Showing papers in "Information Systems Research in 2022"
TL;DR: In this article , the authors explore the issues related to human capabilities to work with AI and highlight capabilities that humans need to effectively work with artificial intelligence and still be in control rather than just being directed.
Abstract: A consensus is beginning to emerge that the next phase of artificial intelligence (AI) induction in business organizations will require humans to work with AI in a variety of work arrangements. This article explores the issues related to human capabilities to work with AI. A key to working in many work arrangements is the ability to delegate work to entities that can do them most efficiently. Modern AI can do a remarkable job of efficient delegation to humans because it knows what it knows well and what it does not. Humans, on the other hand, are poor judges of their metaknowledge and are not good at delegating knowledge work to AI—this might prove to be a big stumbling block to create work environments where humans and AI work together. Humans have often created machines to serve them. The sentiment is perhaps exemplified by Oscar Wilde’s statement that “civilization requires slaves…. Human slavery is wrong, insecure and demoralizing. On mechanical slavery, on the slavery of the machine, the future of the world depends.” However, the time has come when humans might switch roles with machines. Our study highlights capabilities that humans need to effectively work with AI and still be in control rather than just being directed.
22 citations
TL;DR: In this paper , the authors investigated the impact of trademarking hashtags on social media audience engagement and information dissemination, and they found that the trademarking of hashtags makes composing tweets with certain linguistic styles more critical.
Abstract: Firms of all sizes are “joining the conversation” on social media platforms and increasingly trademarking hashtags related to their products and brands. This added effort to protect intellectual property and its impact on social media engagement have not been investigated in the literature. In this study, we find that trademarking hashtags plays a pivotal role in increasing social media audience engagement and information dissemination. More importantly, this positive effect is stronger for firms with fewer Twitter followers. Digging deeper into the underlying mechanisms, we find that trademarking hashtags makes composing tweets with certain linguistic styles more critical: It can amplify the positive effects of trademarking hashtags on social media audience engagement. Our findings highlight important managerial implications of trademarking hashtags. First of all, we examine whether trademarking a hashtag helps or hurts a firm in terms of its social media audience engagement. Further, we show, to maximize the effectiveness of trademarking hashtags, how firms should develop the right social media engagement strategies by taking specific communication and linguistic styles into account. Our results provide useful insights to firms in understanding the key benefits of signaling through trademarking hashtags on social media engagement.
13 citations
TL;DR: In this paper , the authors argue that different but no less important processes of digital transformation are generated by the undertow produced by the waves of digitalization, which is referred to as digital displacement, a process that is significantly challenging the capacity of standards to effectively manage industry operations.
Abstract: Digital transformation research shows how waves of digitalization produce strategic changes within and across firms, enabling new forms of value creation. We argue that different but no less important processes of digital transformation are generated by the undertow produced by these waves. Digital undertow, a corollary effect of waves of digitalization, profoundly influences how firms operate by transforming the industry standards that coordinate and regulate their core business activities. This is producing what we refer to as digital displacement, a process that is significantly challenging the capacity of standards to effectively manage industry operations in the digital age.
13 citations
TL;DR: In this paper , the authors present an approach to improve the performance of policy-making in practice and policy-training, and propose an approach for policy-based training and evaluation.
Abstract: Practice and Policy Abstract
13 citations
TL;DR: In this article , the authors explore the effects of network embeddedness on performance rating scores according to two dimensions of embeddedness: (i) positional, the position of an individual in the emerging network of performance ratings, and (ii) structural, the extent to which a person is entrenched in a network of relationships.
Abstract: Firms and organizations are increasingly using real-time performance feedback mechanisms to evaluate employees, where any employee (rather than just the supervisor) can rate other employees. Hence, a need arises to better understand how network positions of employees in such a system impact their performance. Analyzing nearly 4,000 feedback instances from employees at five major organizations that utilize such a real-time performance feedback application called DevelapMe, we explore the effects of network embeddedness—or the nature of relationships among employees—on performance rating scores according to two dimensions of embeddedness: (i) positional, the position of an individual in the emerging network of performance ratings, and (ii) structural, the extent to which a person is entrenched in a network of relationships. We visualize rating networks within organizations: Employees are nodes, and connections between nodes exist if an evaluation between the pair occurs. We find that specific aspects of network embeddedness affect performance rating scores differently. Our findings have important implications for the design of performance management systems using network analysis.
