Pub Date : 2021-06-01DOI: 10.25300/misq/2021/15416
A. Barua, Rajiv Mukherjee
Aided by the increasing ease of use, lower adoption cost, and higher network benefits, consumers are demonstrating a strong propensity to concurrently use competing firms’ products or services. Depending on their relative preference for a firm, such “multi-homing” consumers may adopt each firm partially and therefore contribute to the network benefits of no firm fully, as would be the case with single-homing. Consumers’ level of adoption of competing products is a key feature of multi-homing, which, while observed widely in practice, has not previously been studied in the literature. Through a series of analytical models, we demonstrate the important role of this construct in the pricing and capability-related decisions of competing firms. Our results provide several new insights, which suggest that as multi-homing (M) settings become common across industries, technology strategists and managers should exercise caution against simply extrapolating insights from single-homing (S) settings, where consumers adopt only one firm, or from M settings, where the level of adoption is not accounted for. Specifically, in markets where competing products are not well differentiated, contrary to intuition, we find that under price competition, a firm’s profit can be hurt by high levels of adoption by multi-homing consumers; further, in markets where prices are inflexible, a firm with a higher level of adoption can succeed even with a lower level of capability innovation relative to that of an S setting. In contrast to single-homing settings, we show that firms in M settings need to mitigate uncertainty regarding network benefits if the level of adoption is low. Finally, we explore the role of adoption level in two-sided markets and demonstrate that if one side does not have a strong preference for a platform, then, contrary to prevailing wisdom, the latter need not strongly subsidize the other side of the market.
{"title":"Multi-Homing Revisited: Level of Adoption and Competitive Strategies","authors":"A. Barua, Rajiv Mukherjee","doi":"10.25300/misq/2021/15416","DOIUrl":"https://doi.org/10.25300/misq/2021/15416","url":null,"abstract":"Aided by the increasing ease of use, lower adoption cost, and higher network benefits, consumers are demonstrating a strong propensity to concurrently use competing firms’ products or services. Depending on their relative preference for a firm, such “multi-homing” consumers may adopt each firm partially and therefore contribute to the network benefits of no firm fully, as would be the case with single-homing. Consumers’ level of adoption of competing products is a key feature of multi-homing, which, while observed widely in practice, has not previously been studied in the literature. Through a series of analytical models, we demonstrate the important role of this construct in the pricing and capability-related decisions of competing firms. Our results provide several new insights, which suggest that as multi-homing (M) settings become common across industries, technology strategists and managers should exercise caution against simply extrapolating insights from single-homing (S) settings, where consumers adopt only one firm, or from M settings, where the level of adoption is not accounted for. Specifically, in markets where competing products are not well differentiated, contrary to intuition, we find that under price competition, a firm’s profit can be hurt by high levels of adoption by multi-homing consumers; further, in markets where prices are inflexible, a firm with a higher level of adoption can succeed even with a lower level of capability innovation relative to that of an S setting. In contrast to single-homing settings, we show that firms in M settings need to mitigate uncertainty regarding network benefits if the level of adoption is low. Finally, we explore the role of adoption level in two-sided markets and demonstrate that if one side does not have a strong preference for a platform, then, contrary to prevailing wisdom, the latter need not strongly subsidize the other side of the market.","PeriodicalId":18743,"journal":{"name":"MIS Q.","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81466086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.25300/misq/2021/15718
N. Ilk, Guangzhi Shang, Shaokun Fan, J. L. Zhao
Cryptocurrencies such as Bitcoin are breakthrough financial technologies that promise to revolutionize the digital economy. Unfortunately, their long-term adoption in the business world is imperiled by a lack of stability that manifests as dramatic swings in transaction fees and severe participant dissatisfaction. To date, there has been little academic effort to study how system participants react to volatility in fee movements. Our study addresses this research gap by conceptualizing the Bitcoin platform as a data space market and studying how market equilibrium forms between users who demand data space while trying to avoid transaction delays, and miners who supply data space while trying to maximize fee revenues. Our empirical analysis based on past bitcoin transactions reveals the existence of a relatively flat downward-sloping demand curve and a much steeper upward-sloping supply curve. Regarding users, the inelastic nature of demand signals the utility of Bitcoin as a niche platform for transactions that are otherwise difficult to conduct. This result challenges the belief that users may easily abandon Bitcoin technology given rising transaction costs. We also find that the use of bitcoins as a trading asset is associated with higher levels of tolerance to fees. Regarding miners, the comparatively elastic nature of supply indicates that higher fees stimulate mining by a larger magnitude than suppressing demand. This finding implies that, ceteris paribus, the Bitcoin system turns to self-regulate transaction fees in an efficient manner. Our work has implications for the management of congestion in blockchain-based systems and more broadly for the stability of cryptocurrency markets.
