Bridging the Gap between Education and Practice: The Case of iD Lab

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Adelakun, Olayele; Bui, Quang “Neo”

Abstract: Universities are currently under pressure from multiple fronts: students questi ... Expand

Abstract: Universities are currently under pressure from multiple fronts: students questioning their value propositions due to rising tuition costs, employers being frustrated at the skill gap and lack of experience in recent graduates, and communities asking for higher societal impacts from local universities. Facing these challenges, universities have focused on experiential learning to bridge the gap between education and practice while increasing community engagement. In this paper, we use a case study approach to present the experiential learning model at iD Lab, DePaul University. The success of the iD Lab comes from a tight coupling of experiential learning and engaged scholarship. Three illustrative projects show keys to success are good relationships with the clients and high-quality product deliverables. Collapse

Topics: analytical information system innovation management

Methods: case study action research literature study machine learning

The Evaluation of Founder Failure and Success by Hiring Firms: A Field Experiment

2023 | Organization Science | Citations: 0

Authors: Botelho, Tristan L.; Chang, Melody

Abstract: Organizations tout the importance of innovation and entrepreneurship. Yet, when ... Expand

Abstract: Organizations tout the importance of innovation and entrepreneurship. Yet, when hiring it remains unclear how they evaluate entrepreneurial human capital—namely, job candidates with founder experience. How hiring firms evaluate this experience—and especially how this evaluation varies by entrepreneurial success and failure—reveals insights into the structures and processes within organizations. Organizations research points to two perspectives related to the evaluation of founder experience: Former founders may be advantaged, due to founder experience signaling high-quality capabilities and human capital, or disadvantaged, due to concerns related to fit and commitment. To identify the dominant class of mechanisms driving the evaluation of founder experience, it is important to consider how these evaluations differ, depending on whether the founder’s venture failed or succeeded. To isolate demand-side mechanisms and hold supply-side factors constant, we conducted a field experiment. We sent applications varying the candidate’s founder experience to 2,400 software engineering positions in the United States at random. We find that former founders received 43% fewer callbacks than nonfounders and that this difference is driven by older hiring firms. Further, this founder penalty is greatest for former successful founders, who received 33% fewer callbacks than former failed founders. Our results highlight that mechanisms related to concerns about fit and commitment, rather than information asymmetry about quality, are most influential when hiring firms evaluate former founders in our context. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1592. Collapse

Topics: IT career human resource management entrepreneurship systems development innovation management

Methods: qualitative interview field experiment theory development experiment experimental design

Theories: lemon market theory

Unpacking the Societal and Institutional Risks of Crypto Assets: The Policy-Innovation Nexus

2023 | International Conference on Information Systems | Citations: 0

Authors: Currie, Wendy; seddon, jonathan

Abstract: The Crypto Winter of 2022 exposed multi-dimensional risks in the crypto ecosyst ... Expand

Abstract: The Crypto Winter of 2022 exposed multi-dimensional risks in the crypto ecosystem which extend beyond technical imperatives to include societal and institutional factors. A domino effect saw several major crypto firms losing large amounts of investor cash or becoming bankrupt. This practitioner focused study adopts a grounded methodology to gather empirical data from regulators, crypto firms, and investors on developing a policy framework for crypto assets. The case study context is the US regulatory environment. Findings show regulatory agencies face ideological, operational, and technical obstacles, as they engage in debates about the efficacy of competing regulatory scenarios. The paper presents two major tensions which require the attention of policy makers and legislators to mitigate future societal and institutional risks from crypto assets. Collapse

Topics: cryptoasset innovation management decision making

Methods: qualitative interview grounded theory participant observation archival research qualitative coding

Someone Else to Blame: The Effectiveness of Egocentric and Alter-Centric Impression Management Tactics in the U.S. Food Retail Industry

2023 | Organization Science | Citations: 0

Authors: Diestre, Luis; Montauti, Martina; Pinto de Sousa, Helena

Abstract: We investigate the effectiveness of two types of impression management tactics i ... Expand

Abstract: We investigate the effectiveness of two types of impression management tactics implemented around negative attributes: egocentric (claiming the absence or low presence of a negative attribute in a focal organization) and alter-centric tactics (claiming the greater presence of a negative attribute in an organization’s competitor). We claim that the effectiveness of each tactic depends on the risk of audiences’ skepticism, which stems from the incongruence between the information conveyed in the tactic and audiences’ default expectations about the presence of the attribute among members of a given market segment. Audiences expect a conspicuous presence of the attribute, we propose, the more stakeholders contest a market segment for that very attribute. Thus, we advance that egocentric (alter-centric) tactics are less likely to be effective for contested (uncontested) attributes because the information conveyed in such tactics clashes with audiences’ default expectations, triggering skepticism. We find support for our predictions looking at the impact of nutrient content claims on product sales in the U.S. food retail industry between 2006 and 2015. Funding: H. Pinto de Sousa acknowledges the support, in the form of a research scholarship, granted by the Portuguese Foundation for Science and Technology (Fundação para a Ciência e Tecnologia), under the European Social Fund and the Human Capital Operational Program (Programa Operacional Capital Humano) funding program [Grant SFRH/BD/128536/2017]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1612. Collapse

