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Images and caption descriptions serve as important visual stimuli that influence consumer preferences; therefore, the current study focuses on property images and captions illustrated on the home pages of accommodation-sharing platforms. Specifically, this study investigates the relative importance of hue, brightness and saturation of a property image and caption description styles on potential consumers’ preferences.

A mixed-method approach was used, and a total of 293 valid responses were collected through a discrete choice experiment approach. Interviews were conducted for additional analyses to explore the detailed explanations.

The utility model demonstrated that the image’s saturation was the most critical attribute perceived by the respondents, followed by caption description style, hue and brightness.

This is one of the first studies to investigate the display of attributes on a digital accommodation platform by exploring potential customers’ stated preferences. This study focuses explicitly on images and captions illustrated on the home page of an accommodation booking platform. Detailed image investigation is also a new research area in sharing economy-related research.

The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size, which is one of the essential issues in qualitative research. The fuzzy logic model is proposed to determine the sample size in qualitative research.

Considering the structure of the problem in the present study, the proposed fuzzy logic model will benefit and contribute to the literature and practical applications. In this context, ten variables, namely scope of research, data quality, participant genuineness, duration of the interview, number of interviews, homogeneity, information strength, drilling ability, triangulation and research design, are used as inputs. A total of 20 different scenarios were created to demonstrate the applicability of the model proposed in the research and how the model works.

The authors reflected the results of each scenario in the table and showed the values for the sample size in qualitative studies in Table 4. The research results show that the proposed model's results are of a quality that will support the literature. The research findings show that it is possible to develop a model using the laws of fuzzy logic to determine the sample size in qualitative research.

The model developed in this research can contribute to the literature, and in any case, it can be argued that determining the sample volume is a much more effective and functional model than leaving it to the initiative of the researcher.

This paper aims to propose a method of parametrizing topological transformer model at high flux densities in the core.

The approach proposed is based on terminal voltages and currents measured in a special purpose saturation test whose data are combined with typical saturation curves of grain-oriented electrical steels; the modeling is carried out in the ATPDraw program.

The authors corroborate experimentally the necessity of dividing the zero sequence impedance between all transformer phases and propose a method of the individual representation of the legs and yokes. This eliminates the use of nonexistent leakage inductances of primary and secondary windings.

The presented modeling approach can be used for predicting inrush current events and in the evaluation of the impact caused by geomagnetically induced currents (GICs).

The proposed approach is completely original and will contribute to a better understanding of the transients occurring in a transformer under abnormal conditions, such as inrush current events and GICs.

This paper aims to propose a semianalytical model of a squirrel-cage induction machine (SCIM), considering local magnetic saturation and eddy-currents induced in the rotor bars.

The regions of the rotor and stator are divided into elementary subdomains (E-SDs) characterized by general solutions at the first harmonic of the magneto-harmonic Maxwell’s equations. These E-SDs are connected in both directions (i.e., along the r- and θ-edges).

The calculation of the magnetic field has been validated for various values of slip and iron permeability. All electromagnetic quantities were compared with those obtained using a two-dimensional finite-element method. The semianalytical results are satisfactory compared with the numerical results, considering both the amplitude and waveform.

Expansion of the recent analytical model (E-SD technique) for the full prediction of the magnetic field in SCIMs, considering the local saturation effect and the eddy-currents induced in the rotor bars.

This paper aims to study the issues of adaptive fuzzy control for a category of switched under-actuated systems with input nonlinearities and external disturbances.

A control scheme based on sliding mode surface with a hierarchical structure is introduced to enhance the responsiveness and robustness of the studied systems. An equivalent control and switching control rules are co-designed in a hierarchical sliding mode control (HSMC) framework to ensure that the system state reaches a given sliding surface and remains sliding on the surface, finally stabilizing at the equilibrium point. Besides, the input nonlinearities consist of non-symmetric saturation and dead-zone, which are estimated by an unknown bounded function and a known affine function.

Based on fuzzy logic systems and the hierarchical sliding mode control method, an adaptive fuzzy control method for uncertain switched under-actuated systems is put forward.

