Pub Date : 2023-01-02DOI: 10.1080/07421222.2023.2172766
Vladimir Zwass
{"title":"Editorial Introduction","authors":"Vladimir Zwass","doi":"10.1080/07421222.2023.2172766","DOIUrl":"https://doi.org/10.1080/07421222.2023.2172766","url":null,"abstract":"","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135755004","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 : 2023-01-02DOI: 10.1080/07421222.2023.2172777
Sheila O’Riordan, Bill Emerson, J. Feller, G. Kiely
ABSTRACT This study theorizes the role of social signals in overcoming the motivation, coordination, and integration challenges in a hybrid peer production community, WikiTribune. WikiTribune was a collaborative journalism project that combined elements of firm-based production with that of commons-based peer production. Empirical data (article metrics, project documentation, and user communications) was used to examine the first 18-months of building and developing the collaborative journalism platform and community. The study’s primary contribution is a social signaling model that extends the theory of commons-based peer production and presents three constructs that inform the socially productive behavior in these communities. These constructs (1) system signals, (2) normative signals, and (3) behavioral signals are theorized to shape user engagement through the different levels of project participation. The alignment/misalignment of these signals with project strategy produce positive or negative outcomes. The social signaling model seeks to explain how challenges are overcome and advantages leveraged in commons-based peer production, in both pure and hybrid forms.
{"title":"The Road to Open News: A Theory of Social Signaling in an Open News Production Community","authors":"Sheila O’Riordan, Bill Emerson, J. Feller, G. Kiely","doi":"10.1080/07421222.2023.2172777","DOIUrl":"https://doi.org/10.1080/07421222.2023.2172777","url":null,"abstract":"ABSTRACT This study theorizes the role of social signals in overcoming the motivation, coordination, and integration challenges in a hybrid peer production community, WikiTribune. WikiTribune was a collaborative journalism project that combined elements of firm-based production with that of commons-based peer production. Empirical data (article metrics, project documentation, and user communications) was used to examine the first 18-months of building and developing the collaborative journalism platform and community. The study’s primary contribution is a social signaling model that extends the theory of commons-based peer production and presents three constructs that inform the socially productive behavior in these communities. These constructs (1) system signals, (2) normative signals, and (3) behavioral signals are theorized to shape user engagement through the different levels of project participation. The alignment/misalignment of these signals with project strategy produce positive or negative outcomes. The social signaling model seeks to explain how challenges are overcome and advantages leveraged in commons-based peer production, in both pure and hybrid forms.","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"40 1","pages":"130 - 162"},"PeriodicalIF":7.7,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44277214","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 : 2023-01-02DOI: 10.1080/07421222.2023.2172775
Mateusz Dolata, Dzmitry Katsiuba, Natalie Wellnhammer, G. Schwabe
ABSTRACT Digital agents are considered a general-purpose technology. They spread quickly in private and organizational contexts, including education. Yet, research lacks a conceptual framing to describe interaction with such agents in a holistic manner. While focusing on the interaction with a pedagogical agent, that is, a digital agent capable of natural-language interaction with a learner, we propose a model of learning activity based on activity theory. We use this model and a review of prior research on digital agents in education to analyze how various characteristics of the activity, including features of a pedagogical agent or learner, influence learning outcomes. The analysis leads to identification of information systems research directions and guidance for developers of pedagogical agents and digital agents in general. We conclude by extending the activity theory-based model beyond the context of education and show how it helps designers and researchers ask the right questions when creating a digital agent.
