Pub Date : 2023-09-01DOI: 10.25300/misq/2022/17141
Buomsoo (Raymond) Kim, Karthik Srinivasan, Sung Hye Kong, Jung Hee Kim, Chan Soo Shin, Sudha Ram
Recent developments in big data technologies are revolutionizing the field of healthcare predictive analytics (HPA), enabling researchers to explore challenging problems using complex prediction models. Nevertheless, healthcare practitioners are reluctant to adopt those models as they are less transparent and accountable due to their black-box structure. We believe that instance-level, or local, explanations enhance patient safety and foster trust by enabling patient-level interpretations and medical knowledge discovery. Therefore, we propose the RObust Local EXplanations (ROLEX) method to develop robust, instance-level explanations for HPA models in this study. ROLEX adapts state-of-the-art methods and ameliorates their shortcomings in explaining individual-level predictions made by black-box machine learning models. Our analysis with a large real-world dataset related to a prevalent medical condition called fragility fracture and two publicly available healthcare datasets reveals that ROLEX outperforms widely accepted benchmark methods in terms of local faithfulness of explanations. In addition, ROLEX is more robust since it does not rely on extensive hyperparameter tuning or heuristic algorithms. Explanations generated by ROLEX, along with the prototype user interface presented in this study, have the potential to promote personalized care and precision medicine by providing patient-level interpretations and novel insights. We discuss the theoretical implications of our study in healthcare, big data, and design science.
{"title":"ROLEX: A Novel Method for Interpretable Machine Learning Using Robust Local Explanations","authors":"Buomsoo (Raymond) Kim, Karthik Srinivasan, Sung Hye Kong, Jung Hee Kim, Chan Soo Shin, Sudha Ram","doi":"10.25300/misq/2022/17141","DOIUrl":"https://doi.org/10.25300/misq/2022/17141","url":null,"abstract":"<style>#html-body [data-pb-style=RGODD5T]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}</style>Recent developments in big data technologies are revolutionizing the field of healthcare predictive analytics (HPA), enabling researchers to explore challenging problems using complex prediction models. Nevertheless, healthcare practitioners are reluctant to adopt those models as they are less transparent and accountable due to their black-box structure. We believe that instance-level, or local, explanations enhance patient safety and foster trust by enabling patient-level interpretations and medical knowledge discovery. Therefore, we propose the RObust Local EXplanations (ROLEX) method to develop robust, instance-level explanations for HPA models in this study. ROLEX adapts state-of-the-art methods and ameliorates their shortcomings in explaining individual-level predictions made by black-box machine learning models. Our analysis with a large real-world dataset related to a prevalent medical condition called fragility fracture and two publicly available healthcare datasets reveals that ROLEX outperforms widely accepted benchmark methods in terms of local faithfulness of explanations. In addition, ROLEX is more robust since it does not rely on extensive hyperparameter tuning or heuristic algorithms. Explanations generated by ROLEX, along with the prototype user interface presented in this study, have the potential to promote personalized care and precision medicine by providing patient-level interpretations and novel insights. We discuss the theoretical implications of our study in healthcare, big data, and design science.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"19 5","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164533","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 : 2023-06-01DOI: 10.25300/misq/2022/17432
Sam Ransbotham, Marios Kokkodis, Panagiotis Adamopoulos
Digital markets have proliferated in recent years, overcoming many market inefficiencies by facilitating direct interactions between consumers and creators. Thanks to this disintermediation, consumers now have access to a vast number of alternatives, while creators can efficiently reach huge markets. However, the success of digital markets has created a concomitant challenge for creators: differentiation. In crowded markets, agencies (e.g., publishing companies in books, freelance agencies in online labor markets, independent labels in music) can differentiate creators by signaling product quality. But how do agencies’ reputations affect product success for creators? Can some agencies do more harm than good? To investigate these research questions, we theorize how variation in creator and agency reputation leads to asymmetric and heterogeneous effects, namely that (1) more reputable agencies have a stronger positive effect on less reputable creators than they have on more reputable creators, and (2) less reputable agencies hurt more reputable creators more than they hurt less reputable ones. Analyses of more than one million observations from two digital markets provide empirical support for these theory-driven arguments. The findings have design implications for markets and contribute to our understanding of how agencies, depending on creator reputation, can either benefit or hurt product success.
