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Insights into how fan experience can be used to cultivate football (soccer) fan loyalty are limited. Based on the stimulus–organism–response (S-O-R) paradigm, this study develops and tests a theoretical model investigating the effects of football-game socialisation, team interest, football interest and transaction satisfaction (stimuli) on fanship and cumulative satisfaction (organism), and subsequently, attitudinal loyalty and behavioural loyalty (response). National culture was a moderator.

A self-administered online survey collected data from a convenience sample of 762 football fans from Brazil, China and Germany.

The PLS-SEM results support the S-O-R based model, indicating that football fan-loyalty behaviours are determined by fanship and cumulative satisfaction with the team. Fan experiences, in turn, are also found to be influenced by fan perceptions relating to socialisation, team interest, football interest and transaction satisfaction—elements over which the football team's management may exert some degree of control. Some national cultural differences were found, with three of the model's 12 structural paths significantly different for Germany vis-à-vis Brazil.

This study advances the authors’ understanding of the significance of socialisation and fan-interest factors for football, providing evidence supporting the role of the fan experience and service-consumption stimuli related to those game experiences as significant drivers (stimuli) of the fan's affective (fanship) and cognitive states (cumulative satisfaction). This study enriches the limited body of evidence on fanship's role as a driver of attitudinal and behavioural loyalty. Finally, the multi-country study partially supports the moderation effect of national culture.

It is well-known that consolidation rate of prefabricated vertical drain (PVD)-installed ground is closely related to the discharge capacity of PVD, which decreases with an increase in effective stress. This paper aims to present consolidation behaviors of PVD-improved ground considering a varied discharge capacity of PVD.

A simple equivalent vertical hydraulic conductivity (k′_ve method) was proposed in plane strain numerical analysis, in which the effect of decreased discharge capacity with depth was considered. Numerical analysis was applied to analyze field behaviors of test embankment of soft mucky deposit.

Finite element method results indicated that consolidation behaviors of PVD-improved soil with a nonlinear distribution of discharge capacity with depth were in a good agreement with the observed field behaviors, compared with those with a constant discharge capacity and a linear distribution of discharge capacity. At a given time and depth, the consolidation rate in the case of discharge capacity with a nonlinear distribution is lower than that of a linear or constant distribution.

A geotechnical engineer could use the proposed method to predict consolidation behaviors of drainage-installed ground.

Consolidation behaviors of PVD-installed ground could be reasonably predicted by using the proposed method with considering effect of discharge capacity reduction.

Neuroimaging technologies such as electroencephalogram and magnetic resonance imaging allow us to analyze consumers’ brains in real time as they experience emotions. These technologies collect and integrate data on consumers’ brains for big data analytics. The purpose of this paper is to identify new opportunities and challenges for neuromarketing as an applied neuroscience.

The authors discuss conceptual and methodological contributions of neuromarketing based on studies that have employed neural approaches in market-related investigations, explaining the various tools and designs of neuromarketing research. The authors identify marketing-related questions to which neuroscientific approaches can make meaningful contributions, evaluating several challenges that lie ahead for neuromarketing.

The authors summarize the contributions of neuromarketing and discuss synergistic findings that neuromarketing has the potential to yield.

The authors ask: do consumers’ self-reported choices and their neural representations tell different stories?; what are the effects of subtle and peripheral marketing stimuli?; and can neuromarketing help to reveal the underlying causal mechanisms for perceptual and learning processes, such as motivation and emotions?

The authors identify marketing-related questions to which neuroscientific approaches can make meaningful contributions, evaluating several challenges that lie ahead for neuromarketing.

To the best of the authors’ knowledge, no current review has identified avenues for future research in neuromarketing and the emerging challenges that researchers may face. The current paper aims to update readers on what neuroscience and other psychophysiological measures have achieved, as well as what these tools have to offer in the field of marketing. The authors also aim to foster greater application of neuroscientific methods, beyond the more biased/post-test methods such as self-report studies, which currently exist in consumer research.

The purpose of the paper is to contribute to the extant sport marketing literature by positing fan engagement, team brand image and cumulative fan satisfaction with the team as factors influencing attitudinal and behavioural soccer (football) fan loyalty, with enduring involvement with the team as a moderator.

A convenience sample of Australian A-League soccer fans completed a paper-and-pencil, self-administered survey to evaluate their team on the focal constructs. A total of 207 participants were recruited from a major Australian east-coast university.

Using partial least squares-structural equation modelling (PLS-SEM), the study found that fan engagement influences both team brand image and cumulative fan satisfaction, while team brand image also influences cumulative fan satisfaction, and both of these constructs influence attitudinal loyalty and behavioural loyalty. The moderating role of enduring involvement was also found for two relationships: team brand image → attitudinal loyalty and team brand image → behavioural loyalty, along with a mediating role of attitudinal loyalty.

This study increases our understanding of the reasons why soccer fans are committed to and exhibit fan-related behaviours for a team, thus contributing to the sports-marketing literature on the relationships amongst fan engagement, team brand image, cumulative fan satisfaction, attitudinal loyalty and behavioural loyalty, along with the moderating role of enduring involvement. The findings also assist sports-marketing practitioners to formulate more effective, fan-centric marketing-communication strategies leading to a larger loyal fan base.

