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The purpose of this paper is to explore the motivations of consumers engage with fashion retail applications (apps) from a consumer motivation perspective to inform the design for fashion retail apps. This is an area with increasing economic significance, yet of limited academic research to date.

Through 18 in-depth qualitative interviews, utilitarian stimuli was identified as primary motivating factor to attract customers to shop for fashion garments through m-commerce retail apps.

Results from thematic analysis identified that the utilitarian elements of “efficiency” and “convenience” were two of the most important motivators for engagement, with “personalized services”, and “convenient operation process” also dominant functions to attract customers to shop on m-commerce retail apps. While “Social” shopping was shown to be a motivating factor for consumer behaviour, participants showed greater preference to interpersonal communications channels than to social media.

Findings from this study reveal the utilitarian focus of fashion retail apps within an industry often focussed on experiential interactions, and provide a focus for fashion retail m-commerce app designers to tailor their products for higher consumer engagement. Future apps should be designed specifically with this in mind to increase the chance of consumer engagement.

This paper provides original insight into the hedonic and utilitarian value motivations most prevalent to users of m-commerce fashion retail apps. This is distinct from previous research that has focussed on physical retail environments or general e-commerce interactions (e.g. non-fashion web stores accessed through a PC/laptop).

The classification of aircraft failures has been a significant part of functional hazard analysis (FHA). Aiming at the shortcomings of the traditional FHA method in the evaluation of aircraft risk, the purpose of this paper is to put forward a new approach by combining the gray comprehensive relation calculation method in the gray system theory with the traditional FHA in order to deal with the problem of “little data, poor information.”

This paper combines FHA, 1–9-scale method and gray relation analysis. At first, aircraft failure scenarios are chosen and data from experts are collected; then gray system theory is applied to find the relevance of such scenarios. Finally, the classification according to relevance is determined.

In the past, “little data, poor information” made it difficult for researchers to implement FHA. In this paper, the authors manage to deal with the problem of “poor information” and provide an approach to find the seriousness of aircraft failure.

Due to the use of expert-evaluating methods, the classification of failures is still a little subjective and can be improved in this area. In the future, the method can be improved from the perspective of combining FMEA to analyze more complex indicators or using multisource heterogeneous solutions to solve fuzzy numbers, probabilities, gray numbers and indicators that cannot be assigned.

The paper uses FHA to divide the failure state and establishes a gray evaluation model of the aircraft failure state classification to verify the relevant method. Some aircraft safety design requirements are used to check the safety hazards of the aircraft during the design process, and to provide rational recommendations for the functional design of the aircraft.

Improving the safety of aircraft is undoubtedly of great practical significance and has become a top priority in the development of the civil aviation industry. In this paper, the FHA method and the failure state of the aircraft are studied. The original FHA method is innovated by using the gray system theory applicable to the poor information state. Therefore, to some extent, this study has significance for improving the safety of civil aircraft flight, ensuring people’s travel safety and enhancing the society’s trust in civil aviation.

The main innovation of this paper is integrating the FHA method and the gray system theory. This study calculates the comprehensive relation degree of each failure under different flight stages, and uses FHA to divide the failure state, and finally establishes a gray evaluation model of the aircraft failure state classification to analyze the different conditions of the landing gear brake system, so that it improves the present situation, and the problem with the character of “little data, poor information” can be addressed better.