We study how firms respond to online customer reviews in a competitive market where they jostle with one another for sales based on online ratings. The focus of this paper is on how firms can optimally manage their ratings through management response and how review ratings affect the sales and profits of competing firms. We develop a controlled diffusion process to model the coevolution of sales and ratings as a function of the response strategy chosen to maximize profit over time. Our model considers a variety of factors, such as profit margin and customer rating sensitivity, that influence a firm’s effort to manage ratings and subsequently its sales and profits. More response effort needs to be exerted to manage ratings when either the profit margin of a tour is very high or customers are very sensitive to ratings. We estimate our model using data on Ctrip’s tours that include each tour’s sales, reviews, prices, and tour features. We find that consumers anchor their beliefs in the mean market rating and that their purchase decisions depend on the tour’s rating relative to this anchor. Thus, relative, rather than absolute, ratings matter. Our study informs firms on how competition and other primitives impact their efforts to manage ratings and hence profit. Our methodology allowed us to conduct “what-if” analyses, for example, to study what would happen to the review ratings, sales, and profits of a tour if a firm adopted a different response strategy. We were also able to provide turnaround strategies for struggling tours, i.e., factors that a loss-making tour should change if it wishes to make a positive profit. Ultimately, we conducted a competitive analysis that allowed us to modify certain parameters that affect the intensity of competition and hence the sales and the profits of competing tours. Finally, we demonstrate the flexibility of the model by extending it to incorporate multiple state variables that might affect the response strategy.
{"title":"Responding to Online Reviews in Competitive Markets: A Controlled Diffusion Approach","authors":"Mingwen Yang, Zhiqiang (Eric) Zheng, Vijay Mookerjee, Hongyu Chen","doi":"10.25300/misq/2022/16163","DOIUrl":"https://doi.org/10.25300/misq/2022/16163","url":null,"abstract":"We study how firms respond to online customer reviews in a competitive market where they jostle with one another for sales based on online ratings. The focus of this paper is on how firms can optimally manage their ratings through management response and how review ratings affect the sales and profits of competing firms. We develop a controlled diffusion process to model the coevolution of sales and ratings as a function of the response strategy chosen to maximize profit over time. Our model considers a variety of factors, such as profit margin and customer rating sensitivity, that influence a firm’s effort to manage ratings and subsequently its sales and profits. More response effort needs to be exerted to manage ratings when either the profit margin of a tour is very high or customers are very sensitive to ratings. We estimate our model using data on Ctrip’s tours that include each tour’s sales, reviews, prices, and tour features. We find that consumers anchor their beliefs in the mean market rating and that their purchase decisions depend on the tour’s rating relative to this anchor. Thus, relative, rather than absolute, ratings matter. Our study informs firms on how competition and other primitives impact their efforts to manage ratings and hence profit. Our methodology allowed us to conduct “what-if” analyses, for example, to study what would happen to the review ratings, sales, and profits of a tour if a firm adopted a different response strategy. We were also able to provide turnaround strategies for struggling tours, i.e., factors that a loss-making tour should change if it wishes to make a positive profit. Ultimately, we conducted a competitive analysis that allowed us to modify certain parameters that affect the intensity of competition and hence the sales and the profits of competing tours. Finally, we demonstrate the flexibility of the model by extending it to incorporate multiple state variables that might affect the response strategy.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"12 5","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Online health communities (OHCs) play an important role in enabling patients to exchange information and obtain social support from each other. However, do OHC interactions always benefit patients? In this research, we investigate different mechanisms by which OHC content may affect patients’ emotions. Specifically, we notice users can read not only emotional support intended to help them but also emotional support targeting other persons or posts that are not intended to generate any emotional support (auxiliary content). Drawing from emotional contagion theories, we argue that even though emotional support may benefit targeted support seekers, it could have a negative impact on the emotions of other support seekers. Our empirical study on an OHC for depression patients supports these arguments. Our findings are new to the literature and have critical practical implications since they suggest that we should carefully manage OHC-based interventions for depression patients to avoid unintended consequences. We design a novel deep learning model to differentiate emotional support from auxiliary content. Such differentiation is critical for identifying the negative effect of emotional support on unintended recipients. We also discuss options to alter the intervention volume, length, and frequency to tackle the challenge of the negative effect.
