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Considering both online and offline service scenarios, this study aims to explore the factors affecting doctors' intention to offer consulting services in eHealth and compare the factors between the free- and paid-service doctors. The theory of reasoned action and social exchange theory are integrated to develop the research model that conceptualizes the role of extrinsic motivations, intrinsic motivations, costs, and attitudes in doctors' behavioral intentions.

Partial least square structural equation modeling (PLS-SEM) was leveraged to analyze 326 valid sample data. To provide robust results, three non-parametric multigroup analysis (MGA) methods, including the PLS-MGA, confidence set, and permutation test approaches, were applied to detect the potential heterogeneity between the free- and paid-service doctors.

The results with overall samples reveal that anticipated rewards, anticipated associations, anticipated contribution, and perceived fee are all positively related to attitude, which in turn positively influences behavioral intention, and that perceived fee positively moderates the relationship between attitude and behavioral intention. Attitude's full mediation is also confirmed. However, results vary between the two groups of doctors. The three MGA approaches return relatively convergent results, indicating that the effects of anticipated associations and perceived fee on attitude are significantly larger for the paid-service doctors, while that of anticipated rewards is found to be significantly larger for the free-service doctors.

eHealth, as a potential contactless alternative to face-to-face diagnoses, has recently attracted widespread attention, especially during the continued spread of COVID-19. Most existing studies have neglected the underlying heterogeneity between free- and paid-service doctors regarding their motivations to engage in online healthcare activities. This study advances the understanding of doctors' participation in eHealth by emphasizing their motivations derived from both online and offline service scenarios and comparing the differences between free- and paid-service doctors. Besides, horizontally comparing the results by applying diverse MGA approaches enriches empirical evidence for the selection of MGA approaches in PLS-SEM.

The purpose of this paper is to develop a proportional-integral-derivative-based fuzzy neural network (PIDFNN) with elitist bacterial foraging optimization (EBFO)-based optimal membership functions (PIDFNN-EBFO) position controller to control the voice coil motor (VCM) for tracking reference trajectory accurately.

Because the control characteristics of the VCM are highly nonlinear and time varying, a PIDFNN, which integrates adaptive PID control with fuzzy rules, is proposed to control the mover position of the VCM. Moreover, an EBFO algorithm is further proposed to find the initial optimal fuzzy membership functions for the PIDFNN controller.

Due to the gradient descent method used in back propagation (BP) to derive the on-line learning algorithm for the PIDFNN, it may reach the local optimal solution due to the inappropriate initial values. Hence, a hybrid learning method, which includes BP and EBFO algorithms, is proposed to improve the learning performance of the PIDFNN controller.

Future work will consider reducing the computational burden of bacterial foraging optimization algorithm for on-line parameters optimization.

The real-time control system is implemented on a 32-bit floating-point digital signal processor (DSP). The experimental results demonstrate the favorable effectiveness of the proposed PIDFNN-EBFO controlled VCM system.

A new PIDFNN-EBFO control scheme is proposed and implemented via DSP for real-time VCM position control. The experimental results show the superior control performance of the proposed PIDFNN-EBFO compared with the other control systems.

The purpose of this paper is to propose and demonstrate a new additive manufacturing approach that breaks the layer-based point scanning limitations to increase fabrication speed, obtain better surface finish, achieve material flexibility and reduce equipment costs.

The freeform additive manufacturing approach conceptually views a 3D article as an assembly of freeform elements distributed spatially following a flexible 3D assembly structure, which conforms to the surface of the article and physically builds the article by sequentially forming the freeform elements by a vari-directional vari-dimensional capable material deposition mechanism. Vari-directional building along tangential directions of part surface gives surface smoothness. Vari-dimensional deposition maximizes material output to increase build rate wherever allowed and minimizes deposition sizes for resolution whenever needed.

Process steps based on geometric and data processing considerations were described. Dispensing and forming of basic vari-directional and vari-dimensional freeform elements and basic operations of joining them were developed using thermoplastics. Forming of 3D articles at build rates of 2-5 times the fused deposition modeling (FDM) rate was demonstrated and improvement over ten times was shown to be feasible. FDM compatible operations using 0.7 mm wire depositions from a variable exit-dispensing unit were demonstrated. Preliminary tests of a surface finishing process showed a result of 0.8-1.9 um Ra. Initial results of dispensing wax, tin alloy and steel were also shown.

This is the first time that both vari-directional and vari-dimensional material depositions are combined in a new freeform building method, which has potential impact on the FDM and other additive manufacturing methods.