{"title":"Learning with Digital Agents: An Analysis based on the Activity Theory","authors":"Mateusz Dolata, Dzmitry Katsiuba, Natalie Wellnhammer, G. Schwabe","doi":"10.1080/07421222.2023.2172775","DOIUrl":"https://doi.org/10.1080/07421222.2023.2172775","url":null,"abstract":"ABSTRACT Digital agents are considered a general-purpose technology. They spread quickly in private and organizational contexts, including education. Yet, research lacks a conceptual framing to describe interaction with such agents in a holistic manner. While focusing on the interaction with a pedagogical agent, that is, a digital agent capable of natural-language interaction with a learner, we propose a model of learning activity based on activity theory. We use this model and a review of prior research on digital agents in education to analyze how various characteristics of the activity, including features of a pedagogical agent or learner, influence learning outcomes. The analysis leads to identification of information systems research directions and guidance for developers of pedagogical agents and digital agents in general. We conclude by extending the activity theory-based model beyond the context of education and show how it helps designers and researchers ask the right questions when creating a digital agent.","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"40 1","pages":"56 - 95"},"PeriodicalIF":7.7,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49651719","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}
ABSTRACT With the development of the sharing economy, online ride-sharing has become a primary form of commuting. Using secondary transaction data, this study investigates the associations between the heterogeneous features and mutual trust in sharing economy-driven online ride-sharing transactions. Based on an examination of 12,404 ride-sharing orders in Beijing, we propose a set of trust distribution maps using order location data to reveal heterogeneous spatial patterns of the relationship between online ride-sharing transactions and mutual trust. The results show that the historical order completion rate and order distance are positively associated with mutual trust in ride-sharing transactions, whereas order time and departure density negatively and significantly influence mutual trust. Furthermore, we use machine learning algorithms to predict trust. The implications for theory and practice and future research directions are discussed.
{"title":"Trust in Online Ride-Sharing Transactions: Impacts of Heterogeneous Order Features","authors":"Xusen Cheng, Shixuan Fu, Jianshan Sun, Meiyun Zuo, Xiangsong Meng","doi":"10.1080/07421222.2023.2172779","DOIUrl":"https://doi.org/10.1080/07421222.2023.2172779","url":null,"abstract":"ABSTRACT With the development of the sharing economy, online ride-sharing has become a primary form of commuting. Using secondary transaction data, this study investigates the associations between the heterogeneous features and mutual trust in sharing economy-driven online ride-sharing transactions. Based on an examination of 12,404 ride-sharing orders in Beijing, we propose a set of trust distribution maps using order location data to reveal heterogeneous spatial patterns of the relationship between online ride-sharing transactions and mutual trust. The results show that the historical order completion rate and order distance are positively associated with mutual trust in ride-sharing transactions, whereas order time and departure density negatively and significantly influence mutual trust. Furthermore, we use machine learning algorithms to predict trust. The implications for theory and practice and future research directions are discussed.","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"40 1","pages":"183 - 207"},"PeriodicalIF":7.7,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44507632","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 : 2023-01-02DOI: 10.1080/07421222.2023.2172774
Evren Eryilmaz, Brian Thoms, Z. Ahmed, Howard Lee
ABSTRACT This paper explores the formation of a learning community facilitated by custom collaborative learning software. Drawing on research in group cognition, knowledge building discourse, and learning analytics, we conducted a mixed-methods field study involving an asynchronous online discussion consisting of 259 messages posted by 50 participants. The cluster analysis results provide evidence that the recommender system within the software can support the formation of a learning community with a small peripheral cluster. Regarding knowledge building discourse, we identified the distinct roles of central, intermediate (i.e., middle of three clusters), and peripheral clusters within a learning community. Furthermore, we found that message lexical complexity does not correlate to the stages of knowledge building. Overall, this study contributes to the group cognition theory to deepen our understanding about collaboration to construct new knowledge in online discussions. Moreover, we add a much-needed text mining perspective to the qualitative interaction analysis model.
{"title":"Formation and Action of a Learning Community with Collaborative Learning Software","authors":"Evren Eryilmaz, Brian Thoms, Z. Ahmed, Howard Lee","doi":"10.1080/07421222.2023.2172774","DOIUrl":"https://doi.org/10.1080/07421222.2023.2172774","url":null,"abstract":"ABSTRACT This paper explores the formation of a learning community facilitated by custom collaborative learning software. Drawing on research in group cognition, knowledge building discourse, and learning analytics, we conducted a mixed-methods field study involving an asynchronous online discussion consisting of 259 messages posted by 50 participants. The cluster analysis results provide evidence that the recommender system within the software can support the formation of a learning community with a small peripheral cluster. Regarding knowledge building discourse, we identified the distinct roles of central, intermediate (i.e., middle of three clusters), and peripheral clusters within a learning community. Furthermore, we found that message lexical complexity does not correlate to the stages of knowledge building. Overall, this study contributes to the group cognition theory to deepen our understanding about collaboration to construct new knowledge in online discussions. Moreover, we add a much-needed text mining perspective to the qualitative interaction analysis model.","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"40 1","pages":"38 - 55"},"PeriodicalIF":7.7,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47104463","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 : 2022-10-02DOI: 10.1080/07421222.2022.2127440
Onkar Malgonde, He Zhang, B. Padmanabhan, M. Limayem
ABSTRACT Digital platforms have replaced traditional markets in most industries and orchestrate socioeconomic aspects of our lives. We address the problem of negative direct side network effects that arise with an increased number of agents on one side of the platform. Negative effects, if unaddressed, lead to undesired long-term consequences for the platform by developing a positive vicious cycle. Addressing negative effects require dynamic solution mechanisms that adapt to the changing landscape of platforms. The recommender systems literature has proposed multi-sided recommender systems (MSR) as a dynamic solution to many problems on platforms. However, current state-of-the-art MSRs do not consider uncertainty in predicting agents’ choices, resulting in limited efficacy. We present a robust multi-sided recommender system that considers estimation errors in agents’ choice to address this concern. Extensive experiments with agent-based models—ride-pooling and education platform—provide support for the efficacy and generalizability of the robust MSR to address negative effects.