{"title":"Reputation Spillover from Agencies on Online Platforms: Evidence from the Entertainment Industry","authors":"Sam Ransbotham, Marios Kokkodis, Panagiotis Adamopoulos","doi":"10.25300/misq/2022/17432","DOIUrl":"https://doi.org/10.25300/misq/2022/17432","url":null,"abstract":"Digital markets have proliferated in recent years, overcoming many market inefficiencies by facilitating direct interactions between consumers and creators. Thanks to this disintermediation, consumers now have access to a vast number of alternatives, while creators can efficiently reach huge markets. However, the success of digital markets has created a concomitant challenge for creators: differentiation. In crowded markets, agencies (e.g., publishing companies in books, freelance agencies in online labor markets, independent labels in music) can differentiate creators by signaling product quality. But how do agencies’ reputations affect product success for creators? Can some agencies do more harm than good? To investigate these research questions, we theorize how variation in creator and agency reputation leads to asymmetric and heterogeneous effects, namely that (1) more reputable agencies have a stronger positive effect on less reputable creators than they have on more reputable creators, and (2) less reputable agencies hurt more reputable creators more than they hurt less reputable ones. Analyses of more than one million observations from two digital markets provide empirical support for these theory-driven arguments. The findings have design implications for markets and contribute to our understanding of how agencies, depending on creator reputation, can either benefit or hurt product success.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"7 4","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164810","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 : 2023-06-01DOI: 10.25300/misq/2022/17875
Jing Peng and Chen Liang
E-commerce platforms often use collaborative filtering (CF) algorithms to recommend products to consumers. What recommendations consumers receive and how they respond to the recommendations largely depend on the design of CF algorithms. However, the extant empirical research on recommender systems has primarily focused on how the presence of recommendations affects product demand, without considering the underlying algorithm design. Leveraging a field experiment on a major e-commerce platform, we examine the differential impact of two widely used CF designs: view-also-view (VAV) and purchase-also-purchase (PAP). We found several striking differences between the impact of these two designs on individual products. First, VAV is about seven times more effective in generating additional product views than PAP but only about twice as effective in generating sales due to a lower conversion rate. Second, VAV is more effective in increasing views for more expensive products, whereas PAP is more effective in increasing the sales of cheaper products. Third, VAV is less effective in increasing the views but more effective in increasing the sales of products with higher purchase incidence rates (PIRs). Finally, when aggregated over all products with the same levels of price or PIRs, VAV dominates PAP in generating views and the difference is more striking for products with higher prices or lower PIRs. Interestingly, PAP is more effective than VAV in increasing the sales of products with low prices or moderate PIRs, though VAV generates more sales than PAP overall. Our findings suggest that platforms may benefit from employing different CF designs for different types of products.
{"title":"On the Differences Between View-Based and Purchase-Based Recommender Systems","authors":"Jing Peng and Chen Liang","doi":"10.25300/misq/2022/17875","DOIUrl":"https://doi.org/10.25300/misq/2022/17875","url":null,"abstract":"E-commerce platforms often use collaborative filtering (CF) algorithms to recommend products to consumers. What recommendations consumers receive and how they respond to the recommendations largely depend on the design of CF algorithms. However, the extant empirical research on recommender systems has primarily focused on how the presence of recommendations affects product demand, without considering the underlying algorithm design. Leveraging a field experiment on a major e-commerce platform, we examine the differential impact of two widely used CF designs: view-also-view (VAV) and purchase-also-purchase (PAP). We found several striking differences between the impact of these two designs on individual products. First, VAV is about seven times more effective in generating additional product views than PAP but only about twice as effective in generating sales due to a lower conversion rate. Second, VAV is more effective in increasing views for more expensive products, whereas PAP is more effective in increasing the sales of cheaper products. Third, VAV is less effective in increasing the views but more effective in increasing the sales of products with higher purchase incidence rates (PIRs). Finally, when aggregated over all products with the same levels of price or PIRs, VAV dominates PAP in generating views and the difference is more striking for products with higher prices or lower PIRs. Interestingly, PAP is more effective than VAV in increasing the sales of products with low prices or moderate PIRs, though VAV generates more sales than PAP overall. Our findings suggest that platforms may benefit from employing different CF designs for different types of products.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"6 6","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164814","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 : 2023-06-01DOI: 10.25300/misq/2022/16733