{"title":"Unintended Emotional Effects of Online Health Communities: A Text Mining-Supported Empirical Study","authors":"Jiaqi Zhou, Qingpeng Zhang, Sijia Zhou, Xin Li, Xiaoquan (Michael) Zhang","doi":"10.25300/misq/2022/17018","DOIUrl":"https://doi.org/10.25300/misq/2022/17018","url":null,"abstract":"Online health communities (OHCs) play an important role in enabling patients to exchange information and obtain social support from each other. However, do OHC interactions always benefit patients? In this research, we investigate different mechanisms by which OHC content may affect patients’ emotions. Specifically, we notice users can read not only emotional support intended to help them but also emotional support targeting other persons or posts that are not intended to generate any emotional support (auxiliary content). Drawing from emotional contagion theories, we argue that even though emotional support may benefit targeted support seekers, it could have a negative impact on the emotions of other support seekers. Our empirical study on an OHC for depression patients supports these arguments. Our findings are new to the literature and have critical practical implications since they suggest that we should carefully manage OHC-based interventions for depression patients to avoid unintended consequences. We design a novel deep learning model to differentiate emotional support from auxiliary content. Such differentiation is critical for identifying the negative effect of emotional support on unintended recipients. We also discuss options to alter the intervention volume, length, and frequency to tackle the challenge of the negative effect.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135742774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.25300/misq/2022/16162
Fei Ren, Yong Tan, Fei Wan
We examine the impact of firm social media engagement on sales performance, answering “whether,” “what,” and “how” questions. The study uses a quasi-experimental design in a social e-commerce setting, for which propensity score matching and difference-in-differences methods quantify a mean 20.67% sales increase after firm social media adoption. We also find that firms that sell low-involvement products benefit more from social media adoption, compared to those that sell high-involvement products. Further, in terms of how to manage social media engagement, we find that informative content, in general, is effective for sales of high-involvement products, whereas promotional content, a new type of content discovered in this study, is more beneficial for sales of low-involvement products. Meanwhile, more social media followers generate better firm sales performance. We used instrumental variables and the control function method to address endogeneity issues and conducted robustness checks to support our conclusions. This study sheds light on the value of firm social media, particularly regarding industry differences and firm know-how.
{"title":"Know Your Firm: Managing Social Media Engagement to Improve Firm Sales Performance","authors":"Fei Ren, Yong Tan, Fei Wan","doi":"10.25300/misq/2022/16162","DOIUrl":"https://doi.org/10.25300/misq/2022/16162","url":null,"abstract":"We examine the impact of firm social media engagement on sales performance, answering “whether,” “what,” and “how” questions. The study uses a quasi-experimental design in a social e-commerce setting, for which propensity score matching and difference-in-differences methods quantify a mean 20.67% sales increase after firm social media adoption. We also find that firms that sell low-involvement products benefit more from social media adoption, compared to those that sell high-involvement products. Further, in terms of how to manage social media engagement, we find that informative content, in general, is effective for sales of high-involvement products, whereas promotional content, a new type of content discovered in this study, is more beneficial for sales of low-involvement products. Meanwhile, more social media followers generate better firm sales performance. We used instrumental variables and the control function method to address endogeneity issues and conducted robustness checks to support our conclusions. This study sheds light on the value of firm social media, particularly regarding industry differences and firm know-how.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"12 9","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.25300/misq/2022/17234
Jun Li, Xianwei Liu, Qiang Ye, Feng Zhao, Xiaofei Zhao
Existing studies have found that online search is a revealed measure for investor attention and a useful predictor of stock returns. We study the heterogeneity in retail investor attention by comparing search conducted on weekdays vs. weekends and investigate the price pressure channel and information processing channel for stock return predictability. According to the information processing channel, weekends afford retail investors more time for the intensive cognitive analysis necessary to make better predictions. Alternatively, weekend search might better capture the price pressure from retail investors’ trading activities. We provide empirical results that support the information processing channel. We first show that weekend search, rather than weekday search, predicts large-cap stock returns in both the cross-section and time series. Additionally, our findings on retail trading activity contradict the price pressure channel in that weekday search, rather than weekend search, leads to a subsequent retail order imbalance. Overall, our study contributes to the literature on the predictive power of online search on stock returns, which has mainly focused on the price pressure channel, which yields significant results for small-cap stocks only.
