Jian Li, Xiang (Shawn) Wan, Hsing Kenneth Cheng, Xi Zhao
Practice AbstractInitial Coin Offerings (ICOs) have become a new and popular fundraising approach for blockchain start-ups. To motivate blockchain individuals to invest in the subsequent ICO, a growing number of blockchain-based project founders employ the airdrop campaign, through which they distribute a specific amount of free official tokens or promotional tokens to potential investors on the blockchain with or without their permission. Of paramount concern to the blockchain founders contemplating whether to launch an airdrop campaign are whether the airdrop campaign has a positive effect on the potential investors’ investment behaviors in their ICOs and how the efficacy of the airdrop may vary with investors. We find that the promotional airdrop significantly increases the potential investors’ ICO investment. We further find that the airdrop is more effective in increasing the investment for individuals with transacted projects dissimilar to the focal project than those with similar ones. By incorporating the insights from our study into their airdrop campaign strategy, blockchain start-ups can effectively target the right segment of potential investors to enhance the success of their ICOs.
{"title":"Operation Dumbo Drop: To Airdrop or Not to Airdrop for Initial Coin Offering Success?","authors":"Jian Li, Xiang (Shawn) Wan, Hsing Kenneth Cheng, Xi Zhao","doi":"10.1287/isre.2021.0450","DOIUrl":"https://doi.org/10.1287/isre.2021.0450","url":null,"abstract":"Practice AbstractInitial Coin Offerings (ICOs) have become a new and popular fundraising approach for blockchain start-ups. To motivate blockchain individuals to invest in the subsequent ICO, a growing number of blockchain-based project founders employ the airdrop campaign, through which they distribute a specific amount of free official tokens or promotional tokens to potential investors on the blockchain with or without their permission. Of paramount concern to the blockchain founders contemplating whether to launch an airdrop campaign are whether the airdrop campaign has a positive effect on the potential investors’ investment behaviors in their ICOs and how the efficacy of the airdrop may vary with investors. We find that the promotional airdrop significantly increases the potential investors’ ICO investment. We further find that the airdrop is more effective in increasing the investment for individuals with transacted projects dissimilar to the focal project than those with similar ones. By incorporating the insights from our study into their airdrop campaign strategy, blockchain start-ups can effectively target the right segment of potential investors to enhance the success of their ICOs.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"14 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139760910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiawei Chen, Luo He, Hongyan Liu, Yinghui (Catherine) Yang, Xuan Bi
On short video sharing platforms, users often choose background music for their videos. In this paper, we study the problem of background music recommendation for short videos on short video sharing platforms. In our recommendation setting, the item (music) is not recommended directly to the user, but to the video created by the user. When making music recommendations for videos, we consider three important players: users, videos, and music. We define a unique background music recommendation problem and design a novel background music recommendation model to address the problem. We propose a model based on the deep learning framework to effectively address the distinctive three-way relationships among users, videos, and music. Our model considers not only of the conventional user–music alignment, but also the alignment between videos and music. To evaluate our model, we conduct comprehensive experiments on real-world data collected from one of the most popular short video sharing platforms. Our proposed model significantly outperforms other existing models in recommendation performance. The superiority of our proposed model remains consistent across various scenarios, including cold-start recommendations, data sets with varying density levels, and data sets spanning diverse video categories.