Laia Pujol Priego and Jonathan Wareham
Although considered a relatively recent phenomenon of the past decade, open source hardware (OSH) is already influencing commercial hardware development. However, a common belief is that the greater economic cost and complexity of hybrid digital objects (i.e., digital objects with both hardware and software) precludes their development with open source methods traditionally used for software. We study a sophisticated OSH named White Rabbit initiated at CERN and developed through a vibrant and heterogenous open source community. Our findings show that the assumption that hardware and software require fundamentally distinctive development and production modes should be replaced with a more nuanced differentiation characterized by three main attributes describing an object’s composition: embodiment, modularity, and granularity. Taken together, these three attributes determine how a hybrid object is developed throughout its evolution in an open source community. Our research offers several contributions. First, we provide a more nuanced view of the consequences of the material embodiment of hardware. Once considered a simple deterrent to open source development, we describe how economic cost is subordinate to more influential aspects of an object’s physical layers: as the open source community modifies the object to accommodate the operating requirements of diverse physical instantiations, such modifications can be incorporated in the logical design covered by the open source license. Additionally, we show how embodiment, modularity, and granularity progress through the object’s evolution and how this maturation subsequently affects development modes. We trace the implications of our findings for hybrids and digital object conceptualizations in IS research, open source development and, more broadly, normative implications for OSH in scientific and commercial computing.
{"title":"From Bits to Atoms: Open Source Hardware at CERN","authors":"Laia Pujol Priego and Jonathan Wareham","doi":"10.25300/misq/2022/16733","DOIUrl":"https://doi.org/10.25300/misq/2022/16733","url":null,"abstract":"Although considered a relatively recent phenomenon of the past decade, open source hardware (OSH) is already influencing commercial hardware development. However, a common belief is that the greater economic cost and complexity of hybrid digital objects (i.e., digital objects with both hardware and software) precludes their development with open source methods traditionally used for software. We study a sophisticated OSH named White Rabbit initiated at CERN and developed through a vibrant and heterogenous open source community. Our findings show that the assumption that hardware and software require fundamentally distinctive development and production modes should be replaced with a more nuanced differentiation characterized by three main attributes describing an object’s composition: embodiment, modularity, and granularity. Taken together, these three attributes determine how a hybrid object is developed throughout its evolution in an open source community. Our research offers several contributions. First, we provide a more nuanced view of the consequences of the material embodiment of hardware. Once considered a simple deterrent to open source development, we describe how economic cost is subordinate to more influential aspects of an object’s physical layers: as the open source community modifies the object to accommodate the operating requirements of diverse physical instantiations, such modifications can be incorporated in the logical design covered by the open source license. Additionally, we show how embodiment, modularity, and granularity progress through the object’s evolution and how this maturation subsequently affects development modes. We trace the implications of our findings for hybrids and digital object conceptualizations in IS research, open source development and, more broadly, normative implications for OSH in scientific and commercial computing.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"7 6","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164808","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 : 2023-06-01DOI: 10.25300/misq/2022/15554
Julia Kotlarsky, Suzanne Rivard, Ilan Oshri
One noticeable trend in the maturing information technology (IT) outsourcing industry is the growing interest from client firms seeking to benefit from supplier-led innovations. Yet IT outsourcing suppliers still find it challenging to shift their reputation from the competent provision of a low-end service to a high-value innovative line of services, thus becoming known as business partners. We address this issue by examining the reputation formation efforts of an IT supplier experiencing a reputation deficit in terms of quality (its ability as a business partner) and intent (its intention to adopt trustworthy behavior). We develop a model based on a case study of a large IT supplier engaged in reputation formation with its outsourcing clients. We portray reputation formation as a process wherein an IT supplier alternately emits signals of quality and intent from a repertoire of signals. Our process model distinguishes between signaling at the market level, which relies on rhetorical mediums to broadcast a message promoting the supplier’s ability as a business partner, and signaling at the client level, which relies on substantive mediums such as demonstrations of the supplier’s ability to solve the client’s business problems and behavioral mediums that allow the client to assess the supplier’s intent to adopt trustworthy behavior.
