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The paper aims to overcome the shortcomings that proportional‐integral‐derivative (PID) control for unmanned robot applied to automotive test (URAT) needs a priori manual retuning, has large speed fluctuations and is hard to adjust control parameters. A novel control approach based on fuzzy neural network applied to URAT was proposed.

According to the target vehicle speed and driving command table, the multiple manipulator coordinated control model was established. After that, the displacement of throttle mechanical leg, clutch mechanical leg, brake mechanical leg and shift mechanical arm for URAT was used as input of fuzzy neural network (FNN) model, and vehicle speed was used as output of FNN model. The number of membership functions was three, and the type of that was generalized bell membership function (gbellmf). The hybrid learning algorithm which combined with back propagation algorithm and least square method was applied to train the model. The Sugeno model was selected as fuzzy reasoning model.

Experimental results demonstrated that compared with PID control method, the proposed approach can greatly improve the accuracy of vehicle speed tracking. The approach can accurately realize the vehicle speed tracking of given driving test cycle. Therefore, it can ensure the accuracy and effectiveness of automotive test results.

Future work will focus on improving the efficiency of this learning algorithm.

The paper provides effective methods for improving the accuracy of speed tracking and repeatability.

After establishing the multiple manipulator coordinated control model, this paper proposes a novel control approach based on FNN for URAT.

This research aims to provide new empirical evidence, showing that trivial attributes can exert a significant impact on product evaluation when they help to fulfill non-consumption goals (goal that goes beyond functional benefits).

The research presents two experimental studies that investigate the role of trivial product attributes in various non-consumption contexts.

Trivial attributes can have a significant impact on product evaluation when they help to fulfill non-consumption goals. First, in the non-competitive versus competitive choice settings, a trivial attribute becomes more important when it helps to make a choice (i.e. a non-consumption goal). Second, in the low versus high social risk settings, a trivial attribute becomes more important when it helps to reduce a social risk (i.e. a non-consumption goal). In addition, self-confidence is a moderator, which regulates consumers’ ability to rely on trivial attributes in making product choices.

The social risk manipulations (high vs low) were operationalized by manipulating the impression motive related to social risk. The more important a goal is, the more risk consumers feel in decision making (Lazarus, 1991). Therefore, risk is a proxy of the goal strength or goal relevance. Future research is needed to examine goal strength’s sole influence on the perception of the trivial attribute.

From managerial perspective, trivial attributes can help companies to improve their sales. For example, a way to increase an attribute’s importance is to put the product in a competitive setting. Increasing a social risk further increases the influence of trivial attributes. When less confident consumers perceive the social risk is high, they prefer a brand with a trivial attribute. For consumers, the findings also suggest that consumers should not be tempted to consider trivial attributes in their purchase decisions. Reconsidering attributes and increasing self-confidence could help maintain focus on non-trivial attributes.

The study makes several contributions to theory and practice. This is the first study to systematically propose a framework of how trivial attributes’ role in product evaluation and choice change based on goals. The paper clarifies confusions about the definitions of trivial attributes and reconciles contradictory findings in literature. A trivial attribute can be instrumental in evaluation and choice when it helps to achieve a non-consumption goal. It is also the first study to introduce social risks into trivial attributes research in choices. The findings provide empirical evidence that social risks and self-confidence together drive consumers to prefer for trivial attribute.

This paper aims to construct an argument in support of the idea that absorptive capacity may lead to improved transactive memory conditional to the effectiveness of knowledge transfer between team members.

The study reports on the results of data collected from 10 knowledge worker teams in a business-to-business context across various industries. The study tests a theoretical model to consider the relationship between the dimensions of absorptive capacity, knowledge transfer effectiveness and transactive memory systems.

At the individual level, the results suggest that knowledge acquisition and assimilation is associated with higher levels of knowledge transfer while unstructured knowledge transfer is associated with specialisation, credibility and coordination that drives transactive memory.

The results suggest that an alternative conceptualisation of the relationship between absorptive capacity, knowledge transfer effectiveness and transactive memory systems is indeed conceivable. This implies that transactive memory can benefit from increased absorptive capacity and enhanced knowledge transfer effectiveness and may point at an under-explored avenue of research.

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).