Seeding strategies have strong influences on the success of viral marketing campaigns, but previous studies using computer simulations and analytical models have produced conflicting recommendations ...about the optimal seeding strategy. This study compares four seeding strategies in two complementary small-scale field experiments, as well as in one real-life viral marketing campaign involving more than 200,000 customers of a mobile phone service provider. The empirical results show that the best seeding strategies can be up to eight times more successful than other seeding strategies. Seeding to well-connected people is the most successful approach because these attractive seeding points are more likely to participate in viral marketing campaigns. This finding contradicts a common assumption in other studies. Well-connected people also actively use their greater reach but do not have more influence on their peers than do less well-connected people.
Today, online social networks (OSNs) constitute a major part of our lives and have, to a large extent, replaced traditional media for direct communication, as well as information dissemination and ...gathering. In the vast amount of posts that get published in OSNs each day, some posts do not draw any attention while others catch on, become viral, and develop as so-called buzzes. Buzzes are defined through their characteristics of immediacy, unexpectedness, and intensity. The early detection of buzzes is of vital importance for companies, public figures, institutions, or political parties—e.g., for the pricing of profitable advertising placement or the development of an appropriate social media strategy. While previous researchers developed systems for detecting trending topics, mainly characterized by their intensity, this is the first study to implement a buzz detection system (BDS). Based on almost 120,000 manually classified Facebook posts, we estimated and trained models for the BDS by applying various classification techniques. Our results highlight that, among other predictors, the number of previously passive users who then engage in the buzz post, as well as the number of likes given to the comments, are important. Evaluating the BDS over a five-month evaluation period, we found that these two classifiers perform best and detected over 97% of the buzzes.
•Buzzes represent viral posts that are immediate, unexpected, and intense.•The early detection of buzzes can be of vital importance for various parties.•119,910 Facebook posts were manually classified to train classifiers.•The buzz detection system detected over 97% of the buzzes.•The system allows for user interactions and was tested over two evaluation periods.
Purpose
– Although the health information seeking behavior of consumers through the internet has received great attention, limited attempt has been made to integrate both the health information ...seeking behavior and the usage behavior in a mobile online context. The purpose of this paper is to explore the factors that influence consumer mobile health information seeking (MHIS) and usage behavior based on information quality, perceived value, personal health value, and trust.
Design/methodology/approach
– A survey was conducted to collect data. A two-step approach of structure equation modeling based was used to test the measurement model and hypothesis model.
Findings
– Information quality, perceived value, and trust were found to have positive effects on both the intention to seek and to use health information, and that the intention to seek affects the intention to use. Among the three components of perceived value, the utilitarian and epistemic values were found to have significant effects on intention to seek. In addition, the current health status of health consumers moderates the relationships between MHIS and usage intention and their determinants.
Originality/value
– Studies have primarily focussed on online health information seeking behavior, whereas a few of these studies have examined the seeking behavior intention and the usage behavior intention in a general model. The results indicate that health information usage behavior intention is closely related to the seeking behavior intention in the mobile context, which enriches the research on the relationship between information seeking and its outcomes. Furthermore, this study highlights the impact of information quality, perceived value, and trust on the intention to seek, and the impacts of information quality and trust on the intention to use, which have been overlooked in previous studies on MHIS.
Previous research has shown that user-generated stock votes from online communities can be valuable for investment decisions. However, to support investors on a day-to-day basis, there is a need for ...an efficient support system to facilitate the use of the data and to transform crowd votes into actionable investment opportunities. We propose a decision support system (DSS) design that enables investors to include the crowd's recommendations in their investment decisions and use it to manage a portfolio. A prototype with two test scenarios shows the potential of the system as the portfolios recommended by the system clearly outperform the market benchmark and comparable public funds in the observation period in terms of absolute returns and with respect to the Reward-to-Variability-Ratio.
•Stock ratings of online stock communities have shown to provide predictive value for investment decisions.•We develop a decision support system that enables day-to-day usage of these data for investors.•The system supports customized metrics and decision rules based and automatic portfolio management.•The portfolios of two test scenarios strongly outperform the market benchmark and comparable public funds, even after risk assessment..
Network analytical metrics often seek to capture the structural dimension of social capital, but such data collections using traditional social research tools often suffer from biases like ...interviewer effects and are usually only suitable to study small groups of participants. Digital sources of social relations might offer great potential for facilitating such measures though, because they digitally store unprecedented amounts of relational data, free from the limitations associated with self-reported data. This study therefore compares individual node degrees collected through a contact diary (i.e., overall-social capital), and a counterpart extracted from digital footprint data from the social media network, Facebook (i.e., social media network-social capital). The findings suggest that researchers conducting empirical studies involving the concept thus should not ignore social media network-social capital as a practical alternative measure of overall-social capital; it provides a sound approximation but only after controlling for other influential factors. In particular, our results highlight that the usability of the digital social capital metric is conditional on the three-way interaction between the variables gender, age, and social media network-social capital. Thus, the evidence from our study, in turn, also intimates that individuals act heterogeneously in the digital sphere with respect to their networking behaviour.