{"title":"Managing Digital Platforms with Robust Multi-Sided Recommender Systems","authors":"Onkar Malgonde, He Zhang, B. Padmanabhan, M. Limayem","doi":"10.1080/07421222.2022.2127440","DOIUrl":"https://doi.org/10.1080/07421222.2022.2127440","url":null,"abstract":"ABSTRACT Digital platforms have replaced traditional markets in most industries and orchestrate socioeconomic aspects of our lives. We address the problem of negative direct side network effects that arise with an increased number of agents on one side of the platform. Negative effects, if unaddressed, lead to undesired long-term consequences for the platform by developing a positive vicious cycle. Addressing negative effects require dynamic solution mechanisms that adapt to the changing landscape of platforms. The recommender systems literature has proposed multi-sided recommender systems (MSR) as a dynamic solution to many problems on platforms. However, current state-of-the-art MSRs do not consider uncertainty in predicting agents’ choices, resulting in limited efficacy. We present a robust multi-sided recommender system that considers estimation errors in agents’ choice to address this concern. Extensive experiments with agent-based models—ride-pooling and education platform—provide support for the efficacy and generalizability of the robust MSR to address negative effects.","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"39 1","pages":"938 - 968"},"PeriodicalIF":7.7,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47316271","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 : 2022-10-02DOI: 10.1080/07421222.2022.2127442
R. Banker, Cecilia Feng, P. Pavlou
ABSTRACT Chief Information Officers (CIOs) influence their firm’s strategy implementation and facilitate improved firm performance by effectively managing information technology (IT) resources. However, it remains unclear how firms select CIOs and how the stock market perceives the selection. We posit that firms’ preferences regarding CIO background (business acumen versus technical expertise) depend on their strategic positioning. Also, we argue that the stock market pays attention to the alignment between the appointed CIO’s background and firm strategy. To empirically examine this, we employ factor analysis on a sample of 1,287 CIOs with detailed biographic information on education, work experience, and certification to identify the CIO’s background. Utilizing these measures, we examine whether the appointed CIO’s background depends on the appointing firm’s strategic positioning in a normative model. Then, we use a predictive model to test the stock market reactions to CIO appointments. We document that cost-leadership-leaning firms are more likely to appoint a CIO with a stronger business-oriented background, while differentiation-leaning firms are more likely to appoint a CIO with a stronger technical-oriented background. Interestingly, firms with misaligned CIO appointments suffer a negative stock market reaction. We discuss theoretical and practical implications of selecting aligned versus misaligned CIOs.
