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The purpose of this paper is to apply a factorization‐based control system design procedure to design of auto‐pilot systems.

The design approach is based on a previously developed factorization‐based control system design procedure. The design approach requires a stable coprime factorization of the plant, a set of stable coprime factors that are solutions to the Bezout identity, the linear model of a desired response, and the desired frequency range of interest. When all this information is provided, the developed automated software outputs a candidate auto‐pilot whose performance should be verified.

For a specific class of aerospace vehicles, it is found that the described factorization‐based auto‐pilot design procedure may replace the presently complicated auto‐pilot design procedures. The final design is simpler than other techniques that are based on classical, robust, adaptive, QFT, gain scheduling, or interpolation techniques, and the total required man hours for the design loop is less than the mentioned alternative approaches.

There are two basic limitations – time variations of plant parameters must not be very large as is the case with the agile aerospace vehicles, and specification of the desired closed‐loop system behavior is not systematic.

The major outcome of this research is that complicated autopilots of a class of aerospace vehicles may be replaced by simpler systems with competitive performance.

This is the first paper in the area of autopilot design that is based on the application of a simple factorization‐based design procedure.

With the increasing use of Internet and mobile handsets, mobile-based electronic payment apps (MEPAs) are becoming very popular around the world due to having various advantages. The intention of this exploratory study is to investigate the role/impact of selected factors in adopting three MEPAs of China: Wechat, Alipay and UnionPay based on the extended technology acceptance model (ETAM). After conducting a thorough and careful literature review, this study identified and divided seven such factors into three broad categories: (1) technological factors: perceived ease of use (PEU) and perceived usefulness (PU); (2) personal factors: perceived trust (PT), perceived privacy (PP) and perceived risk (PR); and (3) social factors: social influence (SI) and peer influence (PI) that were assumed to affect the intention to adopt MEPAs (IAMEPAs).

1,597 Chinese individuals were selected through purposive sampling technique who regularly used MEPAs at the time of collecting data. For collecting primary data from the selected respondents, a cross-sectional survey instrument was used. The study utilized IBM SPSS 25 for descriptive statistics and a second generation covariance-based structural equation modeling (CB-SEM) technique through AMOS 25 for testing the hypothesized relationships.

From statistical analysis, it was identified that five factors: PEU, PU, PT, SI and PI have significant positive impact on the dependent variable, IAMEPAs while PR and PP have insignificant influence on IAMEPAs.

This is one of the studies ever conducted to discover the factors that can have impact on the adoption of MEPAs using ETAM. It is strongly expected that this exploratory study can motivate the scholars to commence additional investigations regarding this increasingly popular financial technology (Fin-Tech). In addition, it can be anticipated that the MEPA service providers can widen their service effectiveness according to the users’ opinion reflected in this study. Furthermore, policymakers involved with Fin-Tech can also formulate and implement effective policies and guidelines based on the empirical outcomes.