Value destruction is intertwined with value co-creation in the technology alliances and ecosystems; this is a key reason that most partnerships fail in the real world. Managers and policymakers will be enabled to identify destructive behavioral signals right from the onset drawing on our findings that opportunism, unjust appropriation of rents, shirking, exploitation of asymmetric power, and undue dependence can initiate the value destruction process. For the partners in an ecosystem, our findings underscore that opportunistic and exploitative behaviors do not pay off in the long run as these result in collateral and unintended losses for all. Dominant partner’s opportunism and exploitation of power asymmetry could give rise to a proverbial “pack of wolves,” a collective of resentful partners, for “challenging/killing the lion”—replacing the hub firm itself. In this vicious cycle, original intent of value co-creation gets lost with multidimensional losses on multiple fronts to the extent that opportunities open up even for the competitors with the help of hub’s former resentful complementors. Equipped with this knowledge, leaders can proactively manage ecosystem relationships keeping them on the path of originally intended value co-creation by remaining alert toward catching the signals of value destruction and reverting it deftly toward value co-creation.
With firms increasingly relying on external knowledge resources for solving complex problems, the role of digital platforms, which make this external search efficient, has become significant. For such platforms, of which Kaggle is an example, a perennial challenge is to elicit high-quality solutions from their voluntary contributors. To this end, our work underscores the importance of platform-wide design decisions for the quality of solutions that the platform's users generate. We show that a social feature that offers reputational gain may lead to significant quality improvements. Therefore, we recommend that platforms should view such features more favorably and include them. In addition, our work also suggests that firms that are using digital platforms to engage with external knowledge sources should time their activities, keeping in mind platform-wide design changes given that such changes can directly impact the firm's surplus.
The assumption that generativity engenders unbounded growth has acquired an almost taken-for-granted position in information systems and management literature. Against this premise, we examine the relationship between generativity and user base growth in the context of a digital platform. To do this, we synthesize the literature on generativity into two views, social interaction (expansion of ecosystem boundaries) and product view (expansion of product boundaries), that jointly and individually relate to user base growth. Both views help us explain how opening a platform relates to the emergence and resolution of conflicting expectations in a platform ecosystem that result in new functions and expanded use. We adopt a panel vector autoregressive approach combining data from six large transaction platforms that engaged with open-source developer communities. We found that the dominant narrative of generativity engendering growth, although generally supported by our analysis, obscures the fact that the inverse is also true; that is, growth can lead to expansion of product boundaries (inverse generativity) and that generativity can be bounded; that is, growth can stabilize ecosystem boundaries (bounded generativity). Against this background, we propose an extended generativity theory that presents generativity and growth in an integrative view and raises awareness about the limitations of the “unbounded growth” claim. We conclude that there is value in separating the two views of generativity conceptually and analytically, along with their relationship to user base growth, and we call for research on the pathways through which generativity produces growth. History: Ola Henfridsson, Senior Editor; Robert Wayne Gregory, Associate Editor.
The rise of emotional intelligence technology and the recent debate about the possibility of a “sentient” artificial intelligence (AI) urge the need to study the role of emotion during people’s interactions with AIs. In customer service, human employees are increasingly replaced by AI agents, such as chatbots, and often these AI agents are equipped with emotion-expressing capabilities to replicate the positive impact of human-expressed positive emotion. But is it indeed beneficial? This research explores how, when, and why an AI agent’s expression of positive emotion affects customers’ service evaluations. Through controlled experiments in which the subjects interacted with a service agent (AI or human) to resolve a hypothetical service issue, we provide answers to these questions. We show that AI-expressed positive emotion can influence customers affectively (by evoking customers’ positive emotions) and cognitively (by violating customers’ expectations) in opposite directions. Thus, positive emotion expressed by an AI agent (versus a human employee) is less effective in facilitating service evaluations. We further underscore that, depending on customers’ expectations toward their relationship with a service agent, AI-expressed positive emotion may enhance or hurt service evaluations. Overall, our work provides useful guidance on how and when companies can best deploy emotion-expressing AI agents.
Access to short-term capital remains a pressing problem for many people, especially those facing medical emergencies or needing immediate care. Peer-to-peer lending platforms have the ability to resolve these capital constraints by providing access to small to medium sums of money in an environment that is private and protective of personal information. In this study, we consider how the introduction of P2P lending platforms, and the resulting access to capital, influences local abortion rates, a medical procedure characterized by significant financial barriers and social stigma. We find that the entry of the P2P platform LendingClub is associated with an increase in the rate at which women choose to not carry to term. We argue that the availability of capital through these platforms, when combined with privacy protections, is able to reduce the financial barriers women face when accessing abortion services. This observed effect is stronger in more religious areas and areas with lower levels of education, indicating that social frictions and stigma may be higher in these areas, and also showing where providing an additional channel for funding is more influential.
Online learning is of growing importance to institutions and learners, and the COVID-19 pandemic has underscored its importance even more. Because learner autonomy is relatively high in these online environments, they must engage in self-regulated learning processes to achieve successful learning outcomes, but studies show that most learners are not able to do so. Hence, in this longitudinal field experiment, using a massively open online course (MOOCs), a type of online learning environment, we investigate whether gamified interventions through the learning platform can foster learners to engage in self-regulated learning processes and improve their learning outcomes. We find that gamification interventions are indeed useful, but for these gamification interventions to succeed, they must be designed to provide personalized feedback to learners that match with their learning goal-orientation. Overall, our findings point to the fact that gamification designs in online learning platforms can enhance learners’ engagement and learning outcomes, but they must be personalized. A one-size-fits-all approach to gamification design in online learning just does not work and may even backfire to reduce the engagement of some learners.