{"title":"Businessperson or Technologist: Stock Market Reaction to the Alignment between CIO Background and Firm Strategy","authors":"R. Banker, Cecilia Feng, P. Pavlou","doi":"10.1080/07421222.2022.2127442","DOIUrl":"https://doi.org/10.1080/07421222.2022.2127442","url":null,"abstract":"ABSTRACT Chief Information Officers (CIOs) influence their firm’s strategy implementation and facilitate improved firm performance by effectively managing information technology (IT) resources. However, it remains unclear how firms select CIOs and how the stock market perceives the selection. We posit that firms’ preferences regarding CIO background (business acumen versus technical expertise) depend on their strategic positioning. Also, we argue that the stock market pays attention to the alignment between the appointed CIO’s background and firm strategy. To empirically examine this, we employ factor analysis on a sample of 1,287 CIOs with detailed biographic information on education, work experience, and certification to identify the CIO’s background. Utilizing these measures, we examine whether the appointed CIO’s background depends on the appointing firm’s strategic positioning in a normative model. Then, we use a predictive model to test the stock market reactions to CIO appointments. We document that cost-leadership-leaning firms are more likely to appoint a CIO with a stronger business-oriented background, while differentiation-leaning firms are more likely to appoint a CIO with a stronger technical-oriented background. Interestingly, firms with misaligned CIO appointments suffer a negative stock market reaction. We discuss theoretical and practical implications of selecting aligned versus misaligned CIOs.","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"39 1","pages":"1006 - 1036"},"PeriodicalIF":7.7,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48044012","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 : 2022-10-02DOI: 10.1080/07421222.2022.2127443
Xue Tan, Fujie Jin, A. Dennis
ABSTRACT We conducted three studies to examine how two types of user-generated feedback, appreciation and attention, affect users’ decisions to make voluntary knowledge contributions to electronic networks of practice (ENPs). Appreciation is reflected in positive ratings, votes, and helpfulness evaluations. Attention is reflected in the number of views of contributed content. The first study used clickstream data from a college application ENP in China, where information seekers can read posted information asynchronously and request synchronous consultations with volunteers. The second study was a controlled online experiment in the United States where we assessed users’ willingness to answer questions in a college application ENP asynchronously. The third study examined knowledge contribution across a diverse set of topics using a well-established ENP that serves more than 100 countries. In all three studies, the results consistently show that greater appreciation increased continued knowledge contribution, but greater attention without sufficient appreciation negatively affected contributions. Our findings show the theoretically intertwined nature of attention and appreciation and offer insights for the design and management of ENP feedback systems to encourage user contributions.
{"title":"How Appreciation and Attention Affect Contributions to Electronic Networks of Practice","authors":"Xue Tan, Fujie Jin, A. Dennis","doi":"10.1080/07421222.2022.2127443","DOIUrl":"https://doi.org/10.1080/07421222.2022.2127443","url":null,"abstract":"ABSTRACT We conducted three studies to examine how two types of user-generated feedback, appreciation and attention, affect users’ decisions to make voluntary knowledge contributions to electronic networks of practice (ENPs). Appreciation is reflected in positive ratings, votes, and helpfulness evaluations. Attention is reflected in the number of views of contributed content. The first study used clickstream data from a college application ENP in China, where information seekers can read posted information asynchronously and request synchronous consultations with volunteers. The second study was a controlled online experiment in the United States where we assessed users’ willingness to answer questions in a college application ENP asynchronously. The third study examined knowledge contribution across a diverse set of topics using a well-established ENP that serves more than 100 countries. In all three studies, the results consistently show that greater appreciation increased continued knowledge contribution, but greater attention without sufficient appreciation negatively affected contributions. Our findings show the theoretically intertwined nature of attention and appreciation and offer insights for the design and management of ENP feedback systems to encourage user contributions.","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"39 1","pages":"1037 - 1063"},"PeriodicalIF":7.7,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43186065","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 : 2022-10-02DOI: 10.1080/07421222.2022.2127449
A. Nehme, Joey F. George
ABSTRACT Not securing smart home devices has proven a threat to cyberspace. This has underscored the importance of using fear appeals to promote users’ information security behavior. We practiced context-specific theorization to enhance fear appeal theory and design. Particularly, we extended Protection Motivation Theory to include avoidant-focused motivation (i.e., users’ intent to avoid using their devices), the positive emotion of hope, and information technology (IT)-self extension. Our hypotheses include that fear engenders both protection and avoidant-focused motivations, hope mediates coping appraisal to engender (reduce) protection (avoidant-focused) motivation, and IT-self-extension acts as an antecedent. We conducted four studies, including two surveys and two experiments, and validated our extensions. Our main theoretical contributions include showing that hope is critical in determining which coping mechanism occurs and that it improves the theory’s predictive power. In terms of practice, we demonstrate that a fear appeal message with a self-extension component and a strong coping component is more effective.
