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The purpose of this paper is to examine factors affecting fundraisers’ voluntary information disclosure on crowdfunding platforms based on risk-perception theory (RPT).

Structural equation modeling was employed to test the hypothesized relationships using data collected from China.

The authors found that plagiarism risk and financing risk are two important variables that influence fundraisers’ voluntary information disclosure. Specifically, plagiarism risk has a negative effect on fundraisers’ voluntary information disclosure, while financing risk has a positive effect on fundraisers’ voluntary information disclosure. Plagiarism risk is affected by information concerns, perceived control, project innovativeness, and quality of alternatives, while financing risk is affected by protection policy and information norms.

This study enriches crowdfunding research by identifying factors influencing fundraisers’ voluntary information disclosure and contributes to RPT by applying it in a new crowdfunding context.

The purpose of this paper is to identify funders’ motivations for investing in crowdfunding. It applies trust theory to propose a research model including three subject measures – fundraiser-related, project-related and platform-related factors. Trust has been categorized into cognitive and affective dimensions to specifically analyze the influential factors.

Bootstrapping is employed to analyze data collected from respondents with investment experience on equity crowdfunding projects. Structural equation modeling techniques are adopted to examine the factors that influence trust between funders and crowdfunding as well as the outcomes of this trust.

The results indicate that calculus trust and relationship trust collectively or separately transmit the effect of some antecedents to investment intention. However, there is no evidence indicating the mediating effects of calculus trust and relationship trust on the relationship of structural assurance and value congruence to investment intention.

This paper provides insights for crowdfunding fundraisers on how to build a strong relationship with funders, and it also gives crowdfunding designers advice on how to improve and perfect the platform functions.

This study contributes to a better understanding of the driving forces of calculus and relationship trust and their influence on investment intention. It is also the first to address a funder’s trust using a theoretical model describing the investor intention in crowdfunding and thereby extending the knowledge base of trust theory.

The purpose of this paper is to examine whether social networking site (SNS) communities benefit from collective knowledge and collaboration, which represent a portfolio of knowledge transfer on SNSs.

A survey was conducted on a large scale through an online questionnaire. Structural equation modeling was employed to analyze data collected from 674 experienced SNS users.

The results indicate that all three exogenous variables, presented as user characteristics and integrated into SNS user characteristics, were positively related to the knowledge transfer portfolio, namely, to collective knowledge and collaboration, and these variables had significant moderating effects on SNS users’ community cohesiveness. Early SNS adoption was more likely than late SNS adoption to moderate the relationship between collective knowledge and community cohesiveness and that between collective collaboration and community cohesiveness.

The findings provide useful insights for SNS operators to enhance the process of collaborative knowledge transfer. They may also be used to obtain better insights into important factors that require closer attention during SNS use.

The present study provides a systematic analysis of SNS use by considering a new research model and investigating the effects of SNS-based knowledge transfer on user outcomes based on three major characteristics of SNS users. The results are expected to provide a major foundation for further SNS research and a better understanding of the relationships between SNS user characteristics, knowledge transfer, and community cohesiveness.

The purpose of this paper is to apply the self-determination theory (SDT) to propose a research model that incorporates the SDT framework and contextual variables as determinants and self-identity and social identity as mediating constructs to predict individuals’ intentions toward donation crowdfunding in China.

Structural equation modeling is used to analyze the data collected from China.

The results indicate that the self-identity and social identity collectively or separately mediate the effect exerted by the sense of self-worth, face concern, moral obligation, perceived donor effectiveness, social interaction and referent network size on donation intentions. However, there is no evidence supporting the hypothesis connecting moral obligation with self-identity.

The study provides suggestions for service providers on how to improve and perfect the functions, and it also provides insights for donation crowdfunding fundraisers on how to increase the success rate.

The conclusions of this study provide academics with a more thorough understanding of the driving forces of individual behavior intention toward donation crowdfunding in China. This study further expands the SDT and identity theory in the context of donation crowdfunding, which improves their robustness in explaining behavioral intention. These theories may be an important part of future information system research.

This study aimed to verify the impact of e-commerce live streaming interactivity on consumer engagement behavior. Specifically, the multiple dimensions of interactivity and tie strength together form a high-level consumer engagement behavior.

Data collection was carried out in the form of a questionnaire survey. Data from 416 respondents were analyzed by structural, followed by further test by fsQCA method.

Perceived controllability, perceived responsiveness and perceived mutuality positively influence tie strength, and tie strength promotes consumer engagement behavior. Moreover, we found a configuration effect between interactivity and tie strength and revealed four configurations that can affect high-level engagement behavior.

