Strategy, Information, Technology, Economics, and Society (SITES)

Permanent URI for this collectionhttps://hdl.handle.net/10125/72270

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Now showing 1 - 13 of 13

Should We Outlaw Ransomware Payments?
(2021-01-05) Dey, Debabrata; Lahiri, Atanu
Recently, there has been an upsurge in ransomware attacks. A ransomware attacker encrypts a user's files and then demands a ransom in exchange for the decryption key. While paying the ransom allows the user to quickly unlock the locked files and avoid potentially larger losses, it also strengthens the hands of the attacker and increases the chance of a future attack. We study this dilemma of the victims using a game-theoretic model and the resulting equilibrium. This leads to several interesting insights such as that legally prohibiting ransom payments may not always have the desired economic effects---in some cases, a ban is effective in addressing the economic externality but, in others, it may reduce overall welfare. We explain when and why a ban may help and when it may not. Our findings have important implications for policymakers who are currently debating laws that, if enacted, will ban payments to attackers.
Seeing Humans in the Data: Ethical Blind Spots of Taiwan Academic Researchers in the Era of Behavioral Big Data
(2021-01-05) Fell, Jan; Shmueli, Galit; Greene, Travis; Wang, Jyun-Cheng; Ray, Soumya; Wu, Shu-Yuan
The advent of Behavioral Big Data (BBD) has profoundly impacted research ethics. At the same time, academic disciplines with no experience in human subjects research increasingly make use of BBD datasets. In this first-of-its-kind study, we evaluate Taiwan academic researchers’ knowledge and awareness of data ethics using a series of four BBD-based hypothetical research scenarios. We uncover several data ethics blind spots affecting academic researchers. Through the results of this research we hope to strengthen academic researchers’ data ethics awareness and knowledge in the context of BBD, and provide suggestions for improving the ethics training of academic researchers conducting BBD studies. We also contribute a re-conceptualization of data ethics encompassing both traditional human subjects research ethics and new paradigms for the regulation of personal data, such as the General Data Protection Regulation (GDPR).
Is Data Ownership Empowerment Welfare-Enhancing?
(2021-01-05) Li, Shilei; Feng, Juan
Under current business models, consumers have to hand over their personal data to “digital giants” in exchange for high-quality services. Should consumers be empowered to have ownership towards the data they generated through their own actions in the platform firm’s site? New technologies emerge to empower consumers to control their own data, and the platform firm may need to compensate for the usage of consumers’ private data. How consumers and the firm should react to such data ownership empowerment policy, however, is not clear. We build a theoretical model in which consumers have different sensitivities to the loss of data ownership. We show that the impact of data ownership empowerment depends not only on the firm’s revenue structure, but also on consumers’ need for customized services. The results of the welfare analysis offer managerial implications for policy making.
Inferring Supplier Quality in the Gig Economy: The Effectiveness of Signals in Freelance Job Markets
(2021-01-05) Kathuria, Abhishek; Saldanha, Terence; Khuntia, Jiban; Andrade Rojas, Mariana; Mithas, Sunil; Hah, Hyeyoung
Inferring quality of labor suppliers is a challenge in the gig economy. Many online freelance job markets address this challenge by incorporating signals. We test effectiveness of two kinds of information signals as indicators of supplier quality: skill signal (which reflects suppliers’ skill and potential), and achievement signal (which reflects suppliers’ past achievement). We theorize that two job characteristics in cross-national labor demand settings strengthen effectiveness of these signals: job duration, and cultural distance. Econometric analysis on a dataset from a leading online freelance job marketplace containing information on jobs posted by buyers and completed by suppliers located across several countries supports our hypotheses. We find that both skill and achievement signals are more effective at inferring supplier quality in jobs involving longer duration, and in jobs involving greater cultural distance between buyers and suppliers.
Fundamentals for the Design of Products for a Circular Economy: Examples from Software Engineering To Motivate Efficient and Ethical Design of Physical Products
(2021-01-05) Clemons, Eric; Teilmann-Lock, Stina
Often research in information systems looks for reference disciplines, like information economics or game theory, that can inform and motivate our re-search. Here we reverse that paradigm and offer an area in which information system provides a reference discipline for the design of physical products. Design for the Circular Economy is a green initiative that goes beyond recycling and focuses on the design of products that can remain in use almost indefinitely, and thus are not replaced and are not recycled. This leads to products for which maintenance, repair, upgrades, and style enhancements are less wasteful. This usually requires breakthroughs in design and in manufacturing processes. There is a small set of design principles that enable Design for the Circular Economy, and that yield long-term benefits in the ownership and operation of products. Green design for the Circular Economy becomes relevant even for products with shorter life-times and lower costs.
Effects of Sentiments on the Morphing of Falsehoods and Correction Messages on Social Media
(2021-01-05) King, Kelvin; Wang, Bin; Escobari, Diego
The burgeoning literature on fake news reveals that the emotional context of the message is a major factor that drives its diffusion on social media. However, studies have largely missed a major aspect of the diffusion process, which is the morphing of the textual contents themselves during this process. Our study first visually illustrates through hazard functions that, while falsehoods morphs aggressively at the initial stages, correction messages morph more aggressively in the long run. In addition, we leverage on cosine distance and econometric modeling to empirically investigate how sentiment affects the morphing of fake news and their correction messages. We find that positive sentiments, emotionally charged messages and correction messages positively affect the morphing of messages during the diffusion process. Our results also show that, as time goes by, the impacts of sentiments on morphing change.
Does Exposure to Shared Solutions Lead to Better Outcomes? An Empirical Investigation in Online Crowdsourcing Contests
(2021-01-05) Hou, Jingbo; Chen, Pei-Yu; Gu, Bin