12 citations
TL;DR: It is shown that the number of offline appointments for doctors increases after opening online consultation services and this provides useful implications for all the stakeholders—doctors, patients, hospitals, and policy makers—regarding how to integrate online and offline channels in the healthcare context.
Abstract: Online healthcare portals have become prevalent worldwide in recent years. One common form of healthcare portal is the online consultation website, which provides a bridge between patients and doctors and reduces patients’ time and cost when seeking healthcare services. Another form is the healthcare service appointment website, which facilitates offline visits for patients. Though nominally separate, the behaviors of the users (including patients and doctors) on these two types of websites could be related to each other. In particular, how does opening online consultation services impact the offline appointments of doctors? Although this is an important question for healthcare portals, doctors, and policy makers, it has not been rigorously examined in the literature. We examine the overall impact of opening online consultation services on offline appointments and show that the number of offline appointments for doctors increases after opening online consultation services. Given that online consultation is a new but important way to connect patients and doctors, our findings provide useful implications for all the stakeholders—doctors, patients, hospitals, and policy makers—regarding how to integrate online and offline channels in the healthcare context.
11 citations
TL;DR: In this article , the authors show that firms do not need to have the same levels of IT exploitation and exploration simultaneously to improve organizational agility, and that the maximal agility is not associated with the perfect balance between IT exploits and exploration.
Abstract: Firms in the digital age often do not know whether they should focus on exploiting their existing information technology (IT) resources or focus on exploring novel IT resources. They are often told to maintain a perfect balance between IT exploitation and IT exploration. In this study, we show that firms do not need to have the same levels of IT exploitation and exploration simultaneously to improve organizational agility. IT ambidexterity can be achieved by proportional balance between IT exploitation and exploration without forcing the perfect balance between the two. With finite resources, the maximal agility is not associated the perfect balance between IT exploitation and exploration; instead, it is associated with the proportional balance between IT exploitation and exploration, and the optimal proportional balance could vary based on the firm’s total resources allocated for IT ambidexterity. Our findings on proportional balance between IT exploitation and exploration could profoundly influence how firms make IT investment decisions. Rather than pursuing a perfect balance between IT exploitation and IT exploration, firms should consider both their organizational characteristics and environmental conditions to identify optimal levels of proportional balance between the two.
10 citations
TL;DR: Wang et al. as discussed by the authors built on the theoretical lens of justice theory to integrate justice provision with two key privacy protection features, negotiation and active-recommendation, and proposed an information technology (IT) solution to balance the tradeoff between privacy protection and consumer data collection.
Abstract: Companies face a trade-off between creating stronger privacy protection policies for consumers and employing more sophisticated data collection methods. Justice-driven privacy protection outlines a method to manage this trade-off. We built on the theoretical lens of justice theory to integrate justice provision with two key privacy protection features, negotiation and active-recommendation, and proposed an information technology (IT) solution to balance the trade-off between privacy protection and consumer data collection. In the context of mobile banking applications, we prototyped a theory-driven IT solution, referred to as negotiation, active-recommendation privacy policy application, which enables customer service agents to interact with and actively recommend personalized privacy policies to consumers. We benchmarked our solution through a field experiment relative to two conventional applications: an online privacy statement and a privacy policy with only a simple negotiation feature. The results showed that the proposed IT solution improved consumers’ perceived procedural justice, interactive justice, and distributive justice and increased their psychological comfort in using our application design and in turn reduced their privacy concerns, enhanced their privacy awareness, and increased their information disclosure intentions and actual disclosure behavior in practice. Our proposed design can provide consumers better privacy protection while ensuring that consumers voluntarily disclose personal information desirable for companies.
10 citations
TL;DR: In this article , a potential-dyads approach and a quasi-natural experiment jointly demonstrate that employees are inclined to answer a question from their higher-ups and even exert more effort in those answers.
