts scheduling.