{"title":"It Depends on When You Search","authors":"Jun Li, Xianwei Liu, Qiang Ye, Feng Zhao, Xiaofei Zhao","doi":"10.25300/misq/2022/17234","DOIUrl":"https://doi.org/10.25300/misq/2022/17234","url":null,"abstract":"Existing studies have found that online search is a revealed measure for investor attention and a useful predictor of stock returns. We study the heterogeneity in retail investor attention by comparing search conducted on weekdays vs. weekends and investigate the price pressure channel and information processing channel for stock return predictability. According to the information processing channel, weekends afford retail investors more time for the intensive cognitive analysis necessary to make better predictions. Alternatively, weekend search might better capture the price pressure from retail investors’ trading activities. We provide empirical results that support the information processing channel. We first show that weekend search, rather than weekday search, predicts large-cap stock returns in both the cross-section and time series. Additionally, our findings on retail trading activity contradict the price pressure channel in that weekday search, rather than weekend search, leads to a subsequent retail order imbalance. Overall, our study contributes to the literature on the predictive power of online search on stock returns, which has mainly focused on the price pressure channel, which yields significant results for small-cap stocks only.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"12 4","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.25300/misq/2022/17321
Mingfeng Lin, Richard W. Sias, Zaiyan Wei
The growth of crowdfunding markets that include both expert and nonexpert investors will soon accelerate due to recent changes in Securities Exchange Commission (SEC) regulations. Prior work has suggested that nonexperts (1) may benefit from experts’ participation via mimicking their trades, but (2) will also face a cost, as experts crowding nonexperts out of the best opportunities will ensure that nonexperts will suffer lower returns than experts. Traditional economic theory holds that the crowding effect means that the relative importance of nonexperts in the market will decline over time until they become unimportant. Exploiting a unique period in one crowdfunding market (Prosper.com) that allowed us to directly estimate the net cost of competing with better-informed experts, we found that the net negative effects of expert participation on nonexperts are small. We used simulations to both better understand (1) the market characteristics and crowdfunding platform choices that influence experts’ and nonexperts’ returns, their return gap, and the extent to which nonexperts are better or worse off relative to a market without expert participation, and (2) the factors that may contribute to the small expert/nonexpert Prosper return gap.
{"title":"Experts vs. Non-Experts in Online Crowdfunding Markets","authors":"Mingfeng Lin, Richard W. Sias, Zaiyan Wei","doi":"10.25300/misq/2022/17321","DOIUrl":"https://doi.org/10.25300/misq/2022/17321","url":null,"abstract":"The growth of crowdfunding markets that include both expert and nonexpert investors will soon accelerate due to recent changes in Securities Exchange Commission (SEC) regulations. Prior work has suggested that nonexperts (1) may benefit from experts’ participation via mimicking their trades, but (2) will also face a cost, as experts crowding nonexperts out of the best opportunities will ensure that nonexperts will suffer lower returns than experts. Traditional economic theory holds that the crowding effect means that the relative importance of nonexperts in the market will decline over time until they become unimportant. Exploiting a unique period in one crowdfunding market (Prosper.com) that allowed us to directly estimate the net cost of competing with better-informed experts, we found that the net negative effects of expert participation on nonexperts are small. We used simulations to both better understand (1) the market characteristics and crowdfunding platform choices that influence experts’ and nonexperts’ returns, their return gap, and the extent to which nonexperts are better or worse off relative to a market without expert participation, and (2) the factors that may contribute to the small expert/nonexpert Prosper return gap.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"12 6","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.25300/misq/2022/15713
Wilson Weixun Li, Alvin Chung Man Leung, Wei Thoo Yue
Data breaches can severely damage a firm’s reputation and its customers’ confidence. Firms must therefore continuously invest in security measures to prevent such breaches. However, the effectiveness of security investment has been questioned by both practitioners and academics. We illustrate the bidirectional dynamic relationship between information technology (IT) investment and data breaches moderated by threat and countermeasure security awareness using an eight-year panel of 311 U.S.-listed firms to provide empirical evidence that threat awareness broadens firms’ scope for addressing data-breach issues by investing more in IT than in security. Countermeasure awareness equips firms with sufficient knowledge and experience to ensure effective implementation of IT, which provides more comprehensive protection than security investment alone. Our results suggest that firms should evolve beyond the reactive mindset of solely upgrading security and begin nurturing both threat awareness and countermeasure awareness to address the underlying IT system issues that are the cause of data breaches.