{"title":"Building a Reputation as a Business Partner in Information Technology Outsourcing (Open Access)","authors":"Julia Kotlarsky, Suzanne Rivard, Ilan Oshri","doi":"10.25300/misq/2022/15554","DOIUrl":"https://doi.org/10.25300/misq/2022/15554","url":null,"abstract":"One noticeable trend in the maturing information technology (IT) outsourcing industry is the growing interest from client firms seeking to benefit from supplier-led innovations. Yet IT outsourcing suppliers still find it challenging to shift their reputation from the competent provision of a low-end service to a high-value innovative line of services, thus becoming known as business partners. We address this issue by examining the reputation formation efforts of an IT supplier experiencing a reputation deficit in terms of quality (its ability as a business partner) and intent (its intention to adopt trustworthy behavior). We develop a model based on a case study of a large IT supplier engaged in reputation formation with its outsourcing clients. We portray reputation formation as a process wherein an IT supplier alternately emits signals of quality and intent from a repertoire of signals. Our process model distinguishes between signaling at the market level, which relies on rhetorical mediums to broadcast a message promoting the supplier’s ability as a business partner, and signaling at the client level, which relies on substantive mediums such as demonstrations of the supplier’s ability to solve the client’s business problems and behavioral mediums that allow the client to assess the supplier’s intent to adopt trustworthy behavior.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"6 5","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164815","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 : 2023-06-01DOI: 10.25300/misq/2022/17333
Yoonseock Son, Wonseok Oh, Il Im
The present study investigates the effects of smart speaker usage on consumers’ digital content search, purchase, and consumption behaviors. Using a unique panel data set comprising information on household patterns of digital content (e.g., video on demand [VOD]) transactions and consumption and smart speaker usage, we found that the adoption of smart speakers is positively associated with the increased purchase of digital content but negatively related to the average rate of content completion. More specifically, we found that VOD content-related expenditures increased by 21.5% following smart speaker adoption but the average consumption of VOD content purchased decreased by 3.0%. We also examined millions of data points on TV remote-control use and conducted a survey via MTurk to support the validity of the findings. Smart speaker usage can reduce search costs, which subsequently increases search incidence and conversion rates, behavioral changes that can lead to a rise in purchases. We further show that the use of smart speakers for purposes other than information seeking is positively associated with purchases. We develop insights on how to elicit economic value from voice recognition technologies and provide implications for the design and implementation of effective voice commerce strategies.
{"title":"The Voice of Commerce: How Smart Speakers Reshape Digital Content Consumption and Preference","authors":"Yoonseock Son, Wonseok Oh, Il Im","doi":"10.25300/misq/2022/17333","DOIUrl":"https://doi.org/10.25300/misq/2022/17333","url":null,"abstract":"The present study investigates the effects of smart speaker usage on consumers’ digital content search, purchase, and consumption behaviors. Using a unique panel data set comprising information on household patterns of digital content (e.g., video on demand [VOD]) transactions and consumption and smart speaker usage, we found that the adoption of smart speakers is positively associated with the increased purchase of digital content but negatively related to the average rate of content completion. More specifically, we found that VOD content-related expenditures increased by 21.5% following smart speaker adoption but the average consumption of VOD content purchased decreased by 3.0%. We also examined millions of data points on TV remote-control use and conducted a survey via MTurk to support the validity of the findings. Smart speaker usage can reduce search costs, which subsequently increases search incidence and conversion rates, behavioral changes that can lead to a rise in purchases. We further show that the use of smart speakers for purposes other than information seeking is positively associated with purchases. We develop insights on how to elicit economic value from voice recognition technologies and provide implications for the design and implementation of effective voice commerce strategies.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"7 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164813","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 : 2023-06-01DOI: 10.25300/misq/2022/15469
Xin Zheng, Jisu Cao, Yili Hong, Sha Yang, Xingyao Ren
Despite a large body of literature on online reviews, none have considered the nuanced impacts of how multidimensional reviews affect product sales differently for mainstream vs. niche products. This study seeks to fill this knowledge gap by conducting complementary studies in two product categories (i.e., automobiles and laptops) with different methods (a field study and three lab experiments). Our paper reveals three key insights into the emerging literature and phenomenon on multidimensional review systems: (1) the interdimensional rating variance is more negatively related to product sales for mainstream products than for niche products in the same category, (2) the intradimensional rating valence on the dominant dimension of a product is more positively related to product sales for niche products than for mainstream products, and (3) the intradimensional rating variance on the dominant dimension of a product is more negatively related to product sales for niche products than for mainstream products. Our research provides important managerial implications for both product providers and review platforms.