{"title":"Stability of Transaction Fees in Bitcoin: A Supply and Demand Perspective","authors":"N. Ilk, Guangzhi Shang, Shaokun Fan, J. L. Zhao","doi":"10.25300/misq/2021/15718","DOIUrl":"https://doi.org/10.25300/misq/2021/15718","url":null,"abstract":"Cryptocurrencies such as Bitcoin are breakthrough financial technologies that promise to revolutionize the digital economy. Unfortunately, their long-term adoption in the business world is imperiled by a lack of stability that manifests as dramatic swings in transaction fees and severe participant dissatisfaction. To date, there has been little academic effort to study how system participants react to volatility in fee movements. Our study addresses this research gap by conceptualizing the Bitcoin platform as a data space market and studying how market equilibrium forms between users who demand data space while trying to avoid transaction delays, and miners who supply data space while trying to maximize fee revenues. Our empirical analysis based on past bitcoin transactions reveals the existence of a relatively flat downward-sloping demand curve and a much steeper upward-sloping supply curve. Regarding users, the inelastic nature of demand signals the utility of Bitcoin as a niche platform for transactions that are otherwise difficult to conduct. This result challenges the belief that users may easily abandon Bitcoin technology given rising transaction costs. We also find that the use of bitcoins as a trading asset is associated with higher levels of tolerance to fees. Regarding miners, the comparatively elastic nature of supply indicates that higher fees stimulate mining by a larger magnitude than suppressing demand. This finding implies that, ceteris paribus, the Bitcoin system turns to self-regulate transaction fees in an efficient manner. Our work has implications for the management of congestion in blockchain-based systems and more broadly for the stability of cryptocurrency markets.","PeriodicalId":18743,"journal":{"name":"MIS Q.","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87568176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.25300/MISQ/2021/12202
Prasanna P. Karhade, John Qi Dong
A firm’s use of boundary-spanning information systems (BSIS) can be beneficial for innovation by providing access to market-facing information. At the same time, BSIS use can give rise to information overload, making it difficult for firms to leverage the most pertinent information for innovation. Although there has been progress in developing the understanding of the role of IS in innovation, it is unclear what capabilities firms need to develop to facilitate innovation in the presence of information overload from BSIS (IO-BSIS). We maintain that firms are increasingly experiencing IO-BSIS and therefore a thorough investigation of firm-level capabilities to facilitate innovation while coping with IO-BSIS is needed. To address this important gap, we broaden the theory of problemistic search for innovation by proposing a digitally enabled collaborative problemistic search (CPS) capability. We propose that a cross-stream CPS effect—the interaction of CPS with customers (CPS-C) and CPS with suppliers (CPS-S)—can enable firms to reinvigorate their internal knowledge for innovation by engaging customers and suppliers in filtering and interpreting market-facing information. Further, we theorize that the presence or absence of IO-BSIS is a contingency factor that affects whether the cross-stream CPS effect is likely to be beneficial or detrimental to innovation. Based on the analysis of data collected from 227 firms, we find that the cross-stream CPS effect is beneficial for innovation when firms face IO-BSIS and detrimental to innovation when firms do not experience IO-BSIS. We thus open the black box of the digitally enabled innovation activity by shedding light on specific collaborative activities that advance innovation while enabling firms to cope with information overload.