{"title":"Background Music Recommendation on Short Video Sharing Platforms","authors":"Jiawei Chen, Luo He, Hongyan Liu, Yinghui (Catherine) Yang, Xuan Bi","doi":"10.1287/isre.2022.0093","DOIUrl":"https://doi.org/10.1287/isre.2022.0093","url":null,"abstract":"On short video sharing platforms, users often choose background music for their videos. In this paper, we study the problem of background music recommendation for short videos on short video sharing platforms. In our recommendation setting, the item (music) is not recommended directly to the user, but to the video created by the user. When making music recommendations for videos, we consider three important players: users, videos, and music. We define a unique background music recommendation problem and design a novel background music recommendation model to address the problem. We propose a model based on the deep learning framework to effectively address the distinctive three-way relationships among users, videos, and music. Our model considers not only of the conventional user–music alignment, but also the alignment between videos and music. To evaluate our model, we conduct comprehensive experiments on real-world data collected from one of the most popular short video sharing platforms. Our proposed model significantly outperforms other existing models in recommendation performance. The superiority of our proposed model remains consistent across various scenarios, including cold-start recommendations, data sets with varying density levels, and data sets spanning diverse video categories.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"190 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139656909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Air pollution contributes to global warming and climate change, leading to extreme weather events and rising sea levels. Promoting sustainable practices has become the focus of policy programs and awareness campaigns. In this study, we propose an effective and powerful way to promote eco-driving behaviors by drawing on data storytelling. Our study shows that animated narrative and narrative sequence can trigger varying emphases on the feasibility and desirability of eco-driving practices, affecting actual driving behaviors and attitudes toward efficient driving. Specifically, in two experiments, we find that a chronological narrative sequence with animation improves subsequent driving efficiency and efficient driving attitudes. Visualization designers may consider employing narrative sequence and animation to facilitate individuals’ information comprehension and behavioral changes. Policymakers can also encourage ecological practices through effective designs of data storytelling.
{"title":"Encouraging Eco-driving with Post-trip Visualized Storytelling: An Experiment Combining Eye-Tracking and a Driving Simulator","authors":"Zhiyin Li, Ben C. F. Choi","doi":"10.1287/isre.2022.0332","DOIUrl":"https://doi.org/10.1287/isre.2022.0332","url":null,"abstract":"Air pollution contributes to global warming and climate change, leading to extreme weather events and rising sea levels. Promoting sustainable practices has become the focus of policy programs and awareness campaigns. In this study, we propose an effective and powerful way to promote eco-driving behaviors by drawing on data storytelling. Our study shows that animated narrative and narrative sequence can trigger varying emphases on the feasibility and desirability of eco-driving practices, affecting actual driving behaviors and attitudes toward efficient driving. Specifically, in two experiments, we find that a chronological narrative sequence with animation improves subsequent driving efficiency and efficient driving attitudes. Visualization designers may consider employing narrative sequence and animation to facilitate individuals’ information comprehension and behavioral changes. Policymakers can also encourage ecological practices through effective designs of data storytelling.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"44 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139656912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Policy/Practice-Focused AbstractDespite considerable and continued resource investments, effective solutions to broad-scope problems of social interest or societal grand challenges (GCs) have proven to be elusive in many domains. In multiactor situations that characterize GCs, divergent goals, needs, priorities, and capabilities of global and local actors create organizing design tensions that need to be considered before solutions can be enacted. Emergent digital technologies can play an important and transformative role in addressing the organizing design tensions that pervade such collective action problems. In this article, we draw on Elinor Ostrom’s principles of public value creation and identify a set of eight organizing design tensions that arise from employing global and local perspectives in addressing GCs. We consider novel digital approaches—that involve alternative arrangements of digital and socio-political elements in GC settings—to resolving each of these design tensions. Our discussion foreshadows the considerable opportunity for information systems research to contribute to the broader dialog on GCs; inform GC-related policy and practice at global and local levels; and, more broadly, speed the identification and enactment of effective solutions to grand challenges.
