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As a standard source of capital for entrepreneurs, crowdfunding has recently gained wide attention in business and academia. With scientific endorsement, some research is conducted to explore the antecedents of online crowdfunding success. The factors that can influence the backers’ investment which is the key to success are information from prior backers’ and creators’ behaviors. Based on the signaling theory, the purpose of this paper is to systematically investigate the dynamic influences and interaction effects of signals with different forms (action-based or opinion-based signals) and sources (creator-sourced or backer-sourced signals) on backers’ investment behaviors over a project-funding cycle.

A panel data set of 3,010 projects with 640,625 transaction records from April 28, 2013 to September 31, 2017 is collected from a famous online crowdfunding platform – Zhongchou.cn in China and the negative binomial panel data model with fixed effect is used to obtain our empirical results.

The findings demonstrate that the work of different signals is significantly effective at the early stage of a project and decreases with time. Furthermore, our results show that there are both synergistic effect and substitution effect among different signals. Specifically, the direction of interaction effect depends on the forms of signals and the backers’ sensitivity toward that signal, and the interaction effects are also dynamic.

This paper has shed light on the roles of different signal types and their interactions in influencing funding behavior over a project-funding cycle, enriched the literature on crowdfunding and provided both theoretical and practical implications.

This work proposes a research model that explains investment intention in online peer-to-peer (P2P) lending based on the persuasion theory of elaboration likelihood model (ELM). In the proposed model, investment intention indirectly relates to source credibility and argument quality through the mediation of trust. At the same time, the study hypothetically moderates the relationships between source credibility and trust and between argument quality and trust by financial self-efficacy and risk preference.

This research presents an experiment to empirically validate its theoretical rationales. The hypotheses herein were tested using data from working professionals at a large science park in Taiwan. A total of 500 participants took part in the experiment in which the scenario of a pseudo-online P2P lending intermediary was first presented for their perusal, and then questionnaires based on the scenario were provided for the participants to fill out.

Trust cannot be improved over night without making great efforts on source credibility and argument quality in the long run. Online marketers should study market segmentations to decide what appropriate elements and promises should be provided in advertisements in order to improve their source credibility. Moreover, how online intermediaries formulate convincing messages and Polish their delivery communication skills should be improved so as to increase argument quality.

First, the theoretical conceptualization of source credibility and argument quality built upon the ELM not only broadens the boundary of virtual communities beyond the literature that considers source credibility and argument quality as important determinants, but also shows the practical status quo of trust as a critical mediator. Second, this research incorporates financial self-efficacy (based on social cognitive theory) and risk preference (based on economic theory) as important moderators in the development of trust. For that reason, customer education initiatives that influence financial self-efficacy and risk preference are discussed in greater detail.

Information disclosure requirements are a relatively common feature of consumer protection regimes generally. In the case of retail investment products such requirements have been in place since the late 1980s. Now the European Distance Marketing of Financial Services Directive will impose a similar disclosure regime wherever a contract is concluded at a distance. But, despite the popularity of disclosure regimes with policy makers, the available evidence suggests that such regimes may not be particularly effective. The purpose of this paper is to discuss first, the extent to which disclosure regimes are underpinned by a solid understanding of consumer decision‐making behaviour, and secondly, the implications the development of the internet as a delivery channel for retail investment products might have for their effectiveness. The paper concludes that, despite the indeterminacy of consumer decision‐making research such that it fails to provide a ready model on which to (re)design disclosure regimes, the development of the internet as a delivery channel both compounds the challenges for the regulator in devising an effective disclosure regime, but also provides the regulator with an opportunity to explore the potential to deliver interactive capabilities which would enhance the potential to better influence consumer decision making. As such, the paper should be of interest to regulators, the industry (which has expressed doubts about the cost‐effectiveness of such regimes) as well as academics interested in regulatory policy.

Digital currency investment has emerged as a result of global transformation toward technology-driven human lives. In Asia, Malaysia as an Islamic country is one of the early adopters with a high level of awareness on cryptocurrency. This paper aims to investigate the factors affecting the investment decision in cryptocurrency among potential investors in Malaysia.

Data was collected from 200 individuals aged 18 years and over. The hypotheses were tested using the partial least squares – structural equation modeling technique.

Results showed that attitude toward risk and perceived behavioral control have a significant positive effect on the investor’s investment decision in cryptocurrency. Interestingly, machine learning forecasting enhances the relationship between perceived benefits and the investment decision in cryptocurrency.

Results benefit investors and practitioners on the significant determinants of investment decision in cryptocurrency in emerging market.

Despite having high volatility and complexity in price determination, and being decentralized, cryptocurrency has managed to attract many investors due to reasons less explored. The outcome of this study extends the theory of planned behavior and confirms the role of machine learning forecasting as a moderator in the context of cryptocurrency investment.

The vast amount of information available via online social networks (OSN) makes it a very good avenue for understanding human behavior. One of the human characteristics of interest to financial practitioners is an individual’s financial risk tolerance. The purpose of this paper is to look at the relationship between an individual’s OSN behavior and his/her financial risk tolerance.