{"title":"Innovation Outcomes of Digitally Enabled Collaborative Problemistic Search Capability","authors":"Prasanna P. Karhade, John Qi Dong","doi":"10.25300/MISQ/2021/12202","DOIUrl":"https://doi.org/10.25300/MISQ/2021/12202","url":null,"abstract":"A firm’s use of boundary-spanning information systems (BSIS) can be beneficial for innovation by providing access to market-facing information. At the same time, BSIS use can give rise to information overload, making it difficult for firms to leverage the most pertinent information for innovation. Although there has been progress in developing the understanding of the role of IS in innovation, it is unclear what capabilities firms need to develop to facilitate innovation in the presence of information overload from BSIS (IO-BSIS). We maintain that firms are increasingly experiencing IO-BSIS and therefore a thorough investigation of firm-level capabilities to facilitate innovation while coping with IO-BSIS is needed. To address this important gap, we broaden the theory of problemistic search for innovation by proposing a digitally enabled collaborative problemistic search (CPS) capability. We propose that a cross-stream CPS effect—the interaction of CPS with customers (CPS-C) and CPS with suppliers (CPS-S)—can enable firms to reinvigorate their internal knowledge for innovation by engaging customers and suppliers in filtering and interpreting market-facing information. Further, we theorize that the presence or absence of IO-BSIS is a contingency factor that affects whether the cross-stream CPS effect is likely to be beneficial or detrimental to innovation. Based on the analysis of data collected from 227 firms, we find that the cross-stream CPS effect is beneficial for innovation when firms face IO-BSIS and detrimental to innovation when firms do not experience IO-BSIS. We thus open the black box of the digitally enabled innovation activity by shedding light on specific collaborative activities that advance innovation while enabling firms to cope with information overload.","PeriodicalId":18743,"journal":{"name":"MIS Q.","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88043250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-01DOI: 10.25300/MISQ/2021/15573
Min Chen, Min-Seok Pang, Subodha Kumar
We are witnessing an interesting and unique phenomenon in enterprise information technology (IT) adoption and management in public sector organizations: shared IT services. Instead of implementing separate IT services, governments come together to pool their IT resources into a single IT service. In this study, we develop a game theoretic model to analyze governments’ decisions to share IT services and understand how the introduction of shared services transforms the strategic interactions between governments and vendors. We study three common regimes used in the adoption of shared IT services: (1) a cost-sharing regime where costs are split proportionally, (2) a profit-center regime where one government charges a surplus-maximization price to the another, and (3) a coordination regime where governments coordinate their decisions to maximize aggregate surplus. Our analyses generate several intriguing findings. First, although charging a surplus-maximizing price seems to be a lucrative option, we find that a government does not always benefit by acting as a profit center. Second, the cost-sharing regime does not always incentivize the shared service adoption despite being often viewed as a fairer and more convenient arrangement. Third, we find that there can be significant under-utilization of shared services in the absence of proper coordination, in a sense that the governments may choose not to share their IT services even if doing so would increase their aggregate surplus. Finally, even though coordination promotes the adoption of shared IT services, it can sometimes be inefficient from a social welfare perspective because the increase in government surplus can be outweighed by the decrease in vendor profit. We also present a range of extensions to our model to show that our main take-aways carry over when some model assumptions are relaxed.
{"title":"Do You Have a Room for Us in Your IT? An Economic Analysis of Shared IT Services and Implications for IT Industries","authors":"Min Chen, Min-Seok Pang, Subodha Kumar","doi":"10.25300/MISQ/2021/15573","DOIUrl":"https://doi.org/10.25300/MISQ/2021/15573","url":null,"abstract":"We are witnessing an interesting and unique phenomenon in enterprise information technology (IT) adoption and management in public sector organizations: shared IT services. Instead of implementing separate IT services, governments come together to pool their IT resources into a single IT service. In this study, we develop a game theoretic model to analyze governments’ decisions to share IT services and understand how the introduction of shared services transforms the strategic interactions between governments and vendors. We study three common regimes used in the adoption of shared IT services: (1) a cost-sharing regime where costs are split proportionally, (2) a profit-center regime where one government charges a surplus-maximization price to the another, and (3) a coordination regime where governments coordinate their decisions to maximize aggregate surplus. Our analyses generate several intriguing findings. First, although charging a surplus-maximizing price seems to be a lucrative option, we find that a government does not always benefit by acting as a profit center. Second, the cost-sharing regime does not always incentivize the shared service adoption despite being often viewed as a fairer and more convenient arrangement. Third, we find that there can be significant under-utilization of shared services in the absence of proper coordination, in a sense that the governments may choose not to share their IT services even if doing so would increase their aggregate surplus. Finally, even though coordination promotes the adoption of shared IT services, it can sometimes be inefficient from a social welfare perspective because the increase in government surplus can be outweighed by the decrease in vendor profit. We also present a range of extensions to our model to show that our main take-aways carry over when some model assumptions are relaxed.","PeriodicalId":18743,"journal":{"name":"MIS Q.","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79722974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-01DOI: 10.25300/MISQ/2021/15434.1
A. Burton-Jones, B. Butler, Susan V. Scott, S. Xu
The Information Systems research community has a complex relationship with theory and theorizing. As a community of scholars, our assumptions about theory and theorizing affect every aspect of our intellectual lives. Ideas about what theory is, who theorizes, where theory comes from, when we theorize about, how theory is developed and changes, and why theory is (or isn’t) important shapes the projects we do, the partnerships we have, the resources available to us, and phenomena that we find to be significant, interesting, and novel.