Crowdsourcing contests provide an effective way to elicit novel ideas and creative solutions from collective intelligence. A key design feature of crowdsourcing contests is the competition between contest participants to complete a specific task with financial awards to the winner(s). In recent years, some crowdsourcing contest platforms provide options to contest participants for solution sharing during the competition. This study intends to evaluate the influence of exposure to shared solutions on different stakeholders, including the team, and the requester. Our study employs a multiple-level panel data from a large online crowdsourcing platform, Kaggle.com, to examine these effects. For teams, exposure to shared solutions helps new entrant teams to jump-start and help teams to achieve better performance in the subsequent submissions, and the teams’ skill level negatively moderates these positive effects. For requesters, allowing solution sharing has both benefits and costs in terms of improving the best performance of the crowd. We highlight the theoretical implications of the study and provide practical suggestions for crowdsourcing contest platforms to help them decide whether to allow solution sharing during the competition.
Creators and Backers in Rewards-Based Crowdfunding: Will Incentive Misalignment Affect Kickstarter’s Sustainability?
(2021-01-05) Wessel, Michael; Gleasure, Rob; Kauffman, Robert
Incentive misalignment in rewards-based crowd-funding occurs because creators may benefit disproportionately from fundraising, while backers may benefit disproportionately from the quality of project deliverables. The resulting principal-agent relationship means backers rely on campaign information to identify signs of moral hazard, adverse selection, and risk attitude asymmetry. We analyze campaign information related to fundraising, and compare how different information affects eventual backer satisfaction, based on an extensive dataset from Kickstarter. The data analysis uses a multi-model comparison to reveal similarities and contrasts in the estimated drivers of dependent variables that capture different outcomes in Kickstarter’s funding campaigns, using a linear probability model (LPM), which is a special case of the binary probability model. Our results reveal inconsistencies in funding information compared to backers’ satisfaction, and a plat-form-wide trend of decreasing satisfaction. The findings broadly suggest fundraising is influenced by information disclosure and backer feedback, while eventual backer satisfaction is closely potentially caused by in-formation about deferred compensation and long-term relationship-building.
Collaborative Innovation (or Not?!) when Product Performance is Critical
(2021-01-05) Weber, Thomas
Research and development (R&D) collaborations are horizontal agreements among firms to join forces in their inventive activities. As in the context of the recent COVID-19 global pandemic, such collaborations are often promoted with an argument of increased R&D productivity. In numerous contexts, especially when marginal production costs are low, such as for medications or for software, the consumers' surplus depends critically on the best-performing product available on the market, for -- all else equal -- this product will tend to take a dominant position. Using a simple two-stage model of innovation and subsequent product commercialization on a market with heterogeneous consumers, we show that a noncollaborative patent race with patent protection (for the best product) provides strong innovation incentives, leading to better performing products than a regime of either noncollaborative research without patent protection or collaborative research (with profit sharing).
Chronic Complainers or Increased Awareness? The Dynamics of Social Media Customer Service
(2021-01-05) Sun, Shujing; Gao, Yang; Rui, Huaxia
Despite that social media has become a promising alternative to traditional call centers, managers hesitate to fully harness its power because they worry that active service intervention may encourage excessive use of the channel by disgruntled customers. This paper sheds light on such a concern by examining the dynamics between brand-level customer complaints and service interventions on social media. Using details of customer-brand interactions of 40 airlines on Twitter, we find that more service interventions indeed cause more customer complaints, accounting for the online customer population and service quality. However, the increased complaints are primarily driven by the awareness enhancement mechanism rather than by chronic complainers. Furthermore, holding everything else fixed, high-quality care leads to fewer future complaints. The managerial implication is clear: firms shall implement a more active, prompt, and effective strategy, which can redirect customers to this cost-effective service channel and ultimately reduce customer churn.
A Scaling Perspective on AI Startups
(2021-01-05) Schulte-Althoff, Matthias; Fürstenau, Daniel; Lee, Gene Moo
Digital startups’ use of AI technologies has significantly increased in recent years, bringing to the fore specific barriers to deployment, use, and extraction of business value from AI. Utilizing a quantitative framework regarding the themes of startup growth and scaling, we examine the scaling behavior of AI, platform, and service startups. We find evidence of a sublinear scaling ratio of revenue to age-discounted employment count. The results suggest that revenue-employee growth pattern of AI startups is close to that of service startups, and less so to that of platform startups. Furthermore, we find a superlinear growth pattern of acquired funding in relation to the employment size that is largest for AI startups, possibly suggesting hype tendencies around AI startups. We discuss implications in the light of new economies of scale and scope of AI startups related to decision-making and prediction.
Are Review Helpfulness Score and Review Unhelpfulness Score Two Sides of The Same Coin or Different Coins?
(2021-01-05) Khern-Am-Nuai, Warut; Yu, Yinan
Online review platforms have increasingly incorporated the review evaluating system (i.e., a system that allows users to evaluate whether reviews are helpful/unhelpful) to assist review readers and encourage review contributors. However, although we have extensive knowledge about the review helpfulness score, our insights regarding its counterpart, the review unhelpfulness score, are lacking. Addressing this limitation is important because many researchers have adopted the review unhelpfulness score assuming that it is driven by intrinsic review characteristics while practitioners also implicitly assume that the unhelpfulness score can identify low-quality reviews. The primary objective of this work is to verify whether the review unhelpfulness score is influenced by intrinsic review characteristics that drive review helpfulness score. We find that unlike review helpfulness score, unhelpfulness score is not driven by intrinsic review characteristics, and that helpfulness voters behave significantly different than unhelpfulness voters. Further implications and future directions are also discussed.
Introduction to the Minitrack on Strategy, Information, Technology, Economics, and Society (SITES)
(2021-01-05) Kauffman, Robert; Weber, Thomas

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