The study uses data collected from a sample of 220 university students and the backward variables selection ordinary least squares regression analysis technique to achieve its objective.

The results of the study find that the frequency of logging on to social network sites indicates an individual who has higher financial risk tolerance. Additionally, the increasing use of social networks for social connection is found to be associated with lower financial risk tolerance. The results are mostly consistent when the sample is split based on prior financial knowledge.

To the authors’ knowledge this is the first study which documents the possibility of understanding an individual’s financial risk tolerance via his/her social network activity. This provides investment/financial consultants with more avenues for gathering information in order to understand their current or potential clients hence providing better services.

The purpose of this paper is to test an augmented technology acceptance model (TAM) in the online financial trading context. This research aims to investigate how e‐investors are influenced by perceived trust, security, and privacy jointly with traditional TAM constructs.

The research examines e‐investors' behavioral intention to use online dealers' and stockbrokers' services. The model suggests that perceived trust jointly with perceived usefulness and perceived ease of use are important antecedents of intentions; the hypotheses are statistically tested using structural modeling.

The results from this study suggest that perceived trust, usefulness and ease of use are important issues in online trading systems. The findings suggest that online financial dealers and stockbrokers must improve the security of the online system since e‐investors form perceptions about its perceived security and when these perceptions are confirmed, their trust is enhanced and consequently they are more likely to use these online services particularly if the financial information is useful for their purposes.

The findings of the present study have various implications for research as well as practice. First, perceived trust, perceived usefulness and perceived ease of use are critical to the success of an online trading system. Second, perceived privacy did not influence users' beliefs in trust. Since perceived trust and perceived usefulness are the most important antecedents of behavioral intention, managers can increase e‐investors' usage intention by improving their beliefs in how the online trading system can enhance their performance and effectiveness using a system with enough security mechanisms. The major limitation is that trust is examined as a single‐dimension construct.

This paper is one of the first that has empirically tested the link between trust, security, privacy, usefulness, ease of use and behavioral intention in the online trading context.

The current study employs text mining and sentiment analysis to identify core banking service attributes and customer sentiment in online user-generated reviews. Additionally, the study explains customer satisfaction based on the identified predictors.

A total of 32,217 customer reviews were collected across 29 top banks on bankbazaar.com posted from 2014 to 2021. In total three conceptual models were developed and evaluated employing regression analysis.

The study revealed that all variables were found to be statistically significant and affect customer satisfaction in their respective models except the interest rate.

The study is confined to the geographical representation of its subjects' i.e. Indian customers. A cross-cultural and socioeconomic background analysis of banking customers in different countries may help to better generalize the findings.

The study makes essential theoretical and managerial contributions to the existing literature on services, particularly the banking sector.

This paper is unique in nature that focuses on banking customer satisfaction from online reviews and ratings using text mining and sentiment analysis.

Drawing on the taxonomy of patient empowerment and a sense of community (SoC), the purpose of this paper is to analyze the factors that impact the intention of the individual to continue using online social health support community for their chronic disease management.

A survey design was used to collect the data from multiple online social health support groups related to chronic disease management. The survey yielded a total of 246 usable responses.

The primary findings from this study indicate that the informational support – not the nurturant support such as emotional, network, and esteem support – are the major types of support people are seeking from an online social health support community. This research also found that patient empowerment and SoC would positively impact their intention to continue using the online health community.

This study utilized a survey design method may limit precision and realism. Also, there is the self-selection bias as the respondents self-selected themselves to take the survey.

The findings can help the community managers or webmasters to design strategies for the promotion and diffusion of online social health group among patient of chronic disease. Those strategies should focus on patient’s empowerment through action facilitating and social support and through creating a SoC.

An innovative research model integrates patient empowerment and a SoC to study patient’s chronic disease management through online social health groups to fill the existing research gap.

This study aims to examine the relationship between intrinsic motivation and online knowledge sharing intentions (KSIs) and the moderating effect of extrinsic motivation and organisational culture on this relationship. The influence of online KSI on two dimensions of online knowledge sharing behaviour, knowledge donating and knowledge collecting, was also investigated.

Based on the extensive literature review, a questionnaire was designed. In total, 290 questionnaires from employees in Vietnamese companies in the banking and insurance industry were collected and tested using structural equation modelling. Statistical analysis was conducted using SPSS and PLS 3 software to examine the research hypotheses.

This study found that rewards and reciprocity undermined the influence of self-enjoyment on online KSI, while top management support and social interaction ties undermined the relationship between self-efficacy and online KSI. Top management support positively moderated the effect of self-enjoyment on online KSI. The results also suggested that online KSI was a good predictor of online knowledge donating and collecting.

Little is empirically known about the moderating effect of extrinsic motivation and organizational culture on intrinsic motivation. The study brings new insights to further understand about online knowledge sharing in an organisation.