{"title":"Examining Assumptions: Provocations on the Nature, Impact, and Implications of IS Theory","authors":"A. Burton-Jones, B. Butler, Susan V. Scott, S. Xu","doi":"10.25300/MISQ/2021/15434.1","DOIUrl":"https://doi.org/10.25300/MISQ/2021/15434.1","url":null,"abstract":"The Information Systems research community has a complex relationship with theory and theorizing. As a community of scholars, our assumptions about theory and theorizing affect every aspect of our intellectual lives. Ideas about what theory is, who theorizes, where theory comes from, when we theorize about, how theory is developed and changes, and why theory is (or isn’t) important shapes the projects we do, the partnerships we have, the resources available to us, and phenomena that we find to be significant, interesting, and novel.","PeriodicalId":18743,"journal":{"name":"MIS Q.","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78631427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-01DOI: 10.25300/MISQ/2021/14970
Ling Xue, Sunil Mithas, Gautam Ray
{"title":"Commitment to IT Investment Plans: The Interplay of Real Earnings, Management, IT Decentralization, and Corporate Governance","authors":"Ling Xue, Sunil Mithas, Gautam Ray","doi":"10.25300/MISQ/2021/14970","DOIUrl":"https://doi.org/10.25300/MISQ/2021/14970","url":null,"abstract":"","PeriodicalId":18743,"journal":{"name":"MIS Q.","volume":"225 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80966095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-01DOI: 10.25300/MISQ/2021/15882
A. Baird, Likoebe M. Maruping
Information systems (IS) use, the dominant theoretical paradigm for explaining how users apply IS artifacts toward goal attainment, gives primacy to human agency in the user-IS artifact relationship. Models and theorizing in the IS use research stream tend to treat the IS artifact as a passive tool; lacking in the ability to initiate action and accept rights and responsibilities for achieving optimal outcomes under uncertainty. We argue that a new generation of “agentic” IS artifacts requires revisiting the human agency primacy assumption. Agentic IS artifacts are no longer passive tools waiting to be used, are no longer always subordinate to the human agent, and can now assume responsibility for tasks with ambiguous requirements and for seeking optimal outcomes under uncertainty. To move our theorizing forward, we introduce delegation, based on agent interaction theories, as a foundational and powerful lens through which to understand and explain the human-agentic IS artifact relationship. While delegation has always been central to human-IS artifact interactions, it has yet to be explicitly recognized in IS use theorizing. We explicitly theorize IS delegation by developing an IS delegation theoretical framework. This framework provides a scaffolding which can guide future IS delegation theorizing and focuses on the human-agentic IS artifact dyad as the elemental unit of analysis. The framework specifically reveals the importance of agent attributes relevant to delegation (endowments, preferences, and roles) as well as foundational mechanisms of delegation (appraisal, distribution, and coordination). Guidelines are proposed to demonstrate how this theoretical framework can be applied toward generation of testable models. We conclude by outlining a roadmap for mobilizing future research.