{"title":"Where is IT in Information Security? The Interrelationship among IT Investment, Security Awareness, and Data Breaches","authors":"Wilson Weixun Li, Alvin Chung Man Leung, Wei Thoo Yue","doi":"10.25300/misq/2022/15713","DOIUrl":"https://doi.org/10.25300/misq/2022/15713","url":null,"abstract":"Data breaches can severely damage a firm’s reputation and its customers’ confidence. Firms must therefore continuously invest in security measures to prevent such breaches. However, the effectiveness of security investment has been questioned by both practitioners and academics. We illustrate the bidirectional dynamic relationship between information technology (IT) investment and data breaches moderated by threat and countermeasure security awareness using an eight-year panel of 311 U.S.-listed firms to provide empirical evidence that threat awareness broadens firms’ scope for addressing data-breach issues by investing more in IT than in security. Countermeasure awareness equips firms with sufficient knowledge and experience to ensure effective implementation of IT, which provides more comprehensive protection than security investment alone. Our results suggest that firms should evolve beyond the reactive mindset of solely upgrading security and begin nurturing both threat awareness and countermeasure awareness to address the underlying IT system issues that are the cause of data breaches.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"12 3","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.25300/misq/2022/17256
Onkar S. Malgonde, Terence J.V. Saldanha, Sunil Mithas
Contributions by individual open source software (OSS) community members are the lifeblood of the OSS projects that power today’s digital economy and are important for the very survival of such communities. Individual contributions by OSS community members to others’ projects and their own determine whether OSS communities are resilient in the face of major shocks. Arguably, if crises such as the COVID-19 pandemic prompt users to reduce their contributions to others’ projects relative to the contributions to their own projects, such behavior can have implications for the overall resilience of the OSS community. Therefore, whether and how individuals change their contributions in the face of a crisis is an important question. We examine whether members in an OSS community increased or decreased their contributions to others’ projects relative to their own in the face of the COVID-19 pandemic, a sudden and unexpected global health-related shock that has affected almost everyone. We also compare and contrast this behavior when the OSS community faced increasing unemployment, an economic cyclic shock that is arguably and relatively more personal. Drawing on the concept of prosocial behavior and conservation of resources (COR) theory, we hypothesize that the pandemic increased OSS community members’ contributions to others’ projects relative to their own; on the other hand, the threat of rising unemployment decreased OSS community members’ contributions to others’ projects relative to their own. Our empirical analyses of a longitudinal dataset of over 18,000 OSS community members on GitHub, with more than 1.4 million member-day observations, support our hypotheses. This study contributes by uncovering the differential effects of exogenous health-related and economic shocks on the resilience of the OSS community. We conclude with a discussion of our findings’ implications for OSS community resilience.
{"title":"Resilience in the Open Source Software Community: How Pandemic and Unemployment Shocks Influence Contributions to Others’ and One’s Own Projects","authors":"Onkar S. Malgonde, Terence J.V. Saldanha, Sunil Mithas","doi":"10.25300/misq/2022/17256","DOIUrl":"https://doi.org/10.25300/misq/2022/17256","url":null,"abstract":"Contributions by individual open source software (OSS) community members are the lifeblood of the OSS projects that power today’s digital economy and are important for the very survival of such communities. Individual contributions by OSS community members to others’ projects and their own determine whether OSS communities are resilient in the face of major shocks. Arguably, if crises such as the COVID-19 pandemic prompt users to reduce their contributions to others’ projects relative to the contributions to their own projects, such behavior can have implications for the overall resilience of the OSS community. Therefore, whether and how individuals change their contributions in the face of a crisis is an important question. We examine whether members in an OSS community increased or decreased their contributions to others’ projects relative to their own in the face of the COVID-19 pandemic, a sudden and unexpected global health-related shock that has affected almost everyone. We also compare and contrast this behavior when the OSS community faced increasing unemployment, an economic cyclic shock that is arguably and relatively more personal. Drawing on the concept of prosocial behavior and conservation of resources (COR) theory, we hypothesize that the pandemic increased OSS community members’ contributions to others’ projects relative to their own; on the other hand, the threat of rising unemployment decreased OSS community members’ contributions to others’ projects relative to their own. Our empirical analyses of a longitudinal dataset of over 18,000 OSS community members on GitHub, with more than 1.4 million member-day observations, support our hypotheses. This study contributes by uncovering the differential effects of exogenous health-related and economic shocks on the resilience of the OSS community. We conclude with a discussion of our findings’ implications for OSS community resilience.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"12 2","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.25300/misq/2022/17062
Yi Yang, Yu Qin, Yangyang Fan, Zhongju Zhang
Unstructured multimedia data (text and audio) provides unprecedented opportunities to derive actionable decision-making in the financial industry, in areas such as portfolio and risk management. However, due to formidable methodological challenges, the promise of business value from unstructured multimedia data has not materialized. In this study, we use a design science approach to develop DeepVoice, a novel nonverbal predictive analysis system for financial risk prediction, in the setting of quarterly earnings conference calls. DeepVoice forecasts financial risk by leveraging not only what managers say (verbal linguistic cues) but also how managers say it (vocal cues) during the earnings conference calls. The design of DeepVoice addresses several challenges associated with the analysis of nonverbal communication. We also propose a two-stage deep learning model to effectively integrate managers’ sequential vocal and verbal cues. Using a unique dataset of 6,047 earnings call samples (audio recordings and textual transcripts) of S&P 500 firms across four years, we show that DeepVoice yields remarkably lower risk forecast errors than that achieved by previous efforts. The improvement can also translate into nontrivial economic gains in options trading. The theoretical and practical implications of analyzing vocal cues are discussed.