{"title":"Differential Effects of Multidimensional Review Evaluations on Product Sales for Mainstream vs. Niche Products","authors":"Xin Zheng, Jisu Cao, Yili Hong, Sha Yang, Xingyao Ren","doi":"10.25300/misq/2022/15469","DOIUrl":"https://doi.org/10.25300/misq/2022/15469","url":null,"abstract":"Despite a large body of literature on online reviews, none have considered the nuanced impacts of how multidimensional reviews affect product sales differently for mainstream vs. niche products. This study seeks to fill this knowledge gap by conducting complementary studies in two product categories (i.e., automobiles and laptops) with different methods (a field study and three lab experiments). Our paper reveals three key insights into the emerging literature and phenomenon on multidimensional review systems: (1) the interdimensional rating variance is more negatively related to product sales for mainstream products than for niche products in the same category, (2) the intradimensional rating valence on the dominant dimension of a product is more positively related to product sales for niche products than for mainstream products, and (3) the intradimensional rating variance on the dominant dimension of a product is more negatively related to product sales for niche products than for mainstream products. Our research provides important managerial implications for both product providers and review platforms.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135144887","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 : 2023-06-01DOI: 10.25300/misq/2022/16625
Ryan T. Wright, Steven L. Johnson, Brent Kitchens
Despite widespread awareness of risks, significant investments in cybersecurity protection, and substantial economic incentives to avoid security breaches, organizations remain vulnerable to phishing attacks. Phishing research has informed effective practical interventions to address phishing susceptibility that emphasize the importance of broadly applicable IT security knowledge. Yet employees still frequently fall victim to phishing attempts. To help understand why, we conceptualize phishing susceptibility as the failure to differentiate between deceptive and legitimate information processing requests that occur within the context of an employee’s typical job responsibilities. We apply this contextual lens to identify characteristics of knowledge workers’ organizational task and social context that may enhance or diminish performance in detecting deception in phishing email attempts. To test our hypotheses, we conducted a study in which employees of the finance division of a large university encountered simulated email-based phishing attempts as part of their normal work routine. We found evidence supporting our hypotheses that an individual’s susceptibility to phishing attacks is influenced by their position in the knowledge flows of the organization and by the impact of workgroup responsibilities on their cognitive processing. We contend that phishing susceptibility is not merely a matter of IT security knowledge but is also influenced by contextualized, multilevel influences on information processing. As phishing attacks are increasingly targeted to specific organizational settings, it is even more important to incorporate this contextualized information processing view of phishing susceptibility.
{"title":"Phishing Susceptibility in Context: A Multilevel Information Processing Perspective on Deception Detection","authors":"Ryan T. Wright, Steven L. Johnson, Brent Kitchens","doi":"10.25300/misq/2022/16625","DOIUrl":"https://doi.org/10.25300/misq/2022/16625","url":null,"abstract":"Despite widespread awareness of risks, significant investments in cybersecurity protection, and substantial economic incentives to avoid security breaches, organizations remain vulnerable to phishing attacks. Phishing research has informed effective practical interventions to address phishing susceptibility that emphasize the importance of broadly applicable IT security knowledge. Yet employees still frequently fall victim to phishing attempts. To help understand why, we conceptualize phishing susceptibility as the failure to differentiate between deceptive and legitimate information processing requests that occur within the context of an employee’s typical job responsibilities. We apply this contextual lens to identify characteristics of knowledge workers’ organizational task and social context that may enhance or diminish performance in detecting deception in phishing email attempts. To test our hypotheses, we conducted a study in which employees of the finance division of a large university encountered simulated email-based phishing attempts as part of their normal work routine. We found evidence supporting our hypotheses that an individual’s susceptibility to phishing attacks is influenced by their position in the knowledge flows of the organization and by the impact of workgroup responsibilities on their cognitive processing. We contend that phishing susceptibility is not merely a matter of IT security knowledge but is also influenced by contextualized, multilevel influences on information processing. As phishing attacks are increasingly targeted to specific organizational settings, it is even more important to incorporate this contextualized information processing view of phishing susceptibility.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"7 2","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164812","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 : 2023-06-01DOI: 10.25300/misq/2022/16392