Abstract: Are employees willing to voluntarily share knowledge with their higher-ups? The existing studies show that the answer is no—employees are less likely to share knowledge with their higher-ups in the offline setting, corporate wikis, and online discussion groups. We answer the same question in a corporate question-and-answer (Q&A) community and argue that the answer can be yes. A potential-dyads approach and a quasi-natural experiment jointly demonstrate that employees are inclined to answer a question from their higher-ups and even exert more effort in those answers. Using an instrumental-variable design, we show that users who post more answers to higher-ranked individuals and who display greater effort in those answers are more likely to get promoted in subsequent years, meaning that employees do not need to worry about their careers when sharing knowledge with their higher-ups in corporate Q&A communities. Our research, together with research on other contexts, are useful for companies to take the role of the managers into account when considering which type of online community to adopt. Community designers can use our findings to better motivate knowledge sharing by considering users’ different job ranks.
9 citations
TL;DR: In this article , the authors examined the potential economic spillover effects of a home sharing platform (Airbnb) on the growth of a complimentary local service (restaurants) and found that a one-percentage-point increase in the intensity of Airbnb activity leads to approximately 1.7% restaurant employment growth.
Abstract: This paper examines the potential economic spillover effects of a home sharing platform—Airbnb—on the growth of a complimentary local service—restaurants. By circumventing traditional land-use regulations and providing access to underutilized inventory, Airbnb attracts visitors to outlets that are not traditional tourist destinations. Although visitors generally bring significant spending power, it is unclear whether visitors use Airbnb only primarily for lodging and thus do not contribute to the adjacent economy. To evaluate this, we focus on the impact of Airbnb on restaurant employment growth across locales in New York City (NYC). Specifically, we focus on areas in NYC that did not attract a significant tourist volume prior to the emergence of a home-sharing service. Our results indicate a salient and economically significant positive spillover effect on restaurant job growth in an average NYC locality. A one-percentage-point increase in the intensity of Airbnb activity (Airbnb reviews per household) leads to approximately 1.7% restaurant employment growth. Since home-sharing visitors are lodging in areas that are not accustomed to tourists, we also investigate the demographic and market-structure-related heterogeneity of our results. Notably, restaurants in areas with a relatively high number of White residents disproportionately benefit from the economic spillover of Airbnb activity, whereas the impact in majority-Black areas is not statistically significant. Thus, policy makers must consider the heterogeneity in the potential economic benefits as they look to regulate home-sharing activities.
9 citations
TL;DR: In this paper , the authors analyze the welfare implications of consumer data sharing, and restrictions to that sharing, in the context of online targeted advertising, and find evidence of incentive misalignment among the players, as the intermediary prefers to share only a subset of consumer information with firms, whereas advertising firms prefer having complete information about the consumers.
Abstract: We analyze the welfare implications of consumer data sharing, and restrictions to that sharing, in the context of online targeted advertising. Targeting technologies offer firms the ability to reach desired audiences through intermediary platforms. The platforms run auctions in real time to display ads on internet sites, leveraging consumers’ personal information collected online to personalize the ads. The online advertising industry posits that targeted advertising benefits advertising firms (that is, merchants who want to target ads to the desired consumers), consumers who see ads for preferred products, and the intermediary platforms that match consumers with firms. However, the claims that targeted advertising benefits all players involved have not been fully vetted in the literature. We develop an analytical model to analyze the economic and welfare implications of targeting technologies for those three players under alternative consumer information regimes. The regimes differ in the type and amount of consumer data available to the intermediary and to the advertising firms, and reflect the presence or absence of technological or regulatory restrictions to personal information flows. We find evidence of incentive misalignment among the players, as the intermediary prefers to share only a subset of consumer information with firms, whereas advertising firms prefer having complete information about the consumers. As such, a strategic intermediary with the ability to control which information is shared during the auction can have an incentive to use only the information that maximizes its payoff, overlooking the interests of both advertising firms and consumers. The information regimes that maximize consumer welfare vastly differ depending on consumers’ heterogeneity along two dimensions: a horizontal dimension, capturing consumer’s heterogeneity in product preferences; and a vertical dimension, capturing consumers’ heterogeneity in purchase power. Consumers prefer none of their personal information to be used for targeting only in limited circumstances. Otherwise, consumers are either indifferent or prefer only specific types of information to be used for targeting.
TL;DR: In this paper , the authors demonstrate that extending the magnitude of taste differentiation is an effective differentiation strategy and that increasing product differentiation leads to greater perceived value of the service, but undermines fairness perceptions.