{"title":"Digital Approaches to Societal Grand Challenges: Toward a Broader Research Agenda on Managing Global-Local Design Tensions","authors":"Satish Nambisan, Gerard George","doi":"10.1287/isre.2023.0152","DOIUrl":"https://doi.org/10.1287/isre.2023.0152","url":null,"abstract":"Policy/Practice-Focused AbstractDespite considerable and continued resource investments, effective solutions to broad-scope problems of social interest or societal grand challenges (GCs) have proven to be elusive in many domains. In multiactor situations that characterize GCs, divergent goals, needs, priorities, and capabilities of global and local actors create organizing design tensions that need to be considered before solutions can be enacted. Emergent digital technologies can play an important and transformative role in addressing the organizing design tensions that pervade such collective action problems. In this article, we draw on Elinor Ostrom’s principles of public value creation and identify a set of eight organizing design tensions that arise from employing global and local perspectives in addressing GCs. We consider novel digital approaches—that involve alternative arrangements of digital and socio-political elements in GC settings—to resolving each of these design tensions. Our discussion foreshadows the considerable opportunity for information systems research to contribute to the broader dialog on GCs; inform GC-related policy and practice at global and local levels; and, more broadly, speed the identification and enactment of effective solutions to grand challenges.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"1 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139584188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Machine learning is commonly used to estimate the heterogeneous treatment effects (HTEs) in randomized experiments. Using large-scale randomized experiments on Facebook and Criteo platforms, we observe substantial discrepancies between machine learning-based treatment effect estimates and difference-in-means estimates directly from the randomized experiment. This paper provides a two-step framework for practitioners and researchers to diagnose and rectify this discrepancy. We first introduce a diagnostic tool to assess whether bias exists in the model-based estimates from machine learning. If bias exists, we then offer a model-agnostic method to calibrate any HTE estimates to known, unbiased, subgroup difference-in-means estimates, ensuring that the sign and magnitude of the subgroup estimates approximate the model-free benchmarks. This calibration method requires no additional data and can be scaled for large data sets. To highlight potential sources of bias, we theoretically show that this bias can result from regularization, and further use synthetic simulation to show biases result from misspecification and high-dimensional features. We demonstrate the efficacy of our calibration method using extensive synthetic simulations and two real-world randomized experiments. We further demonstrate the practical value of this calibration in three typical policy-making settings: a prescriptive, budget-constrained optimization framework; a setting seeking to maximize multiple performance indicators; and a multitreatment uplift modeling setting.
{"title":"Calibration of Heterogeneous Treatment Effects in Randomized Experiments","authors":"Yan Leng, Drew Dimmery","doi":"10.1287/isre.2021.0343","DOIUrl":"https://doi.org/10.1287/isre.2021.0343","url":null,"abstract":"Machine learning is commonly used to estimate the heterogeneous treatment effects (HTEs) in randomized experiments. Using large-scale randomized experiments on Facebook and Criteo platforms, we observe substantial discrepancies between machine learning-based treatment effect estimates and difference-in-means estimates directly from the randomized experiment. This paper provides a two-step framework for practitioners and researchers to diagnose and rectify this discrepancy. We first introduce a diagnostic tool to assess whether bias exists in the model-based estimates from machine learning. If bias exists, we then offer a model-agnostic method to calibrate any HTE estimates to known, unbiased, subgroup difference-in-means estimates, ensuring that the sign and magnitude of the subgroup estimates approximate the model-free benchmarks. This calibration method requires no additional data and can be scaled for large data sets. To highlight potential sources of bias, we theoretically show that this bias can result from regularization, and further use synthetic simulation to show biases result from misspecification and high-dimensional features. We demonstrate the efficacy of our calibration method using extensive synthetic simulations and two real-world randomized experiments. We further demonstrate the practical value of this calibration in three typical policy-making settings: a prescriptive, budget-constrained optimization framework; a setting seeking to maximize multiple performance indicators; and a multitreatment uplift modeling setting.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"35 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139464120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gorkem Turgut Ozer, Brad N. Greenwood, Anandasivam Gopal
Practice and Policy-Based AbstractExternalities stemming from digital platforms have had a profound impact on the daily lives of people across the globe. In this work, we examine one such externality that contributes to urban quality of life, the noise stemming from home-sharing platforms, which has been subject to aggressive scrutiny by policymakers and the popular press but has received limited rigorous empirical attention. Against a backdrop of significant investment by municipalities to curb extant levels of urban noise, our findings suggest that these platforms are instead correlated with a decrease in noise complaints in New York City (notably when occupancy rates are lower or the residence is located near tourist attractions). These findings suggest that investments in abating the noise stemming from such short-term rentals are less necessary than indicated by anecdotal evidence and are better directed at other forms of urban noise sources, chiefly because such rental units are frequently unoccupied and therefore remain quieter than residential units. However, these findings also underscore the extent to which home-sharing networks may be further straining the already stressed housing market in large metropolitan areas like New York City.
