Knowledge that Transforms

Digital platform ecosystems feature interplatform competition. A potential strategy for a platform with market disadvantage is to make itself compatible with competitors to attract multihoming of developers. However, many questions remain unresolved regarding how a platform’s compatibility strategy impacts developers’ multihoming decisions and subsequent app performance. In this study, we use the context of web browser platforms (i.e., Firefox and Chrome) to investigate how the increase in the technological compatibility of a secondary platform (Firefox) influences developer multihoming from a primary dominant platform (Chrome). We theoretically consider how increased platform compatibility influences the trade-offs in developers’ multihoming decisions and their subsequent app development choices. Based on this trade-off perspective, we posit and empirically investigate the effects of increased platform compatibility on developer multihoming, and the subsequent development choices and app performance resulting from multihoming. Our findings illustrate that developers with larger user bases on the primary platform are more willing to multihome than those with smaller bases, but increased platform compatibility reduces this gap and enables developers with smaller user bases to better embrace multihoming. Increased platform compatibility also encourages multihoming developers to develop exclusive apps for the secondary platform. Moreover, increased platform compatibility facilitates multihoming developers to leverage their primary-platform user bases to enhance their secondary-platform app performance, and this effect is influenced by the development type (porting or exclusive development). Our study generates unique insights that add to the theoretical understanding of platform compatibility, multihoming, and platform competition.

Information, which is the critical resource provided by information systems (IS), is available in increasing volumes due to rapid technological progress. This causes a tension between the cognitive limitations of individuals and their access to large volumes of information. This tension is important not only for individuals but also for teams, which are increasingly making important organizational decisions. Recognizing this tension, this paper investigates the relationship between information volume and decision performance in IS-enabled teams. We use information processing and schema theories to develop a contextualized theoretical model, wherein information volume has a curvilinear (inverted U-shaped) effect on decision performance, and this effect is moderated by three context-relevant attributes of the team members: computer self-efficacy, computer anxiety, and learning goal orientation. We conducted two complementary studies, with similar experimental contexts and procedures but different types of participants and different tasks. In these studies, 236 individuals in 118 dyads (Study 1) and 200 individuals in 60 small teams (Study 2) made decisions over time using an enterprise resource planning system for a competitive virtual firm in a business simulation. We used objective data on system use and decision outcomes, along with survey data, to test the theoretical model. The two complementary studies find consistent results supporting the curvilinear relationship between information volume and decision performance and find that this relationship is flattened by high computer self-efficacy. Study 1 also supports the hypothesized steepening effects of high computer anxiety and learning goal orientation on the curvilinear relationship. Study 2 does not support these effects of computer anxiety and learning goal orientation but highlights some boundary conditions for them. Together, the studies provide insights into how information volume affects decision performance in IS-enabled teams, and how context-relevant team member attributes moderate this relationship and themselves affect decision performance.

The display of personal information in crowdfunding campaigns is vital for facilitating trust; however, this information often communicates the racial identity of the fundraiser. We study the relationship between racial cues and crowdfunding success. Using data from more than 100,000 projects gathered from Kickstarter.com, we categorized racial cues as creator-based versus product-based. For each category, we derived racial cues in two different mediums: photo vs. textual. We used propensity score matching to estimate the effects of racial identity across racial groups, categories, and mediums. We found that the category of racial cues is associated with crowdfunding success. Projects with either creator-based or product-based cues of African American identity had lower success rates. In contrast, creator-based cues of Asian identity were associated with lower levels of success whereas product-based cues were associated with increased success. Furthermore, when product-based cues and creator-based cues were misaligned, we found that the outcomes more closely followed those associated with product-based cues, suggesting that backers are more attuned to product attributes. Our results also suggest that racial anonymity correlates with higher success rates, as compared to African American and Asian racial cues. Our study contributes to the understanding of racial identity on digital platforms across multiple contexts, mediums, and racial groups.

Rural-urban healthcare access inequality refers to a disparity between rural and urban people with severe medical ailments in gaining access to the high-quality healthcare services they need. Although much hope has been pinned on the use of health information technology (HIT) to alleviate this critical and enduring societal challenge, the realized societal impact of HIT is unclear. Anchoring on both social transformation theory and affordance actualization theory, we conducted an in-depth qualitative study with two rounds of data collection in China. In addition to investigating how the societal challenge has triggered transformative HIT interventions, our analysis contributes to a theory on an HIT solution for the rural-urban healthcare access inequality challenge by establishing a link between HIT affordances and HIT interventions. This is done by examining how microlevel HIT effects escalate to macrolevel HIT effects through societal-level affordance actualization, which can affect this healthcare access inequality challenge. Along with providing policy implications on introducing HIT solutions to address intricate and complex societal challenges, this study extends existing theories by revealing the adaptation of the HIT intervention and differentiating the effects of collective and shared affordances.