Device-to-device (D2D) communication is an innovative solution for improving wireless network performance to efficiently handle the ever-increasing mobile data traffic. Communication takes place ...directly between two devices that are in each other's transmission range. So far, research has focused on the technical challenges of implementing this technology and assumes a user's general willingness to participate as forwarder in this technology. However, this simplifying assumption is not realistic, as willingness to participate in D2D communication can vary depending on the user. In this work, we consider the scenario that a user can act as a forwarder for a receiver who is not directly or insufficiently reached by the base station and accordingly has no or poor Internet connection. We take a user-centric approach and investigate the willingness to provide an Internet connection as a forwarder. We are the first to investigate user preferences for D2D communication using a choice-based conjoint analysis. Our results, based on a representative sample of potential users (N = 181), show that the social relationship between the potential forwarder and the receiver has the greatest impact on the potential forwarder's decision to provide an Internet connection to the receiver, accepting sacrifices in terms of additional battery consumption and reduced own service performance. In a detailed segment analysis, we observe significant preference differences depending on smartphone usage behavior and user age. Taking the corresponding preferences into account when matching forwarders and receivers can further increase technology adoption.
Research on online content diffusion is vast but has rarely examined contextual factors, including the influence of online sharing mechanisms, such as social plugins (e.g., Facebook’s “Like” button), ...on online social networks (OSNs). While these mechanisms generally enable the content flow between senders and recipients, they vary in protecting users’
social
and
institutional privacy
on OSNs. Additionally, sharing mechanisms might differ with respect to their
labeling
(e.g., positive versus neutral), which might interact with the sharable content. We examined the effects of these three design aspects on users’ sharing behavior in a controlled experiment and two analyses of observational data. The results show that two types of sharing mechanisms negatively affect content sharing in the domain of news sharing: those that allow greater information flow control over the sharing process and thus protect users’
social privacy
and those that employ two-click designs to preserve users’
institutional privacy
. These negative effects mainly stem from higher frictional costs associated with these features. For the average user in this domain, the disutility and additional cognitive effort generated by one additional click often mitigates the utility of sharing itself. Moreover, we find that neutral button labeling is important for fostering content sharing as users might encounter schema incongruity when using a positively connoted label to share bad news. Overall, a wrong decision in terms of the sharing mechanism can easily decrease the number of shares by up to 86%. Therefore, content providers can easily and substantially increase content sharing by properly designing the sharing mechanism on their websites.
The online appendix is available at
https://doi.org/10.1287/isre.2017.0738
.
Optimal investment decisions by institutional investors require accurate predictions with respect to the development of stock markets. Motivated by previous research that revealed the unsatisfactory ...performance of existing stock market prediction models, this study proposes a novel prediction approach. Our proposed system combines Artificial Intelligence (AI) with data from Virtual Investment Communities (VICs) and leverages VICs’ ability to support the process of predicting stock markets. An empirical study with two different models using real data shows the potential of the AI-based system with VICs information as an instrument for stock market predictions. VICs can be a valuable addition but our results indicate that this type of data is only helpful in certain market phases.
High product return rates are an increasingly pressing challenge for many e-retailers around the world. To address this problem, this paper offers a new perspective by focusing on the critical moment ...of the package-opening process. Going beyond previous research, which has primarily focused on website information and the product itself, we examine the effects of the outside appearance (i.e., the color of the delivery package) and contents of the delivery package (i.e., extra gifts, coupons, and preprinted return labels) on consumer return behavior. Our findings across two experimental studies and an observational field study show that a well-considered package design, including colorful packaging and extra gifts, significantly lowers consumers' return intentions and actual returns. We also explore the process of consumers' cognitive-affective reactions after opening a delivery package. During this two-stage reaction process, pleasure plays a crucial role in the consumer's return choice.
With the growing proliferation of smart home assistants (SHAs), digital services are increasingly pervading people's private households. Through their intrusive features, SHAs threaten to not only ...increase individual users' strain but also impair social relationships at home. However, while previous research has predominantly focused on technology features' detrimental effects on employee strain at work, there is still a lack of understanding of the adverse effects of digital devices on individuals and their social relations at home. In addition, we know little about how these deleterious effects can be mitigated by using information technology (IT) artefact‐based design features. Drawing on the person‐technology fit model, self‐regulation theory, and the literature on anthropomorphism, we used the synergistic properties of an online experiment (N = 136) and a follow‐up field survey with a representative sample of SHA users (N = 214) to show how and why SHAs' intrusive technology features cause strain and interpersonal conflicts at home. Moreover, we demonstrate how SHAs' anthropomorphic design features can attenuate the harmful effects of intrusive technology features on strain by shaping users' feelings of privacy invasion. More broadly, our study sheds light on the largely underinvestigated psychological and social consequences of the digitization of the individual at home.
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