{"title":"Noisebnb: An Empirical Analysis of Home-Sharing Platforms and Residential Noise Complaints","authors":"Gorkem Turgut Ozer, Brad N. Greenwood, Anandasivam Gopal","doi":"10.1287/isre.2022.0070","DOIUrl":"https://doi.org/10.1287/isre.2022.0070","url":null,"abstract":"Practice and Policy-Based AbstractExternalities stemming from digital platforms have had a profound impact on the daily lives of people across the globe. In this work, we examine one such externality that contributes to urban quality of life, the noise stemming from home-sharing platforms, which has been subject to aggressive scrutiny by policymakers and the popular press but has received limited rigorous empirical attention. Against a backdrop of significant investment by municipalities to curb extant levels of urban noise, our findings suggest that these platforms are instead correlated with a decrease in noise complaints in New York City (notably when occupancy rates are lower or the residence is located near tourist attractions). These findings suggest that investments in abating the noise stemming from such short-term rentals are less necessary than indicated by anecdotal evidence and are better directed at other forms of urban noise sources, chiefly because such rental units are frequently unoccupied and therefore remain quieter than residential units. However, these findings also underscore the extent to which home-sharing networks may be further straining the already stressed housing market in large metropolitan areas like New York City.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"14 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139464123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Malte Greulich, Sebastian Lins, Daniel Pienta, Jason Bennett Thatcher, Ali Sunyaev
Encouraging employees to take security precautions is a vital strategy that organizations can use to reduce their vulnerability to information security (ISec) threats. This study investigates how the bright- and dark-side effects of trust in organizational information security impact employees’ intention to take security precautions. Employees who trust organizational security practices are more committed to protecting the organization and are more willing to take security precautions. To foster trust in organizational security practices and security commitment, ISec managers should establish a trusting security climate to ensure that employees can speak freely about the security problems they face in their work and receive support to resolve those problems if needed. This study also alerts managers to the potential adverse consequences of employees’ trust in the organization’s protective structures. We find that employees’ trust in the organization’s protective structures can backfire, making employees complacent regarding security. Further analyses indicate that security mindfulness mediates the influence of security complacency and security commitment on precaution taking. This study contributes by exploring and verifying the bright- and dark-side effects of trust in organizational ISec.
{"title":"Exploring Contrasting Effects of Trust in Organizational Security Practices and Protective Structures on Employees’ Security-Related Precaution Taking","authors":"Malte Greulich, Sebastian Lins, Daniel Pienta, Jason Bennett Thatcher, Ali Sunyaev","doi":"10.1287/isre.2021.0528","DOIUrl":"https://doi.org/10.1287/isre.2021.0528","url":null,"abstract":"Encouraging employees to take security precautions is a vital strategy that organizations can use to reduce their vulnerability to information security (ISec) threats. This study investigates how the bright- and dark-side effects of trust in organizational information security impact employees’ intention to take security precautions. Employees who trust organizational security practices are more committed to protecting the organization and are more willing to take security precautions. To foster trust in organizational security practices and security commitment, ISec managers should establish a trusting security climate to ensure that employees can speak freely about the security problems they face in their work and receive support to resolve those problems if needed. This study also alerts managers to the potential adverse consequences of employees’ trust in the organization’s protective structures. We find that employees’ trust in the organization’s protective structures can backfire, making employees complacent regarding security. Further analyses indicate that security mindfulness mediates the influence of security complacency and security commitment on precaution taking. This study contributes by exploring and verifying the bright- and dark-side effects of trust in organizational ISec.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"234 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139408588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Our study is inspired by the rapid growth of consumer-to-consumer (C2C) media platforms such as TikTok. There are three key findings. First, we show that when content pieces on the platform are longer, viewers set a higher standard of match value in selecting content to view, leading to a lower click-through rate of contributed content on the platform. This finding suggests that a tight limit on content length increases click-through rate. Second, we show that extended content length on the platform first enhances platform performance but then hurts its performance, following an inverted U-shape curve. This pattern holds true for short-term performance measured by viewer traffic and total viewing time, as well as for long-term performance measured by total consumer surplus. This finding suggests the existence of an optimal content length. Third, we find that the optimal content length maximizing viewer traffic is smaller than the one maximizing total viewing time, which is further smaller than the one maximizing consumer surplus. As such, a platform that switches the strategic focus from short-term advertising revenue to long-term growth will benefit from extending the content length limit.