Topics: database system marketing management Twitter social influence sensemaking

Methods: experimental group survey descriptive statistic statistical hypothesis test probit regression

Why Do I Share My Predictions of Stock Returns in Online Communities? An Empirical Study on StockTwits

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Fang, Bin; Yao, Yao; Shangguan, Wuyue; Li, Ziru

Abstract: Online investment communities have been widely adopted by investors to disclose ... Expand

Abstract: Online investment communities have been widely adopted by investors to disclose investment-related information, such as predictions of stock returns. Although it benefits both platforms by attracting more users and other investors by providing additional finely-processed information, it may hurt publishers due to the potential loss of their unique valuable private information. Therefore, understanding why users share their own predictions in online communities becomes an important issue. Drawing on the abilitymotivation-opportunity framework, we seek to identify three important factors influencing users' willingness to share predictions. Utilizing data obtained from StockTwits, our preliminary results show that the number of followers, prediction accuracy, and historical stock performance negatively affect users' sharing of their predictions of stock returns. Our findings can contribute to the literature on information sharing and provide managerial implications for online investment communities. Collapse

Topics: information exchange personality online community open source community microblog

Methods: natural language processing BERT

Take It or Not? Impact of Taking Investments from Tech Giants on IT Startups’ Future Funding

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Huang, Linmei; Wang, Shuting (Ada); Lang, Karl

Abstract: While tech giants have become important external equity financing sources, it r ... Expand

Abstract: While tech giants have become important external equity financing sources, it remains unclear whether ITstartups should take investments from tech giants. In this study we empirically examine how taking investments from tech giants influences future funding of IT-startups. Our results indicate that taking investments from tech giants significantly reduces the amount of funding IT-startups could obtain in the following rounds. Additionally, we find that social ties between IT-startups' regions and locations with substantial capital will attenuate such negative impact of taking investments from tech giants. We further explore the mechanisms. Results suggest that when tech giants make investments in IT-startups, they predominate the new technologies by applying for more patents in the relevant fields and crowd out new investors. We contribute to the literature in IS by examining how investments from tech giants may influence the growth of IT-startups and how social ties may play a role in this interaction. Collapse

Topics: financial performance systems development artificial intelligence innovation management competitive advantage

Methods: propensity score matching experimental group theory development robustness check

Fake review detection system for online E-commerce platforms: A supervised general mixed probability approach

2023 | Decision Support Systems | Citations: 0

Authors: Luo, Jiwei; Luo, Jian; Nan, Guofang; Li, Dahui

Abstract: Online consumer reviews play an important role in helping consumers judge the qu ... Expand

Abstract: Online consumer reviews play an important role in helping consumers judge the quality and authenticity of products on e-commerce platforms. However, the constant presence of fake reviews on these platforms has significantly impacted the operation and development of e-commerce platforms. In this study, we develop a novel supervised probabilistic method to detect fake reviews by utilizing the difference in the distribution of nonfraudulent reviews and that of fake reviews. Specifically, we first derive the univariate distributions of several unique features (linguistic, behavioral, and interrelationship features). We then integrate these distributions into two mixed distributions according to their labels to represent the overall difference between non-fraudulent reviews and fake reviews. Next, we randomly generate synthetic review data points with different labels from the above mixed distributions. Finally, we train a Multilayer Perceptron model by using these synthetic review data to obtain a classifier. We conducted several experiments to test the model using several original real-world review datasets. Numerical results indicated that the proposed supervised method outperformed some wellknown sampling models and fake review detection methods, in terms of classification accuracy. Moreover, we extend the proposed method to handle the scenarios with small samples of raw review data. This study con­ tributes to the literature by exploiting the difference in the distribution of non-fraudulent reviews and that of fraudulent reviews, which can improve the accuracy of fake review detection for online platforms. Collapse

Topics: fake review electronic commerce big data decision support system user behavior

Methods: computational algorithm experiment machine learning semi-supervised learning artificial neural network

Cryptocurrency Market: The Interplay Between Microblog Dynamic Opinion Leader Sentiments and Bitcoin Pricing

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Treku, Daniel; Wang, Bin; Escobari, Diego; Oraby, Tamer

