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The objective of this study was to develop wearable suit platforms with various anchoring structure designs with the intention of improving wearability and enhancing user satisfaction.

This study selected fabrics and materials for the suit platform through material performance tests. Two anchoring structure designs, 11-type and X-type are compared with regular clothing under control conditions. To evaluate the comfort level of the wearable suit platform, a satisfaction survey and electroencephalogram (EEG) measurements are conducted to triangulate the findings.

The 11-type exhibited higher values in comfort indicators such as α, θ, α/High-β and lower values in concentration or stress indicators such as β, ϒ, sensorimotor rhythm (SMR)+Mid-β/θ, and a spectral edge frequency of 95% compared to the X-type while walking. The 11-type offers greater comfort and satisfaction compared to the X-type when lifting based on the EEG measurements and the participants survey.

It is recommended to implement the 11-type when designing wearable suit platforms. These findings offer essential data on wearability, which can guide the development of soft wearable robots.

Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.

This study aims to investigate the fit of a promotion (prevention) focus with malicious (benign) envy and how this fit influences positive and negative behaviours, depending on the context.

Four empirical studies (two laboratory and two online experiments) were used to test key hypotheses. Study 1 manipulated regulatory focus and envy in a job application setting with university students. Study 2 engaged similar manipulations in a social media setting. Studies 3 and 4 extended the regulatory focus and envy manipulations to the general population in pay-what-you-want (PWYW) and pay-it-forward (PIF) restaurant contexts.

The findings showed that a promotion (prevention) focus fits with the emotion of malicious (benign) envy. In the social media context, promotion and prevention foci demonstrated negative behaviour, including unfollowing the envied person, when combined with malicious and benign envy. In the PWYW and PIF contexts, combining envy with a specific type of regulatory focus encouraged both positive and negative behaviours through influencing payments.

Future research could validate and extend this study’s findings with different product/service categories, cross-cultural samples and research methods such as field experiments.

The four studies’ findings will assist managers in formulating marketing strategies to enhance their positioning of target products/services, possibly leading to higher prices for PWYW and PIF businesses.

The conceptual model is novel as, to the best of the authors’ knowledge, no prior research has proposed and tested the fit between envy type and regulatory foci.

This study aims to construct a sentiment series generation method for danmu comments based on deep learning, and explore the features of sentiment series after clustering.

This study consisted of two main parts: danmu comment sentiment series generation and clustering. In the first part, the authors proposed a sentiment classification model based on BERT fine-tuning to quantify danmu comment sentiment polarity. To smooth the sentiment series, they used methods, such as comprehensive weights. In the second part, the shaped-based distance (SBD)-K-shape method was used to cluster the actual collected data.

The filtered sentiment series or curves of the microfilms on the Bilibili website could be divided into four major categories. There is an apparently stable time interval for the first three types of sentiment curves, while the fourth type of sentiment curve shows a clear trend of fluctuation in general. In addition, it was found that “disputed points” or “highlights” are likely to appear at the beginning and the climax of films, resulting in significant changes in the sentiment curves. The clustering results show a significant difference in user participation, with the second type prevailing over others.

Their sentiment classification model based on BERT fine-tuning outperformed the traditional sentiment lexicon method, which provides a reference for using deep learning as well as transfer learning for danmu comment sentiment analysis. The BERT fine-tuning–SBD-K-shape algorithm can weaken the effect of non-regular noise and temporal phase shift of danmu text.

This research delves into the dynamic realm of app design by examining the impact of app icon familiarity and authority on image fit, influencing users' app usage intention. Focusing on the distinctive circumstances of Chinese and Korean customers, the study aims to provide insightful information about how application user behavior changes.

Utilizing structural equation modeling, the study employs data from 293 Korean and Chinese consumers. The research design incorporates a thoughtful approach, including parallel translation methods, focus group interviews, and pre-experimental testing to ensure survey accuracy and validity. The study strategically selects stimuli from the Apple App Store rankings, emphasizing icon features and type considerations.

The results provide important new information about the connections between usage intention, image fit, authority, and familiarity with app icons. Notably, app icon familiarity and authority positively influence image fit. Furthermore, app icon image fit emerges as a positive predictor of usage intention, mediating the complex interplay between familiarity, authority, and intention. The study also identifies moderating effects, shedding light on the nuanced role of app icon features and types.

Originating from a comprehensive exploration of icons, this study significantly contributes to the field by exploring icon differences and uncovering the intricate mechanisms guiding users' decisions. The findings offer valuable insights for app designers, marketers, and researchers seeking a deeper understanding of user behavior in diverse cultural contexts, thereby enhancing the theoretical and practical foundations in app usability and consumer behavior.

The importance of service firms cooperating with digital platforms is widely acknowledged. The authors study three contractual relationships (fixed-cost, cost-sharing, and profit-sharing) between service firms (specifically hotels) and digital platforms in a highly fragmented service supply chain to examine which of these contract types optimizes profits.

The authors extend prior models analyzing the optimal expected total profit from the travel service firm (hotel)–digital platform relationship, providing new insights into each contract type’s ability to coordinate decentralized systems and optimize profits for both parties.

This study finds that fixed cost contracts cannot coordinate the decentralized system. Cost-sharing contracts can coordinate the decentralized system but only allow one channel profit split. In contrast, profit-sharing contracts may not always perfectly coordinate the decentralized system but support alternative profit allocations. Practically, both profit-sharing and cost-sharing contracts are preferable to fixed-cost contracts.