Taha Havakhor, Alireza Golmohammadi, Rajiv Sabherwal, Dinesh Gauri
Online equity markets have significantly changed the dynamics of connecting angels and individual equity investors to new ventures that seek early-stage capital. However, for those early-stage investors, information pointing to the success of business-to-business (B2B) new ventures (B2BNVs) is scattered and disconnected. This paper focuses on social media narratives (SMNs) as a source of insight for such investors and proposes that predicting a B2BNV’s likelihood of success requires a comparative view, i.e., a comparison of its SMNs with those of its competitors and customers. We expect that higher (lower) lingual similarity between the SMNs of an early-stage B2BNV and those of its prospective customers (competitors) predict its success. Using a longitudinal panel of 574 B2BNVs resulting in more than 2,700 venture-round observations, we find that a comparative view of a venture’s SMNs can give early-stage investors reliable predictions about the B2BNV’s ability to manage its market presence and its success in later stages. Our models show that a comparative view of SMNs increases the accuracy of predicting a B2BNV’s later-stage fundraising success by an average of 15%. Furthermore, predictive models can reliably point to a successful market presence in later stages, including the landing of customers, the winning of awards and competitions, the receiving of endorsements, the generating of revenue, and the successful patenting of products. Our study contributes to existing literature that focuses on the business impacts of social media by demonstrating the usefulness of comparative linguistics in social media analytics, i.e., comparing the firm’s social media communications to those of its competitors and business customers in the prediction of the entrepreneurial firm’s success.
{"title":"Do Early Words from New Ventures Predict Fundraising? A Comparative View of Social Media Narratives","authors":"Taha Havakhor, Alireza Golmohammadi, Rajiv Sabherwal, Dinesh Gauri","doi":"10.25300/misq/2022/16392","DOIUrl":"https://doi.org/10.25300/misq/2022/16392","url":null,"abstract":"Online equity markets have significantly changed the dynamics of connecting angels and individual equity investors to new ventures that seek early-stage capital. However, for those early-stage investors, information pointing to the success of business-to-business (B2B) new ventures (B2BNVs) is scattered and disconnected. This paper focuses on social media narratives (SMNs) as a source of insight for such investors and proposes that predicting a B2BNV’s likelihood of success requires a comparative view, i.e., a comparison of its SMNs with those of its competitors and customers. We expect that higher (lower) lingual similarity between the SMNs of an early-stage B2BNV and those of its prospective customers (competitors) predict its success. Using a longitudinal panel of 574 B2BNVs resulting in more than 2,700 venture-round observations, we find that a comparative view of a venture’s SMNs can give early-stage investors reliable predictions about the B2BNV’s ability to manage its market presence and its success in later stages. Our models show that a comparative view of SMNs increases the accuracy of predicting a B2BNV’s later-stage fundraising success by an average of 15%. Furthermore, predictive models can reliably point to a successful market presence in later stages, including the landing of customers, the winning of awards and competitions, the receiving of endorsements, the generating of revenue, and the successful patenting of products. Our study contributes to existing literature that focuses on the business impacts of social media by demonstrating the usefulness of comparative linguistics in social media analytics, i.e., comparing the firm’s social media communications to those of its competitors and business customers in the prediction of the entrepreneurial firm’s success.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135144738","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 : 2023-06-01DOI: 10.25300/misq/2022/17347
Ulrich Laitenberger, Steffen Viete, Olga Slivko, Michael Kummer, Kathrin Borchert, Matthias Hirth
We analyze the relationship between unemployment and the supply of online labor for microtasking. Using detailed U.S. data from a large microtasking platform between 2011 and 2015, we study the participation and the number of hours supplied by workers in the U.S. We found that more individuals registered on the platform and completed microtasks as the unemployment level in the commuting zone increased. This effect was strongest in regions with a high share of low-skilled workers. Our analyses of the intensive margin, wage elasticity, and temporal work patterns suggest that the increased participation was likely motivated by an effort to substitute income. Our findings suggest that microtasking platforms are an interesting online labor market for less educated workers. However, we also observed very low retention rates, indicative of a solely transient participation effect.
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