我们的研究受到 TikTok 等消费者对消费者（C2C）媒体平台快速发展的启发。研究有三个主要发现。首先，我们发现当平台上的内容较长时，观众在选择观看内容时会设定较高的匹配价值标准，从而导致平台上投稿内容的点击率降低。这一发现表明，严格限制内容长度会提高点击率。其次，我们的研究表明，延长平台上的内容长度首先会提高平台的性能，但随后又会降低其性能，呈现出倒 U 型曲线。无论是以观众流量和总观看时间衡量的短期绩效，还是以消费者总剩余衡量的长期绩效，这一模式都是正确的。这一发现表明，存在一个最佳内容长度。第三，我们发现观众流量最大化的最佳内容长度小于总观看时间最大化的最佳内容长度，而总观看时间最大化的最佳内容长度又小于消费者剩余最大化的最佳内容长度。因此，将战略重点从短期广告收入转向长期增长的平台将从延长内容长度限制中获益。
{"title":"Content Length Limit: How Does It Matter for a Consumer-to-Consumer Media Platform?","authors":"Zheyin (Jane) Gu, Xuying Zhao","doi":"10.1287/isre.2022.0595","DOIUrl":"https://doi.org/10.1287/isre.2022.0595","url":null,"abstract":"Our study is inspired by the rapid growth of consumer-to-consumer (C2C) media platforms such as TikTok. There are three key findings. First, we show that when content pieces on the platform are longer, viewers set a higher standard of match value in selecting content to view, leading to a lower click-through rate of contributed content on the platform. This finding suggests that a tight limit on content length increases click-through rate. Second, we show that extended content length on the platform first enhances platform performance but then hurts its performance, following an inverted U-shape curve. This pattern holds true for short-term performance measured by viewer traffic and total viewing time, as well as for long-term performance measured by total consumer surplus. This finding suggests the existence of an optimal content length. Third, we find that the optimal content length maximizing viewer traffic is smaller than the one maximizing total viewing time, which is further smaller than the one maximizing consumer surplus. As such, a platform that switches the strategic focus from short-term advertising revenue to long-term growth will benefit from extending the content length limit.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"211 3 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139374698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Information technologies have been developed and used by government agencies and public authorities to address societal issues, but their effectiveness often hinges on public support and participation. This is evidenced in the use of digital contact tracing (DCT) technology to contain the spread of the coronavirus. Despite the efforts of public authorities and technology firms to develop and promote DCT, its adoption in the United States had been low and uneven. This research resolves the puzzle by showing that the public’s mixed views on DCT are caused by their cultural worldviews, which represent their values and attitudes toward collective responsibility in addressing personal needs as well as social hierarchies and established norms in regulating behaviors. These worldviews influence not only their perceptions of the risks and benefits of the technology but also how they interpret information about the technology. Being more aware of the technology may contribute to, rather than correct, the biases resulting from individuals’ prominent cultural worldviews. This research has practical implications for policymakers and technology developers, highlighting the importance of considering cultural worldviews in communication strategies and technology design. It offers a unique perspective on the interplay between worldviews, technology, and public perception, providing valuable insights for navigating the complex landscape of emerging technologies addressing diverse societal issues.