The paper includes implications for travel service firm managers to consider when structuring contracts with digital platforms to focus on profit optimization. Profit-sharing contracts are most preferable when cost and revenue data are fully shared between parties, while cost-sharing contracts are preferable over fixed-cost contracts.

This study extends prior investigations into the utility of different contract types on the optimal profit of a travel service firm (hotel)-digital platform provider relationship. The research fills a gap in the literature concerning the contracts used in these relationship types.

This study aims to minimize the cost and time of blood delivery in the whole blood supply chain network (BSCN) in disaster conditions. In other words, integrating all strategic, tactical and operational decisions of three levels of blood collection, processing and distribution leads to satisfying the demand at the right time.

This paper proposes an integrated BSCN in disaster conditions to consider four categories of facilities, including temporary blood collection centers, field hospitals, main blood processing centers and medical centers, to optimize demand response time appropriately. The proposed model applies the location of all permanent and emergency facilities in three levels: blood collection, processing and distribution. Other essential decisions, including multipurpose facilities, emergency transportation, inventory and allocation, were also used in the model. The LP metric method is applied to solve the proposed bi-objective mathematical model for the BSCN.

The findings show that this model clarifies its efficiency in the total cost and blood delivery time reduction, which results in a low carbon transmission of the blood supply chain.

The researchers proposed an integrated BSCN in disaster conditions to minimize the cost and time of blood delivery. They considered multipurpose capabilities for facilities (e.g. field hospitals are responsible for the three purposes of blood collection, processing and distribution), and so locating permanent and emergency facilities at three levels of blood collection, processing and distribution, support facilities, emergency transportation and traffic on the route with pollution were used to present a new model.

Social media has significantly impacted the value creation processes within the consumer–brand relationship. This study aims to examine value formation processes within a cosmetics social media brand community and to establish the types of value formation associated with different categories of interactions within a social media brand community.

The research adopted a netnographic approach and followed the operational protocols of netnography. Conversations in one large cosmetics social media brand community were observed and downloaded for analysis over a two-month period. Examples of value-creation and formation processes were identified using netnographic interpretative procedures to develop higher-order themes.

The findings supported the creation of a “Consumer and brand value creation and co-creation framework” highlighting disparate value types within the following interactions: consumer-to-consumer; brand-to-consumer; and consumer-to-brand. The identified value types were specific to the actors (i.e. consumers and brands) involved in value formation processes. The analysis also revealed consumers’ ability to independently generate value through direct interaction with a social media brand community and the brands’ role in supporting consumers in value formation through value facilitation.

The pivotal role of disparate actors’ interactions in value formation processes is highlighted, alongside the autonomous ability to form value with the aid of resources stored and shared within the social media brand community. The network of interactions and value-creation processes contribute to a holistic understanding of the interactions in a social media brand community. Furthermore, the research explores and highlights the emerging role of social media brand communities as “value vestiges”.

The digital transformation is dramatically changing the business-to-business (B2B) sales environment, challenging long-standing views regarding the critical competencies required of salespeople. This paper aims to explore the personal traits associated with sales performance in a digital selling environment.

Using template analysis, the researchers captured and coded over 21 h of in-depth, semi-structured interviews with senior sales leaders from various industry sectors, exploring their perceptions of the personal traits now required of B2B salespeople in the digital landscape.

The research identifies three high-level trait types critical to sales success within a digital selling environment: “analytical curiosity” – the natural motivation and ability to gather and synthesize sales-related knowledge, “empathetic citizenship” – the ability to establish initial rapport while building long-term trust and “disciplined drive” – the exertion of selling effort in a highly focused and methodical manner across all stages of the sales process.

The present data came from interviews with sales leaders in Canada. A more global sample may lead to additional insights. Moreover, the sample was drawn from long-cycle B2B sales environments; conclusions may differ for short-cycle or business-to-consumer markets.

This paper presents a framework for hiring and developing salespeople in the digital sales environment, identifying personal trait types that sales leaders should look for when hiring: analytical curiosity, empathetic citizenship and disciplined drive. The paper identifies how these trait types influence sales success, suggesting that sales leaders could coach and educate their teams to make the best use of them.

This paper presents a conceptual framework for hiring in the digital sales environment and introduces the trait of analytical curiosity not previously discussed in the literature.

Trust plays a crucial role in overcoming uncertainty and reducing risks. Uncovering the trust mechanism in the sharing economy may enable sharing platforms to design more effective marketing strategies. However, existing studies have inconsistent conclusions on the trust mechanism in the sharing economy. Therefore, this study aims to investigate the antecedents and consequences of different dimensions of trust (trust in platform and trust in peers) in the sharing economy.

First, we conducted a meta-analysis of 57 related articles. We tested 13 antecedents of trust in platform (e.g. economic benefits, enjoyment, and information quality) and eight antecedents of trust in peers (e.g. offline service quality and providers’ reputation), as well as their consequences. Then, we conducted subgroup analyses to test the moderating effects of economic development level (Developed vs Developing), gender (Female-dominant vs Male-dominant), platform type (Accommodation vs Transportation), role type (Obtainers vs Providers), and uncertainty avoidance (Strong vs Weak).

The results confirm that all antecedents and consequences significantly affect trust in platform or peers to varying degrees. Moreover, trust in platform greatly enhances trust in peers. Besides, the results of the moderating effect analyses demonstrate the variability of antecedents and consequences of trust under different subgroups.

This paper provides a clear and holistic view of the trust mechanism in the sharing economy from an object-based trust perspective. The findings may offer insights into trust-building in the sharing economy.