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Brand storytelling is an effective marketing tool. However, when choosing whether to tell more or tell less, it remains unclear which of these two narrative styles is most effective. This study aims to examine whether blank-leaving(less) leads to favourable brand attitudes and compares its effects on consumers’ story immersion, to non-blank-leaving(more).

Two experiments were conducted to test the hypotheses. In Study 1, a single-factorial design was used with 252 participants assigned at random to one of two narrative conditions: blank-leaving or non-blank-leaving. Study 2 replicated Study 1 and investigated the moderating role of implicit mindsets.

The results show that a blank-leaving narrative style increases favourable brand attitudes. Consumers present deeper immersion in the brand story that uses blank-leaving, as compared to non-blank-leaving, leading to a more favourable brand attitude. Furthermore, this effect is stronger for individuals with growth mindsets.

Telling the brand story using a blank-leaving narrative style is more effective in catching consumers’ attention than non-blank-leaving. In particular, a blank-leaving narrative is a good approach for targeting consumers who have a growth mindset.

To the best of the authors’ knowledge, this research is the first to investigate and compare the effects of blank-leaving and non-blank-leaving narrative styles on brand attitudes in the context of storytelling marketing.

This paper aims to address the spacecraft attitude regulation problem in the presence of extrinsic disturbances and actuator faults.

Based on adaptive backstepping design technique, a new concise adaptive dual-mode control scheme is proposed, which can either use the fault information detected by fault diagnosis mechanisms or switch to the fault-unknown mode when the fault diagnosis information is non-existent for control signal generation. These two modes share an adaptive mechanism that reduces the complexity of the algorithm.

The new fault-tolerant attitude control algorithm can accommodate both modes with and without fault diagnosis mechanisms.

The proposed algorithm in this paper can be applied to both cases when the attitude control system is equipped with or without fault diagnosis capability. This also enhances the robustness of attitude control algorithm. This study performs numerical simulations and verifies that the algorithm could effectively adapt to both modes.

The coupling impact of hybrid uncertain errors on the machine precision is complex, as a result of which the designing method with multiple independent error sources under uncertainties remains a challenge. For the purpose of precision improvement, this paper focuses on the robot design and aims to present an assembly precision design method based on uncertain hybrid tolerance allocation (UHTA), to improve the positioning precision of the mechanized robot, as well as realize high precision positioning within the workspace.

The fundamentals of the parallel mechanism are introduced first to implement concept design of a 3-R(4S) &3-SS parallel robot. The kinematic modeling of the robot is carried out, and the performance indexes of the robot are calculated via Jacobian matrix, on the basis of which, the 3D spatial overall workspace can be quantified and visualized, under the constraints of limited rod, to avoid the singular position. The error of the robot is described, and a probabilistic error model is hereby developed to classify the hybrid error sensitivity of each independent uncertain error source by Monte Carlo stochastic method. Most innovatively, a methodology called UHTA is proposed to optimize the robot precision, and the tolerance allocation approach is conducted to reduce the overall error amplitude and improve the robotized positioning precision, on the premise of not increasing assembly cost.

The proposed approach is validated by digital simulation of medical puncture robot. The experiment highlights the mathematical findings that the horizontal plane positioning error of the parallel robotic mechanism can be effectively reduced after using UHTA, and the average precision can be improved by up to 39.54%.

The originality lies in UHTA-based precision design method for parallel robots. The proposed method has widely expanding application scenarios in industrial robots, biomedical robots and other assembly automation fields.