Abstract: Companies in platform-based business markets have widely embraced freemium business models, in which profit is primarily determined by a minority of paying customers. However, the key challenge of these models is transitioning participants from free users to paying consumers. To encourage paid consumption, companies often rely on product differentiation such as providing consumers who pay for products or services with enhanced features. Product differentiation can be broadly classified into two categories: taste differentiation and quality differentiation. The authors demonstrate that extending the magnitude of taste differentiation is an effective differentiation strategy. Quality differentiation, however, is a double-edged sword and should be used with care. Increasing product differentiation leads to greater perceived value of the service, but undermines fairness perceptions.
TL;DR: In this article , the authors focus on the largely overlooked but important topic: social value created by teleconsultations, and uncover the underlying mechanisms that drive such frictions and provide recommendations to reduce the frictions.
Abstract: In this study, we focus on the largely overlooked but important topic: social value created by teleconsultations. Many countries suffer from the geographic imbalance of their medical professionals: there are abundant resources in urban cities but too few in rural areas. Teleconsultations have emerged as a promising solution to reduce this disparity because they can remotely deliver healthcare without relocating medical professionals. Yet it is unclear whether teleconsultations actually mobilize healthcare to underserved areas. To answer this question, we collaborate with a large online healthcare platform and analyze its teleconsulting data together with offline healthcare and regional data. Our results indicate that teleconsultations tend to connect physicians in resourceful regions with patients in underserved areas—a desirable pattern that alleviates the geographic healthcare disparity. However, we also find that social, information, and geography frictions persist. For instance, teleconsultations are less likely to occur as regions become farther apart, and financial and information constraints limit rural patients’ access to teleconsultations. We uncover the underlying mechanisms that drive such frictions and provide recommendations to reduce the frictions that hinder teleconsultations.
TL;DR: This paper proposed a text-based personality measurement approach that improves detection of personality dimensions by 10-20 percentage points relative to the best existing methods developed in industry and academia, which can translate into significant improvements in downstream applications such as forecasting future firm performance or predicting pandemic infection rates.
Abstract: Analysts, managers, and policymakers are interested in predictive analytics capable of offering better foresight. It is generally accepted that in forecasting scenarios involving organizational policies or consumer decision making, personal characteristics, including personality, may be an important predictor of downstream outcomes. The inclusion of personality features in forecasting models has been hindered by the fact that traditional measurement mechanisms are often infeasible. Text-based personality detection has garnered attention due to the public availability of digital textual traces, however state-of-the-art models proposed by IBM, Google, Facebook, and academic research are not accurate enough to be used for downstream real-world forecasting tasks. We propose a novel text-based personality measurement approach that improves detection of personality dimensions by 10–20 percentage points relative to the best existing methods developed in industry and academia. Using case studies in the finance and health domains, we show that more accurate text-based personality detection can translate into significant improvements in downstream applications such as forecasting future firm performance or predicting pandemic infection rates. Our findings have important implications for managers focused on enabling, producing, or consuming predictive analytics for enhanced agility in decision making.
TL;DR: In this paper , the authors provide a longitudinal perspective over how and why hedonic information systems (IS) use addiction and break down this process into three phases characterized by different types of use, whether nominal, compulsive, or addicted.
Abstract: Addiction to hedonic information systems yields significant negative consequences for users. Although we know about the causes of addictions, particularly those related to individual differences, recent evidence suggests that addiction evolves gradually over time and is rooted in shared characteristics of users and technology. This paper provides a longitudinal perspective over how and why hedonic information systems (IS) use addiction develops. Based on our analysis, we break down this process into three phases characterized by different types of use, whether nominal, compulsive, or addicted. Each phase highlights salient psychological needs that motivate, technology features that enable, and affordances that are actualized into each type of use. We also provide a detailed account of individuals’ self-control mechanisms, explaining how deficiencies in sensing, comparing, or regulating behavior facilitate one’s transition toward addiction. These insights are applicable to other hedonic IS that are similar in terms of ubiquity and constant access through mobile apps. They point to heterogeneous (preventive or intervening) strategies that can be used to help people regain their control over use, depending on where they are in their trajectory toward addicted use. Our findings carry implications for the design of systems and features that can help reduce the likelihood of addiction development.