This study examines whether relational capital influences self-disclosure behavior through the mechanism of needs-based motivation in virtual communities.

This study adopts hierarchical linear model (HLM) to differentiate between the relationships at different levels, with 378 online questionnaires recovered from 42 virtual communities.

The results show that group-level relational capital is positively related to self-disclosure and affects it through the partially mediating mechanism of motivation. Relational capital also strengthens the positive influence of the need to be on trend on individual self-disclosure behavior.

This study makes four research contributions. Firstly, we identify the means by which relational capital established within a virtual community influences user disclosure behavior. This focus differs from those of previous studies, which have emphasized privacy and security of information systems, cost–benefit considerations, and/or adopted personality traits as the research basis. Secondly, this study examines and verifies the mediating mechanism of motivation, establishing an alternative perspective for theoretical studies, and providing future studies with a reference for investigating the self-disclosure behavior of members. Thirdly, this research introduces and verifies the moderating effects of relational capital based on member relationships, thus making further theoretical and empirical contributions. Finally, we adopt HLM to conduct our analyses, thereby ensuring higher precision regarding the explanatory power of group-level explanatory variables for individual-level dependent variables.

How can governments and survivors prepare for and manage natural disasters? Post-disaster reconstruction researchers advocate that community involvement is needed to help survivors recover effectively. This study aims to propose that cooperative goals between government officials and survivors develop guanxi relationships and constructive controversy wherein survivors voice their opinions to aid disaster recovery.

The authors adopted the critical incident technique (CIT), which has proved especially useful for studying complex issues, as well as site-intensive research for interviews and participant observation. After developing a local reputation and rapport by working in a residential resettlement area for two months, an author used the CIT to ask 118 survivors of the 2008 Sichuan earthquake to describe specific incidents when they interacted with government officials about recovery issues and then to rate survey items that measure independent and dependent variables.

Results, including structural equation analyses, support the reasoning that cooperative goals between government and survivors facilitate guanxi and constructive controversy, which in turn produced effective disaster recovery, as indicated by survivors’ social support, satisfaction, reduced stress and beliefs that government officials led effectively.

The data are self-reported and subject to biases and may not be accurate.

In addition to developing theoretical understanding, the results can have important practical implications for strengthening relationships and constructive controversy between government and survivors.

Results suggest that communities have practical ways to prepare for disasters. Structuring cooperative goals among survivors, encouraging guanxi relationships, and training in constructive controversy should promote effective recovery from natural disasters.

The paper develops theory and research on how leaders can promote community involvement for effective disaster management. The paper proposes that high-quality interpersonal relationships, also referred to guanxi, and the open-minded discussion of opposing ideas, labeled constructive controversy, are major components of effective community involvement. The paper adds to the literature by empirically documenting the utility of the Western-developed theory of cooperation and competition and the concept of constructive controversy for understanding the effectiveness of government leadership for disaster recovery in China.

The purpose of this study was to investigate the participants' attitudes toward the ethical issues caused by collecting social media data (SMD) for research, as well as the effects of familiarity, trust and altruism on the participants' attitudes toward the ethics of SMD research. It is hoped that through this study, scholars will be reminded to respect participants and engage in ethical reflection when using SMD in research.

This study adopted social media users as its research subjects and used Sina Microblog, the world's largest Chinese social media platform, as the example. Based on the 320 valid responses collected from a survey, structural equation modeling was employed to examine the research model.

The results indicated that altruism, familiarity and trust have significant influences on participants' attitudes toward the ethics of SMD research, and familiarity also influences attitudes through the mediating role of trust and altruism.

This study explored the mechanism underlying the relationship between the determining factors and participants' attitudes toward the ethics of SMD research, and the results demonstrated that the informed consent mechanism is an effective way to communicate with participants and that the guiding responsibility of the platform should be improved to standardize SMD research.

In this “Info-plosion” era, recommendation systems (or recommenders) play a significant role in finding interesting items in the surge of online digital activity and e-commerce. The purpose of this paper is to model users' preference evolution to recommend potential items which users may be interested in.

A novel recommendation system, namely evolution-learning recommendation (ELR), is developed to precisely predict user interest for making recommendations. Differing from prior related methods, the authors integrate the matrix factorization (MF) and recurrent neural network (RNN) to effectively describe the variation of user preferences over time.