{"title":"Unlocking the Power of Voice for Financial Risk Prediction: A Theory-Driven Deep Learning Design Approach","authors":"Yi Yang, Yu Qin, Yangyang Fan, Zhongju Zhang","doi":"10.25300/misq/2022/17062","DOIUrl":"https://doi.org/10.25300/misq/2022/17062","url":null,"abstract":"Unstructured multimedia data (text and audio) provides unprecedented opportunities to derive actionable decision-making in the financial industry, in areas such as portfolio and risk management. However, due to formidable methodological challenges, the promise of business value from unstructured multimedia data has not materialized. In this study, we use a design science approach to develop DeepVoice, a novel nonverbal predictive analysis system for financial risk prediction, in the setting of quarterly earnings conference calls. DeepVoice forecasts financial risk by leveraging not only what managers say (verbal linguistic cues) but also how managers say it (vocal cues) during the earnings conference calls. The design of DeepVoice addresses several challenges associated with the analysis of nonverbal communication. We also propose a two-stage deep learning model to effectively integrate managers’ sequential vocal and verbal cues. Using a unique dataset of 6,047 earnings call samples (audio recordings and textual transcripts) of S&P 500 firms across four years, we show that DeepVoice yields remarkably lower risk forecast errors than that achieved by previous efforts. The improvement can also translate into nontrivial economic gains in options trading. The theoretical and practical implications of analyzing vocal cues are discussed.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"12 7","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.25300/misq/2022/16711
Tapani Rinta-Kahila, Esko Penttinen, Kalle Lyytinen
Organizations replace their legacy systems for technical, economic, and operational reasons. Replacement is a risky proposition, as high levels of technical and social inertia make these systems hard to withdraw. Failure to fully replace systems results in complex system architectures involving manifold hidden dependencies that carry technical debt. To understand how a process for replacing a complex legacy system unfolds and accumulates technical debt, we conducted an explanatory case study at a local manufacturing site that had struggled to replace its mission-critical legacy systems as part of the larger global company’s commercial-off-the-shelf (COTS) system implementation. We approach the replacement as a sociotechnical change and leverage the punctuated sociotechnical information system change model in combination with the design-moves framework to analyze how the site balanced creating digital options, countering social inertia, and managing (architectural) technical debt. The findings generalize to a two-level (local/global) system-dynamics model delineating how replacing a deeply entrenched mission-critical system generates positive and negative feedback loops within and between social and technical changes at local and global levels. The loops, unless addressed, accrue technical debt that hinders legacy system discontinuance and gradually locks the organization into a debt-constrained state. The model helps managers anticipate challenges that accompany replacing highly entrenched systems and formulate effective strategies to address them.