{"title":"Approaching IT Security & Avoiding Threats in the Smart Home Context","authors":"A. Nehme, Joey F. George","doi":"10.1080/07421222.2022.2127449","DOIUrl":"https://doi.org/10.1080/07421222.2022.2127449","url":null,"abstract":"ABSTRACT Not securing smart home devices has proven a threat to cyberspace. This has underscored the importance of using fear appeals to promote users’ information security behavior. We practiced context-specific theorization to enhance fear appeal theory and design. Particularly, we extended Protection Motivation Theory to include avoidant-focused motivation (i.e., users’ intent to avoid using their devices), the positive emotion of hope, and information technology (IT)-self extension. Our hypotheses include that fear engenders both protection and avoidant-focused motivations, hope mediates coping appraisal to engender (reduce) protection (avoidant-focused) motivation, and IT-self-extension acts as an antecedent. We conducted four studies, including two surveys and two experiments, and validated our extensions. Our main theoretical contributions include showing that hope is critical in determining which coping mechanism occurs and that it improves the theory’s predictive power. In terms of practice, we demonstrate that a fear appeal message with a self-extension component and a strong coping component is more effective.","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"39 1","pages":"1184 - 1214"},"PeriodicalIF":7.7,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44717111","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 : 2022-10-02DOI: 10.1080/07421222.2022.2127441
Shalini Chandra, Anuragini Shirish, S. Srivastava
ABSTRACT Driven by the need to provide continuous, timely, and efficient customer service, firms are constantly experimenting with emerging technological solutions. In recent times firms have shown an increased interest in designing and implementing artificial intelligence (AI)-based interactional technologies, such as conversational AI agents and chatbots, that obviate the need for having human service agents for the provision of customer service. However, the business impact of conversational AI is contingent on customers using and adequately engaging with these tools. This engagement depends, in turn, on conversational AI’s similarity, or likeness to the human beings it is intended to replace. Businesses therefore need to understand what human-like characteristics and competencies should be embedded in customer-facing conversational AI agents to facilitate smooth user interaction. This focus on “human-likeness” for facilitating user engagement in the case of conversational AI agents is in sharp contrast to most prior information systems (IS) user engagement research, which is predicated on the “instrumental value” of information technology (IT). Grounding our work in the individual human competency and media naturalness literatures, we theorize the key role of human-like interactional competencies in conversational AI agents—specifically, cognitive, relational, and emotional competencies—in facilitating user engagement. We also hypothesize the mediating role of user trust in these relationships. Following a sequential mixed methods approach, we use a quantitative two-wave, survey-based study to test our model. We then examine the results in light of findings from qualitative follow-up interviews with a sampled set of conversational AI users. Together, the results offer a nuanced understanding of desirable human-like competencies in conversational AI agents and the salient role of user trust in fostering user engagement with them. We also discuss the implications of our study for research and practice.
{"title":"To Be or Not to Be …Human? Theorizing the Role of Human-Like Competencies in Conversational Artificial Intelligence Agents","authors":"Shalini Chandra, Anuragini Shirish, S. Srivastava","doi":"10.1080/07421222.2022.2127441","DOIUrl":"https://doi.org/10.1080/07421222.2022.2127441","url":null,"abstract":"ABSTRACT Driven by the need to provide continuous, timely, and efficient customer service, firms are constantly experimenting with emerging technological solutions. In recent times firms have shown an increased interest in designing and implementing artificial intelligence (AI)-based interactional technologies, such as conversational AI agents and chatbots, that obviate the need for having human service agents for the provision of customer service. However, the business impact of conversational AI is contingent on customers using and adequately engaging with these tools. This engagement depends, in turn, on conversational AI’s similarity, or likeness to the human beings it is intended to replace. Businesses therefore need to understand what human-like characteristics and competencies should be embedded in customer-facing conversational AI agents to facilitate smooth user interaction. This focus on “human-likeness” for facilitating user engagement in the case of conversational AI agents is in sharp contrast to most prior information systems (IS) user engagement research, which is predicated on the “instrumental value” of information technology (IT). Grounding our work in the individual human competency and media naturalness literatures, we theorize the key role of human-like interactional competencies in conversational AI agents—specifically, cognitive, relational, and emotional competencies—in facilitating user engagement. We also hypothesize the mediating role of user trust in these relationships. Following a sequential mixed methods approach, we use a quantitative two-wave, survey-based study to test our model. We then examine the results in light of findings from qualitative follow-up interviews with a sampled set of conversational AI users. Together, the results offer a nuanced understanding of desirable human-like competencies in conversational AI agents and the salient role of user trust in fostering user engagement with them. We also discuss the implications of our study for research and practice.","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"39 1","pages":"969 - 1005"},"PeriodicalIF":7.7,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45112712","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：