First, the SEM results show that the three dimensions of perceived interactivity positively impact tie strength: perceived controllability, perceived responsiveness, and perceived mutuality. And perceived personalization has no positive impact on tie strength. Second, the relevant results show that tie strength positively impacts consumer engagement behavior. Third, we find that the relationship between perceived interactivity and consumer engagement behavior may not be asymmetric, so the alternative combination of causal conditions may produce the same results. The fsQCA results revealed four configurations that can affect the level of consumer engagement behavior. And tie strength is the core condition.

This study provides specific solutions for e-retailers and live streaming platforms to promote consumers' participation in engagement behavior in e-commerce live streaming.

This study transforms the linear impact of interactivity on consumer engagement behavior into a configuration effect for the first time, and enriches the live streaming commerce and consumer engagement behavior literature.

Omnichannel has become increasingly important with the development of e-commerce. In omnichannel, merchants expect customers to get the products and services at anytime, anywhere and in any way, and the same is true for customers. This drives multihoming in online platforms for both merchants and customers. Thus, once both customers and merchants are multihomed, what price and subsidy decisions should be made between platforms to compete to obtain optimal profits? The main purpose of this paper is to solve these problems and provide decision-making for two-sided platforms in omnichannel.

This study builds a dual Hotelling model to capture the utility and network effects of customers and merchants on two-sided platforms. This study introduces the exposure effect and convenience effect of multihomed customers and merchants in the model and analyzes the impact of these effects in the market with multihoming on one side. Then, this study extends the model to the market with multihoming on both sides and makes the pricing decision for two-sided platform when considering the exposure effect and convenience effect through an equilibrium solution. Finally, this study also uses numerical analysis to simulate the decision and profit of the platform.

This paper finds that the convenience effect will only increase social welfare when customers are single-homed and merchants are multihomed. In addition, when both users are multihomed, the platform will subsidize to attract merchants and customers if the convenience effect and exposure effect are relatively high. This study also finds that network effects come not only from the same platform but also from another platform in the case with multihoming on both sides. And network effects in the heterogeneous platform will be reduced by the convenience effect and exposure effect.

According to the behavioral characteristics of merchants and customers in omnichannel, this paper first adopts the dual Hotelling model to study the pricing of two-sided platforms with multihoming on both sides. This paper shows that network effects originate not only from the same platform but also from another platform and that the exposure effect and the convenience effect can exist as cross-platform network effects, which provides a new explanation for network effects in markets with multihoming on both sides. This research extends the theory of network effects and plays an important role in the development of two-sided platforms in omnichannel.

The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.

This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.

According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.

In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.

Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.

The purpose of this paper is to explain to educators and system developers the novel systemic instructional methodology and tools which the use to improve students' learning about and development of viable ventures and reliable software systems. This methodology is used to counteract impetuous detail – focussed thinking. For example, it has been evident that students often compromise their learning and their design work by failing to take large enough, or systemic enough, long‐term perspectives. Rarely, do they grasp the need for finding and discussing multiple alternative and contextually well‐situated strategies prior to their attempts at designing systems or plunging into the generation of software code.

Both analytic narratives of intentionality and executable prototype models have essential roles to play in learning about and designing systems, and this paper explains how these can be integrated. This is done by three parallel learning‐conversations: about why we are learning this?; about what is really going on here?; and about which learning strategies (meta‐cognitive strategies) to use. These conversations are carried on at the same time as cybersystemic modelling which often involves the building of a canonical formal representation of entities, relationships and transformations, making possible the running of simulations. The modelling is done using Jaworski's “j‐Maps™” notation (from which various specialized views can be generated by the “CONTEXT+”™ tools as needed). This is done in order to assess the completeness, correctness and requisite control variety aspects of actual and prospective viable systems and software.

It has been found by carefully triangulated observations over two decades of using successive versions of this methodology that graduate students who work through these activities with this notational technology, develop deeper understanding, produce more reliable software and develop more viable systems.

The paper is of value in presenting context map as an advanced, powerful and easy‐to‐implement method for information representation and transformation and systems development.

The study aims to investigate the impact of “decent work” dimensions on faculty members’ work engagement levels in the higher education institutions in India.

Data were obtained from 293 faculty members working in higher education institutes in India. The proposed study hypotheses were tested by deploying the statistical technique of multiple regression analysis using statistical package for social sciences Version-24.

Results demonstrated that of the five dimensions of “decent work,” only “access to health care” and “complementary values” were significant predictors of work engagement. “Adequate compensation,” “free time and rest” and “safe interpersonal working conditions” as dimensions of “decent work” were not found to be significantly related to work engagement.

Findings encourage education policymakers to implement a “decent work” policy for faculty members with greater emphasis on ensuring workplace-fit and provision of adequate health-care facilities to keep the workforce engaged.

It is one of the few studies conducted in the South-Asian context that highlight “decent work” as a crucial job resource, useful in enhancing the work engagement of faculty members in higher education institutions.