Abstract: The relationship between tweet sentiment and cryptocurrency pricing has drawn a ... Expand

Abstract: The relationship between tweet sentiment and cryptocurrency pricing has drawn academic researchers' attention in recent years. However, empirical results have been inconsistent, and no research has examined the bidirectional relationship between cryptocurrency pricing and tweet sentiment nor the impacts of opinion leaders. In this research, we test the presence of bidirectional relationships between Bitcoin opinion leader tweet sentiments and Bitcoin price behaviors. By analyzing a big data set of 78 million Bitcoin-related tweets from 2014 to 2021 through vector autoregression modeling with exogenous variables, we reveal the influences of Bitcoin opinion leaders' tweet subjectivity and polarity on Bitcoin price return and volatility, as well as the reverse effects. Our research contributes to academic literature and business practice on cryptocurrency pricing, social media, and opinion leadership. KeywordsBitcoin cryptocurrency returns, social media sentiment analysis, opinion leader sentiment analysis, twitter microblogs. Collapse

Topics: Bitcoin Twitter cryptocurrency price management social media

Methods: longitudinal research vector autoregression descriptive statistic computational algorithm Granger causality

Anchoring on Historical Round Number Reference Points: Evidence from Durable Goods Resale Prices

2023 | Organization Science | Citations: 0

Authors: Wiltermuth, Scott S.; Gubler, Timothy; Pierce, Lamar

Abstract: This paper examines how people price the resale of durable goods in systematical ... Expand

Abstract: This paper examines how people price the resale of durable goods in systematically biased ways. We show across four studies that the anchoring effect of durable goods’ prior sales prices on subsequent valuations is discontinuous at psychologically salient round number reference points (e.g., $10,000 increments) because these numbers create qualitative differences in how people perceive values below them versus values at/above them. Resellers set disproportionately larger subsequent prices when previous prices move from just below round number thresholds (e.g., $349,000) to those at or just above these thresholds (e.g., $351,000). The findings show that buyers who pay a price just below a round number, therefore, may sacrifice money because they receive disproportionately less when reselling the good. Market forces only partially attenuate this pricing bias, but valuator experience seems to play a moderating role. Archival data show that home buyers who previously paid just under a $10,000 reference point subsequently listed their homes for about 1.8% (over $3,700) less on average than did buyers selling comparable homes who previously paid at or above a round number threshold. This drop is observable controlling for home characteristics and the general relationship between previous and current prices. Three experimental studies looking at housing and used car markets replicate these findings, highlight the mechanism, and increase confidence in causality. Market mechanisms and the negotiation process attenuate discontinuities by about 30%, but lower initial listing prices persist to final sales prices. We find additional weak evidence suggesting that valuator experience may attenuate intergenerational pricing bias. Conflict of Interest: This manuscript was submitted, revised, and accepted prior to the nomination and appointment of Lamar Pierce as Editor-in-Chief. Funding: This project was supported by the University of Southern California Marshall School of Business Behavioral Laboratory. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1632. Collapse

Topics: price management computer hardware decision making human resource management website

Methods: experiment Wald test descriptive statistic parametric test hierarchical linear modeling

Rating deviation and manipulated reviews on the Internet—A multi-method study

2023 | Information & Management | Citations: 0

Authors: Xu, Yukuan; Xu, Xin

Abstract: Manipulated reviews can mislead consumers to make inappropriate purchase decisio ... Expand

Abstract: Manipulated reviews can mislead consumers to make inappropriate purchase decisions and reduce consumers’ dependency on online reviews, jeopardizing the platforms’ reputation. Existing studies mainly focus on the detection and the impact of manipulated reviews but are limited in examining the determinants of review legitimacy from the perspective of consumer perception. The current research introduces perceived review manipulation, defined as the extent to which an individual perceives a review as non-authentic with the goal of misleading others and influencing product sales. Using psychological reactance theory as a general framework, we investigate the impact of reviews with deviation from the average ratings on perceived review manipulation and review adoption. We future examine two boundary conditions of the above relationship—the moderating effects of review content concreteness and reviewer rating distribution. We adopt a multi-method approach to the empirical test of the research model. First, three online randomized experiments reveal that: (1) reviews with deviant ratings are more likely to be perceived as manipulated; (2) the relationship in (1) is enhanced when review content is abstract rather than concrete and when a reviewer is usually negative/positive (i.e., his/her rating distribution has positive/negative skewness) based on the deviation direction; and (3) perceived review manipulation negatively influences review adoption. Second, a field study was conducted to support the external validity of our research model. Our findings have academic and practical implications. Collapse

Topics: online review online word of mouth user-generated content word of mouth disinformation

Methods: experiment parametric test Student's t-test field study ANOVA

Theories: reactance theory