TL;DR: Zhang et al. as mentioned in this paper proposed social pricing, a novel pricing framework under which consumers with higher social capital enjoy a better price, which enables firms to achieve price discrimination based on a consumer's social value.
Abstract: We propose social pricing, a novel pricing framework under which consumers with higher social capital enjoy a better price. Conceptually, social pricing enables firms to achieve price discrimination based on a consumer’s social value. This is in sharp contrast with traditional price discrimination strategies where price differentiation typically hinges on consumers’ personal value. We design and conduct two randomized field experiments on a leading online fresh food retailer to understand the value of social pricing. Social pricing has been commonly credited for its effectiveness in new customer acquisition. Interestingly, our study reveals that it is also highly effective on existing consumers. Our analysis shows that social pricing can increase an online retailer’s profit by 40% solely from existing consumers, compared with regular firm-offered discounts. Exploration of the underlying mechanisms reveals that perceived engagement and social cost are the main drivers, which not only help to increase purchasing frequency but also induce higher order value per purchase. In a follow-up experiment, we vary the rules of social interactions by requiring heterogeneity in consumers’ purchasing frequencies. The results suggest that a heterogeneity-based strategy can further amplify the benefits of social pricing.
TL;DR: In this article , the authors investigate how predecessors' usernames affect successors' herding momentum through varying extent of perceived source credibility, and find that successors demonstrate weaker herding toward predecessors who are presented with real-seeming username than anonymous ones.
Abstract: This research investigates whether and how predecessors’ usernames—as evaluated from a perspective of perceived anonymity—affect successors’ herding momentum through the varying extent of perceived source credibility. Using a unique data set collected from a leading debt-based crowdfunding platform, we classify lenders’ usernames as either anonymous or real-seeming, with the latter referring to usernames that seem to reveal one’s legal name. We find that successors demonstrate weaker herding momentum toward predecessors who are presented with real-seeming usernames than anonymous ones. This finding, which we attribute to a lower extent of perceived credibility resulting from a nonconforming behavior, challenges the conventional wisdom that considers anonymity a negative factor for source credibility. Further, we demonstrate the importance of risk-related factors, in that the uncovered positive effect of perceived anonymity on herding is accentuated in the early stage of the fundraising period. Our findings provide actionable insights for platform owners to utilize the user heterogeneity with respect to perceived anonymity and hence perceived credibility in herding. These findings are also informative for borrowers who desire to exert effort to encourage participation from the crowd.
TL;DR: In this paper , the authors examine whether and how a regulation to increase the saliency of project risks in crowdfunding affects crowdfunders' funding decisions and find that increasing the awareness of project risk is associated with inferior funding outcomes of crowdfunding projects, and the effect exists mainly for high risk projects but not much for low-risk projects.
Abstract: How should crowdfunding platforms alleviate information asymmetry between creators and crowdfunders? In traditional financial markets, public companies are required to disclose potential risks to their investors, and such risk disclosure requirements are enforced by legal and fiduciary regulations. In the crowdfunding context, however, such information asymmetry concerns are often addressed by crowdfunding platforms. In this study, we examine whether and how a regulation to increase the salience of project risks in crowdfunding affects crowdfunders’ funding decisions. We find that increasing the awareness of project risks is associated with inferior funding outcomes of crowdfunding projects, and the effect exists mainly for high-risk projects but not much for low-risk projects. In addition, high-risk projects benefit from a risk disclosure with relevant information, authentic language, and balanced tones that are not overly negative or optimistic. Despite the negative short-term effects, technology funders tend to interpret risk disclosures rationally over time, suggesting a positive long-term effect. Implications for research and insights for practitioners are discussed, particularly the fact that disclosure policies may make crowdfunding markets more sustainable by reducing information asymmetry and helping crowdfunders make more informed decisions.
TL;DR: In this article , the authors examine ITO performance by focusing on client firms' perceived legitimacy of vendors, termed "vendor legitimacy", consisting of pragmatic, cognitive, and moral dimensions.