We live in a time when digital technologies reshape most aspects of business and social life. This challenges received assumptions about modes of operation in organizations. As a result, scholars and practitioners increasingly use the label “digital” to signify that something has changed to the extent that a plethora of long-established management concepts are expressed in a new formulaic form of “digital x,” and x can stand for innovation, strategy, transformation, infrastructure, etc. In the information systems discipline and beyond, “digital” has emerged as an oft-used conceptual label to characterize age-long phenomena hitherto described by the IT (or x) label. There is a sense among academic and practitioner communities that digital and IT are not mere synonyms, but beyond the hype, something fundamentally different is being signaled when the “digital” label is invoked. This paper traces the intellectual roots and foundations of the growing use of “digital” as a conceptual label, identifies when the label use is warranted as well as outlines implications that the moniker holds for future scholarship, policy, and practice. In particular, the paper offers actionable guidance that enables more reflective use of the term “digital” as we move forward.
Blockbuster projects on crowdfunding platforms are those that have achieved outstanding and exceptional performance. Regarding the impact of blockbuster projects on crowdfunding platforms, there are two plausible yet opposing predictions: they may exhibit both a negative effect by monopolizing backer attention and resources and a positive effect by increasing the activeness of backer side. This tension could be further complicated, considering that blockbusters are inherently heterogeneous. Drawing on the cross-side network effects literature and integrating insights from the unique features of crowdfunding, we develop a theoretical framework highlighting the multidimensional view of blockbuster effects: blockbuster projects have an overall positive effect on the performance of concurrent projects (overall effect), and such positive effect is stronger for related blockbusters (local effect) and blockbusters emerging before the focal project (temporal effect). With data from a leading crowdfunding platform, the empirical analyses largely support our proposed framework. Using off-platform data and backer data, we unveil the mechanism driving the blockbuster effects: blockbusters increase the popularity of the platform, whereby backers participating in the blockbusters tend to develop positive impressions and heightened expectations, so that they are likely to participate in other concurrent projects. Our findings have important implications for project creators and platform operators.
Online reviews are very instrumental in driving customer behaviors. This coupled with the fact that negative reviews seem to have a stronger effect on customer behaviors raises the stakes for managers to effectively respond to such reviews in order to protect their brand. However, given the exponential growth in the volume of reviews, a strategic approach that enables managers to focus their efforts in responding to negative reviews is needed. This paper develops a framework to classify negative reviews and managerial responses and examines how the fit between the nature of review and the nature of managerial response impacts the customers’ complaining behavior in the future. We focus on the mix of rational and emotional cues in exploring the appropriateness of managerial responses to negative reviews. Using text analysis (e.g., natural language processing and deep learning) and using large sale review and response data from TripAdvisor, we extract and code the variables in our model. The findings provide specific and actionable guidelines for responding to negative reviews in online forums. First, managers should respond to negative reviews in order to safeguard the brand and improve firm reputation. Second, managers should be aware that they can respond both rationally and emotionally to negative reviews. Whereas emotional responses have been the preferred mode in most firms, our theorizing and findings clearly indicate response with rational cues is also particularly important in dealing with complaints. When complaints pertain to primarily the procedures in the service delivery process such as speed and flexibility, managers should respond with rational cues that explain the reasons for the service failure and the steps taken to address such failures and reinforce the value of the service provided by the firm. When customers complain only about the nature of their interactions with the hotel or also file grievances about the services not aligning with their needs, managers should respond with more emotional cues such as apologizing or appreciating the customer for patronage and being attentive to the empathy and emotional gratification needs of customers. When customers complain that they were discriminated against, they were not getting what they deserve, or the service did not meet their requirements, managers should respond with both rational cues that explain the discrepancy between actions and expected outcomes and providing some compensation and emotional cues that satisfy the customers’ need for emotional gratification. Such customized and calibrated responses that are appropriate for the nature of the complaint would be critical in shaping the views of other customers in the online review forum. Firms, in their efforts to deal with the growing volume of reviews, have increasingly automated the response process using template responses. Our findings suggest that a more deliberate approach of carefully tailoring the responses to negative reviews is likely to be beneficial in online review forums. Firms could use a data-driven approach of extracting and classifying the nature of complaints according to our proposed framework. Recent advances in machine learning algorithms allow for such classification with greater precision. Instead of drafting each response from scratch, managers can use machine-written skeletons in their responses to target some specific reviews. Firms could then generate responses that are tailored to the nature of the complaints. Such approaches to generate tailored responses could allow firms to deal with the large review volumes in a more effective manner.
Online health question-and-answer platforms (OHQPs), where patients post health-related questions, evaluate advice from multiple doctors and select their most preferred answer, are a prominent channel for patients to receive medical advice in China. They are gaining traction globally and have the potential to circumvent resource-based, geographic, or circumstantial barriers that limit access to care. At the same time, they are underregulated in contrast to brick-and-mortar points of care. Ours is the first study to evaluate the quality of healthcare advice promoted by these platforms and to provide insight into how patients respond to advice. We found that, though advice is generally good, patients cannot discern good advice from bad, choose poor advice (when offered) as often as good advice, and do so to a greater extent in vulnerable categories such as pediatrics, cancers/tumors, and internal medicine. Moreover, we found that OHQPs exacerbate care avoidance. Our findings suggest that platform owners and policymakers should ensure that signals of expert consensus are provided to patients to better assist their choices on OHQPs. We also unveiled bad actors on OHQPs, including drug promoters and spammers, indicating that stronger oversight and accountability mechanisms are needed. Physician peer reviewing and auditing can address both problems.