{"title":"Getting Trapped in Technical Debt: Sociotechnical Analysis of a Legacy System’s Replacement","authors":"Tapani Rinta-Kahila, Esko Penttinen, Kalle Lyytinen","doi":"10.25300/misq/2022/16711","DOIUrl":"https://doi.org/10.25300/misq/2022/16711","url":null,"abstract":"Organizations replace their legacy systems for technical, economic, and operational reasons. Replacement is a risky proposition, as high levels of technical and social inertia make these systems hard to withdraw. Failure to fully replace systems results in complex system architectures involving manifold hidden dependencies that carry technical debt. To understand how a process for replacing a complex legacy system unfolds and accumulates technical debt, we conducted an explanatory case study at a local manufacturing site that had struggled to replace its mission-critical legacy systems as part of the larger global company’s commercial-off-the-shelf (COTS) system implementation. We approach the replacement as a sociotechnical change and leverage the punctuated sociotechnical information system change model in combination with the design-moves framework to analyze how the site balanced creating digital options, countering social inertia, and managing (architectural) technical debt. The findings generalize to a two-level (local/global) system-dynamics model delineating how replacing a deeply entrenched mission-critical system generates positive and negative feedback loops within and between social and technical changes at local and global levels. The loops, unless addressed, accrue technical debt that hinders legacy system discontinuance and gradually locks the organization into a debt-constrained state. The model helps managers anticipate challenges that accompany replacing highly entrenched systems and formulate effective strategies to address them.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"12 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rise of technology-enabled ride-hailing services has affected individuals’ transportation-related decisions. The impact of these ride-hailing services likely varies across traveler segments that differ in their usage of various modes of transportation. In this paper, we develop and leverage a framework that allows us to examine the impact of ride-hailing services on the transportation mode choice for three traveler segments: drivers (who primarily use a personal automobile to travel), riders (who primarily use public transit to travel), and walkers (who primarily use non-motorized modes of transport). We first develop a framework outlining how the behavior of different traveler segments would be impacted by the introduction of ride-hailing services and show how this affects traffic congestion and public transportation ridership. To test the framework, we compiled a rich dataset, combining data on public transportation ridership, traffic congestion, and individual transportation mode choice. Employing a difference-in-differences methodology, we show that the Uber entry in a market enabled those who were walkers and riders prior to the entry of Uber to travel more conveniently, leading to an increase in traffic congestion, and induced those who were drivers to substitute their use of private automobiles with a combination of Uber and public transit. We introduced urban compactness to assess the heterogeneous impact of ride-hailing services for cities that differ in their distribution of traveler segments. We found that Uber entry increases traffic congestion and reduces public transit demand more in cities with higher levels of urban compactness, i.e., where the proportion of riders and walkers is higher than that of drivers. This work provides a holistic framework to understand the mechanism underlying the impact of ride-hailing services on public transit and traffic congestion. Urban planners and policy makers can leverage our framework, methodology, and empirical results to guide city planning decisions that have implications for sustainability.
{"title":"Impact of Ride-Hailing Services on Transportation Mode Choices: Evidence from Traffic and Transit Ridership","authors":"Kyunghee Lee, Qianran Jin, Animesh Animesh, Jui Ramaprasad","doi":"10.25300/misq/2022/15707","DOIUrl":"https://doi.org/10.25300/misq/2022/15707","url":null,"abstract":"The rise of technology-enabled ride-hailing services has affected individuals’ transportation-related decisions. The impact of these ride-hailing services likely varies across traveler segments that differ in their usage of various modes of transportation. In this paper, we develop and leverage a framework that allows us to examine the impact of ride-hailing services on the transportation mode choice for three traveler segments: drivers (who primarily use a personal automobile to travel), riders (who primarily use public transit to travel), and walkers (who primarily use non-motorized modes of transport). We first develop a framework outlining how the behavior of different traveler segments would be impacted by the introduction of ride-hailing services and show how this affects traffic congestion and public transportation ridership. To test the framework, we compiled a rich dataset, combining data on public transportation ridership, traffic congestion, and individual transportation mode choice. Employing a difference-in-differences methodology, we show that the Uber entry in a market enabled those who were walkers and riders prior to the entry of Uber to travel more conveniently, leading to an increase in traffic congestion, and induced those who were drivers to substitute their use of private automobiles with a combination of Uber and public transit. We introduced urban compactness to assess the heterogeneous impact of ride-hailing services for cities that differ in their distribution of traveler segments. We found that Uber entry increases traffic congestion and reduces public transit demand more in cities with higher levels of urban compactness, i.e., where the proportion of riders and walkers is higher than that of drivers. This work provides a holistic framework to understand the mechanism underlying the impact of ride-hailing services on public transit and traffic congestion. Urban planners and policy makers can leverage our framework, methodology, and empirical results to guide city planning decisions that have implications for sustainability.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":" ","pages":""},"PeriodicalIF":7.3,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46295582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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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