This paper examines the relationship between enterprise systems (ES) and the likelihood of mergers and acquisitions (M&A). The key argument is that since ES can reduce agency costs associated with internal coordination and the transaction cost of coordinating with external partners, ES may be related to the likelihood of M&A. Using a sample of 3,289 firms headquartered in North America from 2010 to 2018 that made 8,373 M&A deals, the empirical analysis suggests that ES are positively related to horizontal acquisitions and negatively related to conglomerate acquisitions. However, as internal coordination costs increase, ES are becoming associated with more conglomerate M&A, especially when the goal is to introduce new products and enter new markets. Also, in contexts where partners require transaction-specific investments, ES are associated with a relative decrease in the number of horizontal and vertical M&A. These findings suggest that ES create options for managers to engage in ownership as well as information-based coordination, depending on the internal and external coordination costs as well as the goals of the organization.

Social media platforms, such as Facebook, Instagram, and Twitter, are combating the spread of fake news by developing systems that allow their users to report fake news. However, it remains unclear whether these reporting systems that harness the “wisdom of the crowd” are effective. Notably, concerns have been raised that the popularity of videos may hamper users’ reporting of fake news. The persuasive power of videos may render fake news more deceptive and less likely to be reported in practice. However, this is neither theoretically nor empirically straightforward, as videos not only affect users’ ability to detect fake news, but also impact their willingness to report and their engagement (i.e., likes, shares, and comments) which would further spread fake news. Using a unique dataset from a leading social media platform, we empirically examine how including a video in a fake news post affects the number of users reporting the post to the platform. Our results indicate that including a video significantly increases the number of users reporting the fake news post to the social media platform. Additionally, we find that the sentiment intensity of the fake news text content, especially when the sentiment is positive, attenuates the effect of including a video. Randomized experiments and a set of mediation analyses are included to uncover the underlying mechanisms. We contribute to the information systems literature by examining how social media platforms can leverage their users to report fake news, and how different formats (e.g., videos and text) of fake news interact to influence users’ reporting behavior. Social media platforms that seek to leverage the “wisdom of the crowd” to combat the proliferation of fake news should consider both the popularity of videos and the role of text sentiment in fake news to adjust their strategies.

Although financial fraud detection research has made impressive progress because of advanced machine learning algorithms, constructing features (or attributes) that can effectively signal fraudulent behaviors remains a challenge. In recent years, a new type of fraud has emerged on peer-to-peer (P2P) lending platforms, where individuals can borrow money from others without a financial intermediary. In these markets, the information asymmetry problem is seriously elevated. Inspired by the fraud triangle theory and its extensions, and using the design science research methodology, we construct five categories of behavioral features directly from P2P lending transaction data, in addition to the baseline features regarding borrowers and loan requests. These behavioral features are intended to capture the fraud capability, integrity, and opportunity of fraudsters based on their loan requests and payment histories, connected peers, bidding process characteristics, and activity sequences. Using datasets from real users on two large P2P lending platforms in China, our evaluation results show that combining these additional features with the baseline features significantly enhances detection performance. This design science research contributes novel knowledge to the financial fraud detection literature and practice.

Across different domains, websites are incorporating social media features, rendering themselves interactive and community-oriented. This study suggests that these “friendly” websites may indirectly encourage users to disclose private information. To investigate this possibility, we carried out online experiments utilizing a YouTube-like video-browsing platform. This platform provides a realistic and controlled environment in which to study users’ behaviors and perceptions during their first encounter with a website. We show that the presence of social cues on a website (e.g., an environment in which users “like” or rate website content) indirectly affects users’ likelihood of disclosing private information to that website (such as full name, address, and birthdate) by enhancing users’ “social perceptions” of the website (i.e., their perceptions that the website is a place where they can socialize with others). We further show that the presence of social cues is more likely to enhance users’ social perceptions when users are primed to perceive the website as trustworthy, as opposed to untrustworthy (through the presentation of trust cues such as data protection disclaimers). Moreover, we rule out users’ privacy concerns as an alternative mechanism influencing the relationship between social cues and information disclosure. We ground our observations in goal systems and trust theories. Our insights may be beneficial both for managers and for policy makers who seek to safeguard users’ privacy.

As an innovative alternative financing channel, online crowdfunding holds the promise of empowering entrepreneurs and small businesses. However, doubts have been expressed as to whether online crowdfunding can deliver on its promises because of the lack of empirical evidence regarding its effects. In this study, we investigate the effects of prosocial crowdfunding on traditional microfinance institutions (MFIs). Combining multiple data sources, including data from Kiva.org and the Microfinance Information Exchange Market (MIX Market), we examine how access to crowdfunding influences MFIs’ sustainability and interest rates. We find that after joining Kiva, MFIs’ sustainability improves and interest rates decrease. Further investigation suggests that the changes mainly result from efficiency improvement, rather than from increased supply of low-cost funds. We propose that joining an online crowdfunding platform induces greater transparency and crowd monitoring, which motivates and empowers MFIs to improve operations and become more efficient.