Abstract: Information technology outsourcing (ITO) relationships today are facing increasingly turbulent environments. This research examines ITO performance by focusing on client firms’ perceived legitimacy of vendors, termed “vendor legitimacy,” consisting of pragmatic, cognitive, and moral dimensions. Based on our surveys with executives and managers at 200 ITO client firms, the study’s findings present the imperative to actively manage vendor legitimacy for achieving and sustaining ITO performance. Specifically, at the strategic level, clients’ perception of vendors as mutually aligned, long-term-oriented, tightly integrated partners is critical. At the operational level, clients should collaborate with vendors to design and establish interorganizational routines that undergird vendor legitimacy. At the managerial level, clients’ relational governance plays a pivotal role in attaining procedural justice, ethical standards, and fairness in the interorganizational collaboration. In sum, our study suggests that creating a dedicated corporate function or unit for continually overseeing and assessing a portfolio of vendors and swiftly identifying and responding to potential issues and crises related to vendor legitimacy would be a worthwhile investment.
TL;DR: The causes behind electronic device returns are identified and it is found that stress during the trial period is a major contributing factor.
Abstract: Application abstract: A large number of electronic devices are rejected and returned to the seller in the first weeks of trial use, which costs organizations millions of dollars. We aimed to identify the causes behind those returns and find that stress during the trial period is a major contributing factor. Users are stressed as they need to learn how to use the electronic device, integrate it into their daily life, and take care of privacy issues. All that creates stress and makes users feel unhappy with using the electronic device so that they will send it back to the seller. In particular, we see in our results that individuals who are not innovative in using IT in general and have a low willingness to learn using the new electronic device tend to send back electronic devices in the first weeks of the trial period. When discussing those results with individuals who had sent back tablet devices, we see that stress in the trial period can even overwhelm positive thoughts. So, with our results, we conclude that stress in the trial period has many causes that are often responsible for returning electronic devices.
TL;DR: The work unlocks an important missing puzzle for further user empowerment—a way for non-IT professionals to get the most out of the data through a combination of graphical conceptual models with narratives.
Abstract: Elevator Pitch A quiet revolution is happening in the offices, cubicles, and boardrooms of the world. Non-IT professionals are becoming empowered by leveraging organizational data for analytics. We support this movement by offering a powerful way to make data more usable via a combination of graphical conceptual models with narratives. Longer Version We are witnessing a quiet revolution—the rise of empowered users. These non-IT professionals increasingly seek to leverage the ever-expanding amount of organizational data for analytics to support their initiatives, decisions, and actions. All too often, however, the enthusiasm of these users collides against the harsh reality—many of them lack sophisticated IT skills, and they struggle to find/access relevant data, understand their meaning, and extract and adapt them to meet their needs. We propose a powerful way to support empowered users with a combination of conceptual models and narratives. Conceptual models are diagrams that accurately and succinctly represent rules and patterns captured in data. Although somewhat intuitive, these models alone do not suffice, as interpreting them still requires some specialized IT knowledge. Hence, we add narratives—stories written in natural language. The narratives intuitively explain some of the challenging aspects of the conceptual models. We conducted a series of experiments and interviews with empowered users to assess our idea. These studies show the value of the conceptual models with narratives for understanding organizational data. Our work unlocks an important missing puzzle for further user empowerment—a way for non-IT professionals to get the most out of the data.
TL;DR: In this paper , three main processes with which ventures can improve templating: concepting, generalizing, and porting are described and implications for managers engaged in growing their digital venture are discussed.
Abstract: A powerful way of growing digital ventures is templating. Templating involves the generation and use of generic solutions across business areas to reduce cost and increase speed. There are three main processes with which ventures can improve templating: concepting, generalizing, and porting. This paper describes these processes and proposes implications for managers engaged in growing their digital venture.
TL;DR: In this article , the importance of consumers' consideration sets in mediating the positive effects of recommender systems on consumer purchases was highlighted, and the authors developed practical strategies to facilitate the formation of the consideration sets.
Abstract: The findings underscore the important role of consumers’ consideration sets in mediating the positive effects of recommender systems on consumer purchases. Practical strategies can be developed to facilitate the formation of the consideration sets. For example, to reduce consumers’ search costs and cognitive efforts, online retailers can display the recommended products in a descending order according to the predicted closeness of consumers’ preferences. Online retailers can further indicate the predicted closeness scores of consumers’ preferences for the recommended products. Given such a placement arrangement, consumers can quickly screen the recommended products and add the most relevant alternatives to their consideration sets, which should facilitate consumers’ shopping process and increase the shopping satisfaction. The findings also suggest that a larger consideration set due to the use of recommender systems could induce consumers to buy. Yet, it is difficult for consumers to manage many alternatives when the consideration set is very large. To facilitate consumers’ shopping process, online retailers need to consider strategies and tools that help consumers manage the alternatives in the consideration set in a better-organized manner and facilitate the comparison across the alternatives.