The “cause and effect” problems often existing in conventional backstepping designs can be prevented. Furthermore, the presented adaptive laws can eliminate the influence of external disturbances and approximation errors. Besides, in contrast to arbitrary switching strategies, the authors consider a switching rule with average dwell time, which resolves control problems that cannot be resolved with arbitrary switching signals and reduces conservatism.

In binder jetting, the interaction between the liquid binder droplets and the powder particles defines the shape of the printed primitives. The purpose of this study is to explore the interaction of the relative size of powder particles and binder droplets and the subsequent effects on macro-scale part properties.

The effects of different particle size distribution (5–25 µm and 15–45 µm) of stainless steel 316 L powders and droplet sizes (10 and 30 pL) on part density, shrinkage, mechanical strength, pore morphology and distribution are investigated. Experimental samples were fabricated in two different layer thicknesses (50 and 100 µm).

While 15–45 µm samples demonstrated higher green density (53.10 ± 0.25%) than 5–25 µm samples (50.31 ± 1.06%), higher sintered densities were achieved in 5–25 µm samples (70.60 ± 6.18%) compared to 15–45 µm samples (65.23 ± 3.24%). Samples of 5–25 µm also demonstrated superior ultimate tensile strength (94.66 ± 25.92 MPa) compared to 15–45 µm samples (39.34 ± 7.33 MPa). Droplet size effects were found to be negligible on both green and sintered densities; however, specimens printed with 10-pL droplets had higher ultimate tensile strength (79.70 ± 42.31 MPa) compared to those made from 30-pL droplets (54.29 ± 23.35 MPa).

To the best of the authors’ knowledge, this paper details the first report of the combined effects of different particle size distribution with different binder droplet sizes on the part macro-scale properties. The results can inform appropriate process parameters to achieve desired final part properties.

In spite of the rise of social media influencers observed in the 2010s, the direction and future of influencers are ambiguous. This popular yet overused marketing tool has shown certain problems and limitations such as a decrease in perceived authenticity and market saturation. Additionally, the outbreak of COVD-19 has amplified the significance of these factors and made many companies and influencers reconsider their involvement in influencer marketing. Within this context, this paper aims to explore whether influencers were impacted by diminishing perceived authenticity, market saturation or the prolonged pandemic. Also, the authors aim to investigate influencers’ perception of the future of influencer marketing post-pandemic.

To gain insight into trends in influencer marketing from the influencer’s perspective, this paper uses qualitative research in the form of interviews with influencers and industry professionals.

The findings highlight the importance of perceived authenticity for success in influencer marketing. Most interviewees indicated that they had noticed a boom in social media influencer marketing before the pandemic, yet provided mixed views regarding the market during the pandemic. Several believe that influencers will continue to be relevant in the increasingly digital world (e.g. increasing digital marketing spend and e-commerce), whereas an expectation of new digital platforms and innovations was also observed. In the long term, saturation and decreased effectiveness were predicted by several interviewees.

This under-researched topic is of relevance especially to consumer goods companies, as social media marketing and influencer marketing are currently highly effective and popular tools. To refine marketing strategies designed around influencers, understanding the limitations, in the context of COVID-19, is crucial.

To solve the instability problem of Zhangjiayao landslide caused by rainfall, the internal mechanism of slope instability and the supporting effect of anti-slide piles are studied. The research results can provide theoretical basis for the prevention and control of loess landslides.

A three-dimensional finite element model of Zhangjiayao landslide is established by field geological survey, laboratory test and numerical simulation.

The results show that Zhangjiayao landslide is a loess-mudstone contact surface landslide, and rainfall leads to slope instability and traction landslide. The greater the rainfall intensity, the faster the pore water pressure of the slope increases and the faster the matrix suction decreases. The longer the rainfall duration, the greater the pore water pressure of the slope and the smaller the matrix suction. Anti-slide pile treatment can significantly improve slope stability. The slope safety factor increases with the increase of embedded depth of anti-slide pile and decreases with the increase of pile spacing.

Based on the unsaturated soil seepage theory and finite element strength reduction method, the failure mechanism of Zhangjiayao landslide was revealed, and the anti-slide pile structure was optimized and designed based on the pile-soil interaction principle. The research results can provide theoretical basis for the treatment of loess landslides.