{"title":"The Next Generation of Research on IS Use: A Theoretical Framework of Delegation to and from Agentic IS Artifacts","authors":"A. Baird, Likoebe M. Maruping","doi":"10.25300/MISQ/2021/15882","DOIUrl":"https://doi.org/10.25300/MISQ/2021/15882","url":null,"abstract":"Information systems (IS) use, the dominant theoretical paradigm for explaining how users apply IS artifacts toward goal attainment, gives primacy to human agency in the user-IS artifact relationship. Models and theorizing in the IS use research stream tend to treat the IS artifact as a passive tool; lacking in the ability to initiate action and accept rights and responsibilities for achieving optimal outcomes under uncertainty. We argue that a new generation of “agentic” IS artifacts requires revisiting the human agency primacy assumption. Agentic IS artifacts are no longer passive tools waiting to be used, are no longer always subordinate to the human agent, and can now assume responsibility for tasks with ambiguous requirements and for seeking optimal outcomes under uncertainty. To move our theorizing forward, we introduce delegation, based on agent interaction theories, as a foundational and powerful lens through which to understand and explain the human-agentic IS artifact relationship. While delegation has always been central to human-IS artifact interactions, it has yet to be explicitly recognized in IS use theorizing. We explicitly theorize IS delegation by developing an IS delegation theoretical framework. This framework provides a scaffolding which can guide future IS delegation theorizing and focuses on the human-agentic IS artifact dyad as the elemental unit of analysis. The framework specifically reveals the importance of agent attributes relevant to delegation (endowments, preferences, and roles) as well as foundational mechanisms of delegation (appraisal, distribution, and coordination). Guidelines are proposed to demonstrate how this theoretical framework can be applied toward generation of testable models. We conclude by outlining a roadmap for mobilizing future research.","PeriodicalId":18743,"journal":{"name":"MIS Q.","volume":"198 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75757471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-01DOI: 10.25300/MISQ/2021/14312
Ziqiong Zhang, Zili Zhang, P. Chen
Little research has focused on online shopping habits, particularly concerning time, missing the opportunity to potentially improve important outcomes by the simple innovative use of time. Based on a unique dataset that includes reviews as well as pertinent purchases at the individual level from a large online retailer, this study investigates whether consumers exhibit time habits for online shopping and whether following such time habits affects their satisfaction and revisit behavior. We employ activity-based metrics to assess individual shopping time habits, with the results showing that consumers form shopping time habits, and they obtain higher consumer satisfaction and exhibit greater re-visit behavior when the timing of shopping follows their shopping time habits. While prior works have documented that consumers exhibit time habits for physical shopping, driven mostly by time and location constraints, this study is the first, to our knowledge, to examine online shopping time habit and, most importantly, its effects on consumer satisfaction and revisit behavior. With the availability of detailed individual transaction data in online shopping and the advance of technology in providing personalized services which enable companies to act upon knowledge of individual behaviors, this research provides important practical implications for system and website design, marketing strategy, and customer relationship management.
{"title":"Early Bird Versus Late Owl: An Empirical Investigation of Individual Shopping Time Habits and its Effects","authors":"Ziqiong Zhang, Zili Zhang, P. Chen","doi":"10.25300/MISQ/2021/14312","DOIUrl":"https://doi.org/10.25300/MISQ/2021/14312","url":null,"abstract":"Little research has focused on online shopping habits, particularly concerning time, missing the opportunity to potentially improve important outcomes by the simple innovative use of time. Based on a unique dataset that includes reviews as well as pertinent purchases at the individual level from a large online retailer, this study investigates whether consumers exhibit time habits for online shopping and whether following such time habits affects their satisfaction and revisit behavior. We employ activity-based metrics to assess individual shopping time habits, with the results showing that consumers form shopping time habits, and they obtain higher consumer satisfaction and exhibit greater re-visit behavior when the timing of shopping follows their shopping time habits. While prior works have documented that consumers exhibit time habits for physical shopping, driven mostly by time and location constraints, this study is the first, to our knowledge, to examine online shopping time habit and, most importantly, its effects on consumer satisfaction and revisit behavior. With the availability of detailed individual transaction data in online shopping and the advance of technology in providing personalized services which enable companies to act upon knowledge of individual behaviors, this research provides important practical implications for system and website design, marketing strategy, and customer relationship management.","PeriodicalId":18743,"journal":{"name":"MIS Q.","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78079822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-01DOI: 10.25300/MISQ/2021/14372
Xiao Fang, Yuanyuan Gao, P. H. Hu
Containing skyrocketing health care costs is imperative. Toward that end, prescriptive analytics that analyzes health care data to recommend optimal decisions is both relevant and crucial. We develop a novel prescriptive analytics method to improve the cost effectiveness in clinical decision making (CDM), a critical health care dimension that can greatly benefit from analytics. Effective prescriptive analytics for CDM has to address its probabilistic, cost-sensitive, and investment-related characteristics simultaneously. Unlike existing methods that often overlook the investment-related characteristic, the proposed method accounts for all of these characteristics. Specifically, our method considers two sets of costs associated with clinical decisions — before and after an investment — in combination with the probabilities of cost changes due to the investment. In contrast, prevalent methods only emphasize one set of costs, before an investment. Furthermore, the proposed method involves both clinical and investment decisions, whereas existing methods ignore investment decisions. Empirical evaluations with two real-world clinical data sets indicate that the proposed method consistently and significantly outperforms several salient methods from previous research, thereby demonstrating the value of addressing the investment-related characteristic in efforts to improve CDM.