TL;DR: In this article , the authors examined the impact of platform self-regulations in the context of the home-sharing market using policy changes that reduce the number of Airbnb listings and empirically test the impact on crime rates.
Abstract: The rise of the sharing economy has disrupted traditional industries and has had many unforeseen societal impacts. This has sparked policy debates on whether and how the sharing economy should be regulated to promote the healthy growth of such markets. In this research, we examine the impact of platform self-regulations in the context of the home-sharing market. Using policy changes that reduce the number of Airbnb listings, we empirically test the impact of platform self-regulations on crime rates. Our results suggest that a reduction in Airbnb listings resulting from platform self-regulations leads to a reduction in crime. We further study the impact of these policy changes on different types of crime and find that these self-regulations lead to a reduction in incidents of crime such as assault, robbery, and burglary but an increase in theft incidents. In addition, we find that the impact of these policies varies based on the neighborhood’s characteristics, such as income, housing price, and population. This research contributes to our understanding of the societal impacts of the sharing economy and the impact of platform self-regulation. Our findings also provide empirical evidence to inform policy making.
TL;DR: In this article , the authors examine how different configurations of seeker exemplars affect the quantitative outcomes in solvers' scanning, shortlisting, and selection of ideas and suggest ways that contest platforms can contribute to the idea generation process that solvers undertake.
Abstract: Crowdsourcing ideation contests allow solution-seeking firms (seekers) to solicit ideas from external individuals (solvers). Contest platforms often recommend seekers to provide examples of solutions (i.e., seeker exemplars) to guide and inspire solvers in generating ideas. In this study, we delve into solvers’ ideation process and examine how different configurations of seeker exemplars affect the quantitative outcomes in solvers’ scanning, shortlisting, and selection of ideas. Results from an online experiment show that solvers generally search for, shortlist, and/or submit fewer ideas when shown certain seeker exemplars. In addition, solvers who submit fewer ideas tend to submit lower-quality ideas, on average. Thus, a key insight from this study is that showing seeker exemplars, which contest platforms encourage and seekers often do, could negatively affect quantitative ideation outcomes and thereby impair idea quality. To help mitigate these adverse ideation outcomes, we propose a few areas of which seekers should be mindful. We also suggest ways that contests’ platforms can contribute to the idea generation process that solvers undertake.
TL;DR: In this article , the authors examined whether leveraging omnichannel data can lead to statistically and economically, significantly better predictions on consumers' online path-to-purchase journeys, given the intrinsic fluidity in and heterogeneity brought forth by digital transformation of traditional marketing.
Abstract: The proliferation of omnichannel practices and emerging technologies opens up new opportunities for companies to collect voluminous data across multiple channels. This study examines whether leveraging omnichannel data can lead to, statistically and economically, significantly better predictions on consumers’ online path-to-purchase journeys, given the intrinsic fluidity in and heterogeneity brought forth by digital transformation of traditional marketing. Using an omnichannel data set that captures consumers’ online behavior in terms of their website browsing trajectories and their offline behavior in terms of physical location trajectories, we predict consumers’ future path-to-purchase journeys based on their historical omnichannel behaviors. Using a state-of-the-art deep-learning algorithm, we find that using omnichannel data can significantly improve our model’s predictive power. This enhanced predictive power benefits various heterogeneous online firms, regardless of their size, offline presence, mobile app availability, or whether they are selling single- or multi-category products. Using an illustrative example of targeted marketing, we further quantify the economic value of the improved predictive power and the value of data.
TL;DR: In this article , the potential efficacy of an informational intervention, namely, the disclosure of peers' recent demand, was investigated in online dating platforms, and the intervention is particularly effective at improving matching efficiency when presented in tandem with a textual message-framing cue that highlights the capacity implications of the peer demand information.