1. A three-dimensional finite element model of Zhangjiayao landslide is established.

2. Zhangjiayao landslide is a loess-mudstone contact surface landslide.

3. The toe of Zhangjiayao slope is first damaged by heavy rainfall, resulting in traction landslide.

4. The deformation of Zhangjiayao slope is highly dependent on rainfall intensity and duration.

5. The anti-slide pile can effectively control the continuous sliding of Zhangjiayao slope.

A three-dimensional finite element model of Zhangjiayao landslide is established.

Zhangjiayao landslide is a loess-mudstone contact surface landslide.

The toe of Zhangjiayao slope is first damaged by heavy rainfall, resulting in traction landslide.

The deformation of Zhangjiayao slope is highly dependent on rainfall intensity and duration.

The anti-slide pile can effectively control the continuous sliding of Zhangjiayao slope.

This paper aims to theorize and investigate the use of effective color features in artificial intelligence (AI) influencers, an emerging marketing trend in the social media context.

By analyzing 6,132 pictures posted by ten AI influencers on Instagram, this paper examines the effect of warm colors in AI influencers’ social media posts on consumer responses, and how other color features may moderate the effect of warm color. In addition, two experimental studies reveal the underlying process driving the effect of warm color.

Warmer color generated more favorable consumer responses, with brightness significantly moderating the relationship between warm color and favorable consumer responses. Moreover, the results of the experiments establish that perceived warmth and emotional trust mediate the causal effect of warm colors on consumer responses.

There is still little understanding about consumer perceptions of AI influencers and their acceptance of AI influencers’ product recommendations. As such, this research offers theoretical understanding of the color features influencing the effectiveness of recommendations by AI influencers.

Brands have started deploying AI influencers as their brand ambassadors to make product recommendations, representing a new wave of advertising on social media. The findings will thus benefit marketers in developing effective product recommendations using AI influencers.

The present research provides a novel understanding of how visual features, such as color can influence the effectiveness of AI influencers.

This paper aims to focus on the assessment of a domestic property's energy performance status by a domestic energy assessor (DEA), to ascertain the possible underlying reasons for variability in the results of Energy Performance Certificates (EPCs). By variability, the authors mean discrepancies in assessment between different DEAs on similar properties. This is important because the uses for the EPC have been extended beyond their original function as an asset rating system, to include themes encompassing building policy decisions, building performance and the distribution of incentives and grants. Consequently, inaccuracies in EPC reporting will have a greater impact than may have been the case at the outset.

A case study approach involving the conducting of semi-structured interviews with 20 practicing DEAs was carried out, with transcribed recordings of the interview material subjected to thematic analysis. This formed part of a wider mixed methods study.

The results identify a wide range of underlying reasons for variability driven by issues in both practice and process, including conflicts of interests, the EPC auditing process, the default inputting of missing data by RdSAP where information may not be available/discoverable by the DEA, the quality and perception of EPCs and DEA training and experience.

The sample size of 20 is by definition limiting, and it is possible that different results would have been obtained from a different sample. Although thematic saturation from the analysis of the responses on the key question of whether EPCs are considered variable does mitigate this. The respondents were all in possession of five years or more experience and of carrying out EPCs for different purposes. Less experienced DEAs may inevitably have responded to questions differently. The thematic analysis gives the researcher control over the presentation of the results, and it is noted that this creates a potential for bias. The researcher is immersed in the world of construction and property, with regular contact with DEAs and EPCs, which may influence the perspective of the results.

The research identifies risks to the accuracy of EPCs. To this end, and with the specific research findings in mind, this research may be of interest to construction professionals with respect to EPC practice and procurement, to the Accrediting Bodies who audit EPCs, to the creators of RdSAP with respect to automated EPC inputs, to academics either at face value or for use in further research and to policy makers who may wish to consider RdSAP data in future with qualifiers or margins of error, or may even look to review the EPC as the instrument of choice for some applications.

There is much literature analysing the shortcomings and nuances of RdSAP results, and the software model that generates the EPC, but only very limited literature extending the discussion about RdSAP to its operator: the DEA. At the time of writing, there is no literature focusing directly on the DEA and its role within the EPC production process. Their role is more important now, given the expanding use of EPCs, and increased reliance on EPC data.