{"title":"Digital Contact Tracing for Pandemic Response: The Roles of Cultural Worldviews and Technology Awareness","authors":"Jingguo Wang, Yuan Li","doi":"10.1287/isre.2021.0253","DOIUrl":"https://doi.org/10.1287/isre.2021.0253","url":null,"abstract":"Information technologies have been developed and used by government agencies and public authorities to address societal issues, but their effectiveness often hinges on public support and participation. This is evidenced in the use of digital contact tracing (DCT) technology to contain the spread of the coronavirus. Despite the efforts of public authorities and technology firms to develop and promote DCT, its adoption in the United States had been low and uneven. This research resolves the puzzle by showing that the public’s mixed views on DCT are caused by their cultural worldviews, which represent their values and attitudes toward collective responsibility in addressing personal needs as well as social hierarchies and established norms in regulating behaviors. These worldviews influence not only their perceptions of the risks and benefits of the technology but also how they interpret information about the technology. Being more aware of the technology may contribute to, rather than correct, the biases resulting from individuals’ prominent cultural worldviews. This research has practical implications for policymakers and technology developers, highlighting the importance of considering cultural worldviews in communication strategies and technology design. It offers a unique perspective on the interplay between worldviews, technology, and public perception, providing valuable insights for navigating the complex landscape of emerging technologies addressing diverse societal issues.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"52 6","pages":""},"PeriodicalIF":4.9,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138948763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Managerial responses to negative reviews could be easily understood as a brand-safeguarding strategy by firms because negative reviews can damage a company’s reputation. However, it is unclear if managers should respond to positive reviews and if so, if such action helps or hurts the firm. We develop a theoretical framework to explicate the mechanisms underlying the effects of managerial responses to positive reviews on user reviewing behaviors in online platforms. We classify positive reviews into four types: one-sided affective reviews, two-sided affective reviews, one-sided instrumental reviews, and two-sided instrumental reviews. We classify managerial responses as tailored and template responses. Using natural language processing and deep learning algorithms, we extract information presented in the texts in the reviews and responses. We theorize and test which kinds of managerial responses to positive reviews are helpful and which of them are harmful. Overall, we find that a tailored response is more appropriate when responding to two-sided instrumental positive reviews and one-sided affective positive reviews, whereas template responses work for one-sided instrumental positive reviews and two-sided affective positive reviews. Not responding would be an effective strategy for mixed positive reviews.
{"title":"Managerial Response to Online Positive Reviews: Helpful or Harmful?","authors":"Chaoqun Deng, T. Ravichandran","doi":"10.1287/isre.2019.0175","DOIUrl":"https://doi.org/10.1287/isre.2019.0175","url":null,"abstract":"Managerial responses to negative reviews could be easily understood as a brand-safeguarding strategy by firms because negative reviews can damage a company’s reputation. However, it is unclear if managers should respond to positive reviews and if so, if such action helps or hurts the firm. We develop a theoretical framework to explicate the mechanisms underlying the effects of managerial responses to positive reviews on user reviewing behaviors in online platforms. We classify positive reviews into four types: one-sided affective reviews, two-sided affective reviews, one-sided instrumental reviews, and two-sided instrumental reviews. We classify managerial responses as tailored and template responses. Using natural language processing and deep learning algorithms, we extract information presented in the texts in the reviews and responses. We theorize and test which kinds of managerial responses to positive reviews are helpful and which of them are harmful. Overall, we find that a tailored response is more appropriate when responding to two-sided instrumental positive reviews and one-sided affective positive reviews, whereas template responses work for one-sided instrumental positive reviews and two-sided affective positive reviews. Not responding would be an effective strategy for mixed positive reviews.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"307 5 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138823971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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