Abstract: In online dating platforms, users tend to focus their attention on a subset of popular peers, leading to congestion. We consider the potential efficacy of an informational intervention, namely, the disclosure of peers’ recent demand. We evaluate our treatment’s efficacy in mitigating congestion and improving matching efficiency, conducting a randomized field experiment at a large mobile dating platform. Our results show that the intervention is particularly effective at improving matching efficiency when presented in tandem with a textual message-framing cue that highlights the capacity implications of the peer demand information. Heterogeneity analyses further indicate that these effects are driven primarily by those users who most contend with congestion in the form of competition, namely, male users and those who rely more heavily upon outbound messages for matches.
TL;DR: The authors find that social media users are likely to reshare unverifiable messages when they exhibit characteristics of plausibility, vividness, and sender credibility, which signal the novelty of helpfulness of the message.
Abstract: Unverifiable messages abound on the Internet. As policymakers and social media platforms grapple with the spread of misleading, false, or otherwise harmful messages, it is important they better understand why users share messages they cannot verify. This article reports on two studies that shed light on such issues. In the first study, the authors leverage secondary data collected from Twitter to show that true and false unverifiable messages have different characteristics and that those characteristics are predictive of retweeting. In the second study, they conduct a controlled experiment to explain why such characteristics influence resharing. Jointly, these studies show that leaks (i.e., true-but-unverifiable) tend to be more plausible, more vivid, and are sent by more credible senders than rumors (i.e., false-but-unverifiable). Further, the relationships among these variables is multiplicative such that the effects of vividness and sender credibility are strengthened for plausible and weakened for implausible messages. Finally, message recipients use these characteristics to determine whether an unverifiable message is novel and/or helpful. In sum, the authors find that social media users are likely to reshare unverifiable messages when they exhibit characteristics of plausibility, vividness, and sender credibility, which signal the novelty of helpfulness of the message.
TL;DR: In this article , a multidimensional conceptualization of the information systems (IS) discipline's intellectual diversity and applying it to information systems research (ISR) is presented, and an empirical analysis of the intellectual diversity exhibited by the full set of ISR articles published in over the last 10 years is provided.
Abstract: This paper advances the understanding of the information systems (IS) discipline by developing a multidimensional conceptualization of the discipline’s intellectual diversity and applying it to information systems research (ISR). It provides an empirical analysis of the intellectual diversity exhibited by the full set of ISR articles published in over the last 10 years. We categorize IS intellectual diversity into four intellectual dimensions of IS research—namely, domain topic, level of phenomenon, type of contribution, and method—and highlight differences along these dimensions. We use our framework to describe the ebb and flow of the topics, methods, and contributions of IS scholarship that appears in ISR during 2012–2021. Our analysis shows a preponderance of econometric and modeling studies. It also shows that there is a substantial variety of topics, research questions, and methods. Based on these conceptual and empirical insights, we identify implications for intellectual diversity and inclusion in the broader IS discipline.
TL;DR: In this paper, the authors developed an integrative model that explains bystanders' joining-in cyberbullying behaviors on SNSs to offer actionable insights into reducing such harmful behaviors, and tested the model using 1,179 responses using a scenario survey study.
Abstract: Bystanders Join in Cyberbullying on Social Networking Sites: The Deindividuation and Moral Disengagement Perspectives Cyberbullying on social networking sites escalates when bystanders join in the bullying. Bystanders’ joining-in behaviors reinforce the abuse, expose victims to a larger audience, and encourage further abuse by signaling their approval of the aggressive behavior. This study developed an integrative model that explains bystanders’ joining-in cyberbullying behaviors on SNSs to offer actionable insights into reducing such harmful behaviors. We tested the model using 1,179 responses using a scenario survey study. Our findings suggest that IT artifacts (including digital profile, search and privacy, relational ties, and network transparency) activated two key mechanisms that lead to cyberbullying joining-in behaviors: (i) the deindividuation experiences that attenuate self-identity and put salience on group/social identity, and (ii) the moral disengagement practices that permit the exercise of cognitive maneuvers to justify group-interested choices that do not align with social standard. The findings explain why people who do not know each other gang up to bully a target on social media. Platform owners who wish to discourage bystanders from joining in undesirable activities may consider regulating how users could share and access digital resources in a social network and should acknowledge the influence of social identity in igniting, driving, and prolonging harmful online group behaviors.