A novel cumulative factorization technique is proposed to efficiently decompose a rating matrix for discovering latent user preferences. Compared to traditional MF-based methods, the cumulative MF could reduce the utilization of computation resources. Furthermore, the authors depict the significance of long- and short-term effects in the memory cell of RNN for evolution patterns. With the context awareness, a learning model, V-LSTM, is developed to dynamically capture the evolution pattern of user interests. By using a well-trained learning model, the authors predict future user preferences and recommend related items.

Based on the relations among users and items for recommendation, the authors introduce a novel concept, virtual communication, to effectively learn and estimate the correlation among users and items. By incorporating the discovered latent features of users and items in an evolved manner, the proposed ELR model could promote “right” things to “right” users at the “right” time. In addition, several extensive experiments are performed on real datasets and are discussed. Empirical results show that ELR significantly outperforms the prior recommendation models. The proposed ELR exhibits great generalization and robustness in real datasets, including e-commerce, industrial retail and streaming service, with all discussed metrics.

This paper aims to test the relationships among the experiential quality dimensions, the green relationship quality dimensions, environmental friendliness, green support, green desire and green experiential loyalty in a green bed & breakfast (B&B) context.

The data used in this study are based on a sample of 517 customers staying at one green B&B in Yilan County of Taiwan. The predicted relationship is tested using structural equation modeling.

The empirical findings reveal the following: five dimensions (peer-to-peer quality, physical environment quality, outcome quality, venue quality and administration quality) constitute a multidimensional model to conceptualize and measure perceived experiential quality that can achieve green experiential satisfaction in addition to environmental friendliness; environmental friendliness has a direct influence on green trust and green experiential satisfaction, which has a positive significant influence on green support and green desire; and green trust, green experiential satisfaction and green support contribute to green experiential loyalty.

To increase the perceptions of experiential quality dimensions, green relationship quality dimensions, environmental friendliness, green support, green desire and green experiential loyalty, the findings of this study will help green B&B management develop and implement market-orientated service strategies.

This paper provides data that result in a better understanding of the relationships among experiential quality dimensions, green relationship quality dimensions, environmental friendliness, green support, green desire and green experiential loyalty in a green B&B setting.

The purpose of this study is to assess the validity and predictability of insights from the investment model (IM) in the context of strategic manufacturer–industrial supplier relationships. IM is a theoretical model in social psychology pertaining to interpersonal relationship discontinuity. This formal empirical test of IM in a different context supports vertical theory borrowing and minimizes the risk of committing atomistic fallacy.

Data collected from 256 sourcing professionals participating in a scenario-based role-playing experiment were analyzed via structural equation modeling. The authors also performed bootstrapping to assess indirect effects.

The IM is generally applicable to the context of interfirm relationship dissolution. Relative to the original context of interpersonal relationship dissolution, three nuances are detected: investment size as an antecedent has lowered prominence in influencing commitment; satisfaction level, quality of alternatives and investment size have non-orthogonal effects on commitment; and satisfaction level influences relationship continuity through and beyond commitment.

The empirical findings broaden boundary conditions for IM insights. Beyond interpersonal relationship dissolution, the IM appears to also describe, explain and predict interfirm relationship dissolution.

Keeping the manufacturer satisfied is critical. Moreover, suppliers should be cautious when entering joint product development agreements.

This study appears to be among the first to formally validate the applicability of IM insights as they pertain to the dissolution of strategic manufacturer–industrial supplier relationships.

The purpose of this study is to explore how creative-cultural hotels can achieve sustainable service design through the development of a holistic conceptual framework.

The authors created this framework using a qualitative exploratory multi-case study of four creative-cultural hotels in Taiwan. The framework comprises strategic, organizational and interface levels to describe the design process and implementation of service offerings that co-create value within a multifaceted network of actors.

The findings of this study show that incorporating local arts and culture into sustainable service design can generate unique value and experiences for customers. From the perspective of sustainable development, these hotels seek to add value by using local creative and cultural resources to ensure that they have a sound commercial base from which to showcase their cultural features. As such, this study recommends that the hotel industry shift its focus to a paradigm that provides a strategic and sustainability-framed vision to create value for society while protecting local natural and cultural resources.

This multilevel model reframes the development of customer value constellations through a holistic understanding of user experience, eco-design practice, service encounters aligned with user touchpoints and front-line employee capabilities. To integrate the perspectives of both service providers and their customers, the proposed model embeds these stakeholders within a single model through the vehicle of local value co-creation. This holistic framework can assist in designing sustainable service within the hospitality industry to deliver better services and customer experiences. The findings provide an illustration of how the proposed multilevel sustainable-development-oriented service design framework can serve as a useful tool in guiding hotels toward corporate sustainability.