{"title":"A Prescriptive Analytics Method for Cost Reduction in Clinical Decision Making","authors":"Xiao Fang, Yuanyuan Gao, P. H. Hu","doi":"10.25300/MISQ/2021/14372","DOIUrl":"https://doi.org/10.25300/MISQ/2021/14372","url":null,"abstract":"Containing skyrocketing health care costs is imperative. Toward that end, prescriptive analytics that analyzes health care data to recommend optimal decisions is both relevant and crucial. We develop a novel prescriptive analytics method to improve the cost effectiveness in clinical decision making (CDM), a critical health care dimension that can greatly benefit from analytics. Effective prescriptive analytics for CDM has to address its probabilistic, cost-sensitive, and investment-related characteristics simultaneously. Unlike existing methods that often overlook the investment-related characteristic, the proposed method accounts for all of these characteristics. Specifically, our method considers two sets of costs associated with clinical decisions — before and after an investment — in combination with the probabilities of cost changes due to the investment. In contrast, prevalent methods only emphasize one set of costs, before an investment. Furthermore, the proposed method involves both clinical and investment decisions, whereas existing methods ignore investment decisions. Empirical evaluations with two real-world clinical data sets indicate that the proposed method consistently and significantly outperforms several salient methods from previous research, thereby demonstrating the value of addressing the investment-related characteristic in efforts to improve CDM.","PeriodicalId":18743,"journal":{"name":"MIS Q.","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81688295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gerald C. Kane, A. Young, A. Majchrzak, S. Ransbotham
Widespread use of machine learning (ML) systems could result in an oppressive future of ubiquitous monitoring and behavior control that, for dialogic purposes, we call “informania.” This dystopian future results from ML systems’ inherent design based on training data rather than built with code. To avoid this oppressive future, we develop the concept of an emancipatory assistant (EA), an ML system that engages with human users to help them understand and enact emancipatory outcomes amidst the oppressive environment of informania. Using emancipatory pedagogy as a kernel theory, we develop two sets of design principles: one for the near future and the other for the far-term future. Designers optimize EA on emancipatory outcomes for an individual user, which protects the user from informania’s oppression by engaging in an adversarial relationship with its oppressive ML platforms when necessary. The principles should encourage IS researchers to enlarge the range of possibilities for responding to the influx of ML systems. Given the fusion of social and technical expertise that IS research embodies, we encourage other IS researchers to theorize boldly about the long-term consequences of emerging technologies on society and potentially change their trajectory.
{"title":"Avoiding an Oppressive Future of Machine Learning: A Design Theory for Emancipatory Assistants","authors":"Gerald C. Kane, A. Young, A. Majchrzak, S. Ransbotham","doi":"10.25300/MISQ/2021/1578","DOIUrl":"https://doi.org/10.25300/MISQ/2021/1578","url":null,"abstract":"Widespread use of machine learning (ML) systems could result in an oppressive future of ubiquitous monitoring and behavior control that, for dialogic purposes, we call “informania.” This dystopian future results from ML systems’ inherent design based on training data rather than built with code. To avoid this oppressive future, we develop the concept of an emancipatory assistant (EA), an ML system that engages with human users to help them understand and enact emancipatory outcomes amidst the oppressive environment of informania. Using emancipatory pedagogy as a kernel theory, we develop two sets of design principles: one for the near future and the other for the far-term future. Designers optimize EA on emancipatory outcomes for an individual user, which protects the user from informania’s oppression by engaging in an adversarial relationship with its oppressive ML platforms when necessary. The principles should encourage IS researchers to enlarge the range of possibilities for responding to the influx of ML systems. Given the fusion of social and technical expertise that IS research embodies, we encourage other IS researchers to theorize boldly about the long-term consequences of emerging technologies on society and potentially change their trajectory.","PeriodicalId":18743,"journal":{"name":"MIS Q.","volume":"91 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85930223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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