This study investigates the key factors that influence customer satisfaction when interacting with augmented reality shopping assistance applications (ARSAPs). ARSAPs grant consumers the capability to experience products in a virtually simulated user environment before product acquisition. With the development of mobile e-commerce due to breakthroughs in smartphone and augmented reality (AR) technologies, there is an increasing potential for these emergent AR mobile services, yet there is a need for further improvement.

This study initially explored the key satisfaction factors for ARSAPs by utilizing topic modeling of a collection of actual user reviews. These factors are subsequently revisited and complemented by existing literature, and finally verified through logistic regression analysis supported by sentiment analysis.

This study identified the key factors that influence customer satisfaction with ARSAPs, including visuality, sense of reality, credibility, format, completeness, understandability, relevance, flexibility, response time, reliability, availability, ease of use and privacy. In particular, two additional factors (i.e. visuality and sense of reality) were newly identified as important in the context of AR, despite their previous omissions in existing literature.

This study is the first to investigate the key factors that influence customer satisfaction with ARSAPs from users' perspectives, utilizing topic modeling of a large amount of real-world data on actual user feedback. By identifying new factors (i.e. visuality and sense of reality) that were not identified in previous literature, this study provides important academic implications for a broader understanding of AR and related technologies that are essential elements of the metaverse. This study also provides valuable insights for developers and companies in the e-commerce industry on how to optimize AR applications and develop more targeted and effective marketing strategies in this field.

The purpose of this paper is to develop and analyze a new multiple hypothesis receiver autonomous integrity monitoring (RAIM) algorithm, which can handle simultaneous multiple ramp failures.

The proposed algorithm uses measurement residuals and satellite observation matrices of several consecutive epochs for failure detection and exclusion. It detects failures by monitoring the error vector rather than a projection of the error vector. The algorithm assumes that magnitude of range errors can vary with time, while the conventional sequential multiple hypothesis RAIM algorithm assumes that range errors are constant biases.

The algorithm can detect any instance of multiple failures, including failures that cannot be detected by the conventional RAIM algorithm. It can detect multiple failures with magnitudes of several tens of meters, even though the algorithm must solve an ill-conditioned problem. And it can also deal with ramp failures which cannot be detected by conventional sequential multiple hypothesis RAIM algorithm. The detection capability of the proposed algorithm is not dependent on satellite geometry or types of errors.

Implications for the development of the RAIM algorithm for aviation users are included. In particular, it can be a candidate for a future standard architecture in multiple constellations, multiple frequency and satellite-based augmentation system users.

A new multiple hypothesis RAIM algorithm with a relative RAIM concept is proposed. Also presented is a detailed explanation of the algorithms, including rigorous mathematical expressions, and an analysis of differences in detection capability between the conventional multiple hypothesis RAIM algorithm and proposed algorithm.

This paper aims to develop and analyse a new multiple-hypothesis receiver autonomous integrity monitoring (RAIM) algorithm. The proposed algorithm can handle simultaneous multiple failures as well as a single failure.

The proposed algorithm uses measurement residuals and satellite observation matrices of several consecutive epochs for failure detection and exclusion. It detects failures by monitoring the error vector itself instead of monitoring the projection of the error vector. The algorithm reduces the minimum detectable bias via the relative receiver autonomous integrity monitoring (RRAIM) scheme.

The algorithm is able to detect any instance of multiple failures, including failures that are not detected by the conventional RAIM algorithm. It is able to detect multiple failures with magnitudes of several tens of meters, although the algorithm has to solve an ill-conditioning problem. The detection capability of the proposed algorithm is not dependent on satellite geometry.

The algorithm assumes that the error vectors in three consecutive epochs have biases of similar magnitude. As a result, although the algorithm detects occurrences of drifting error, it cannot identify which measurement(s) has the critical error.

The paper includes implications for the development of the RAIM algorithm for aviation users. Especially, it can be a candidate for future standard architecture in multiple constellations, multiple frequency satellite-based augmentation system (SBAS) users.

The paper proposes a new multiple-hypothesis RAIM algorithm with an RRAIM concept. A detailed explanation of the algorithms, including rigorous mathematical expressions, is presented. The paper also includes an analysis of differences in detection capability between conventional algorithm and the proposed algorithm depending on satellite geometry.

This paper aims to introduce the principle of the mask exposure and scanning stereolithography (MESS) and to develop a simulation code to analyze the MESS process.

Photopolymerization is a key reaction in stereolithography. It brings about molecular linkage and releases exothermic temperature. The shrinkage effect is the major cause of prototype deformation, and the shrinkage resulting from scanning and mask exposing is different. It is important to analyze the inaccuracy of each curing layer after the mask exposing in order to optimize the scanning parameters. A simulation code, based on dynamic finite element method, to analyze the shrinkage effect in accordance with scanning path and mask exposure pattern. A benchmark model has been proposed to validate the implementation of the developed code.

The simulation results show that the developed code can analyze the deformation in laser scanning, masking exposing and the MESS process. In benchmark model study, the sharp corner shrinks faster than rounded edge in mask pattern curing. Although the profile scanning can maintain the high accuracy in the MESS process, the residual stress is easily discovered inside of the sharp corner.

The developed simulation code can be applied for optimizing scan path and exposing time due to the analysis process in accordance with the drawing path and fabrication parameters.