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MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1087-1112
Author(s):  
Emmanuelle Vaast ◽  
Alain Pinsonneault ◽  
◽  

Occupations are increasingly embedded with and affected by digital technologies. These technologies both enable and threaten occupational identity and create two important tensions: they make the persistence of an occupation possible while also potentially rendering it obsolete, and they magnify both the similarity and distinctiveness of occupations with regard to other occupations. Based on the critical case study of an online community dedicated to data science, we investigate longitudinally how data scientists address the two tensions of occupational identity associated with digital technologies and reach transient syntheses in terms of “optimal distinctiveness” and “persistent extinction.” We propose that identity work associated with digital technologies follows a composite life-cycle and dialectical process. We explain that people constantly need to adjust and redefine their occupational identity, i.e., how they define who they are and what they do. We contribute to scholarship on digital technologies and identity work by illuminating how people deal in an ongoing manner with digital technologies that simultaneously enable and threaten their occupational identity.


MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1557-1580
Author(s):  
Elmira van den Broek ◽  
◽  
Anastasia Sergeeva ◽  
Marleen Huysman Vrije ◽  
◽  
...  

The introduction of machine learning (ML)in organizations comes with the claim that algorithms will produce insights superior to those of experts by discovering the “truth” from data. Such a claim gives rise to a tension between the need to produce knowledge independent of domain experts and the need to remain relevant to the domain the system serves. This two-year ethnographic study focuses on how developers managed this tension when building an ML system to support the process of hiring job candidates at a large international organization. Despite the initial goal of getting domain experts “out the loop,” we found that developers and experts arrived at a new hybrid practice that relied on a combination of ML and domain expertise. We explain this outcome as resulting from a process of mutual learning in which deep engagement with the technology triggered actors to reflect on how they produced knowledge. These reflections prompted the developers to iterate between excluding domain expertise from the ML system and including it. Contrary to common views that imply an opposition between ML and domain expertise, our study foregrounds their interdependence and as such shows the dialectic nature of developing ML. We discuss the theoretical implications of these findings for the literature on information technologies and knowledge work, information system development and implementation, and human–ML hybrids.


MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1581-1602
Author(s):  
Timo Sturm ◽  
◽  
Jin Gerlacha ◽  
Luisa Pumplun ◽  
Neda Mesbah ◽  
...  

With the rise of machine learning (ML), humans are no longer the only ones capable of learning and contributing to an organization’s stock of knowledge. We study how organizations can coordinate human learning and ML in order to learn effectively as a whole. Based on a series of agent-based simulations, we find that, first, ML can reduce an organization’s demand for human explorative learning that is aimed at uncovering new ideas; second, adjustments to ML systems made by humans are largely beneficial, but this effect can diminish or even become harmful under certain conditions; and third, reliance on knowledge created by ML systems can facilitate organizational learning in turbulent environments, but this requires significant investments in the initial setup of these systems as well as adequately coordinating them with humans. These insights contribute to rethinking organizational learning in the presence of ML and can aid organizations in reallocating scarce resources to facilitate organizational learning in practice.


MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1113-1148
Author(s):  
Angela Xia Liu ◽  
◽  
Yilin Li ◽  
Sean Xu ◽  
◽  
...  

This work examines the question of who is more likely to provide future helpful reviews in the context of online product reviews by synergistically using personality theories and data analytics. It trains a deep learning model to infer a reviewer’s personality traits. This enables analyses to reveal the role of personality traits in review helpfulness among a large population of reviewers. We develop hypotheses on how personality traits are associated with review helpfulness, followed by hypotheses testing that confirms that higher review helpfulness is related to higher openness, conscientiousness, extraversion, and agreeableness and to lower emotional stability. These results suggest the appropriateness of using these five personality traits as inputs for developing a model for predicting future review helpfulness. Based on an ensemble model using supervised classification algorithms, we develop a predictive model and demonstrate its superior performance. Theoretical and practical implications are discussed.


MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1603-1644
Author(s):  
Jingyu Li ◽  
◽  
Mengxiang Li ◽  
Xincheng Wang ◽  
Jason Bennett Thatcher ◽  
...  

This paper applies upper echelons theory to investigate whether chief information officers (CIOs) and boards of directors affect the development of AI orientation, which represents firms’ overall strategic direction and goals regarding the introduction and application of artificial intelligence (AI)technology. We tested our model using a dataset drawn from 1,454 publicly listed firms in China. Our findings show that the presence of a CIO positively influences AI orientation and that board educational diversity, R&D experience, and AI experience positively moderate the CIO’s effect on AI orientation. Our post hoc analysis further demonstrates that these board characteristics represent contingencies that impact AI orientation but not conventional IT orientation. This paper contributes to the upper echelons literature and IT management research by offering contextualized arguments that explain new business and IT strategies such as AI orientation. Further, our findings suggest important implications about how to build top management teams and boards capable of effectively developing AI orientations


MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1187-1212
Author(s):  
Rikard Lindgren ◽  
◽  
Lars Mathiassen ◽  
Ulrike Schultze ◽  
◽  
...  

Technology standardization unfolds as a dialectic process marked by paradoxical tensions. However, standardization research has yet to provide a dialectic analysis of how tensions and management responses interact recursively over time, and with what effect. In this paper, we apply dialectics to analyze an action research study of a Swedish initiative that developed and diffused a technology standard to facilitate the integration of disparate IT systems in road haulage firms. Drawing on the technology standardization literature and our empirical analysis, we engage in midrange theorizing to capture the recursive dynamics through which standard-setters construct and respond to manifestations of three latent tensions: development versus diffusion activities, private versus public interests, and local versus global solutions. Our resulting dialectic theorizing explicates how standard-setters bring these latent tensions into being; how they construct salient tensions through the oppositional logics of polarization, complementarity, and mutuality; how they manage these tensions through splitting, integrating, and suspension responses; and how consequential functional, architectural, and organizational standardization outcomes produce a new social order in which new tensions emerge. These theoretical insights contribute to both the technology standardization and dialectics literatures.


MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1025-1058
Author(s):  
Pouya Rahmati ◽  
◽  
Ali Tafti ◽  
J. Christopher Westland ◽  
Cesar Hidalgo ◽  
...  

During the last four decades, digital technologies have disrupted many industries. Car control systems have gone from mechanical to digital. Telephones have changed from sound boxes to portable computers. But have the firms that digitized their products and services become more valuable than firms that didn’t? Here we introduce the construct of digital proximity, which considers the interdependent activities of firms linked in an economic network. We then explore how the digitization of products and services affects a company’s Tobin’s q—the ratio of market value over assets—a measure of the intangible value of a firm. Our panel regression methods and robustness tests suggest the positive influence of a firm’s digital proximity on its Tobin’s q. This implies that firms able to come closer to the digital sector have increased their intangible value compared to those that have failed to do so. These findings contribute a new way of measuring digitization and its impact on firm performance that is complementary to traditional measures of information technology (IT) intensity.


MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1007-1024
Author(s):  
Prasanna Karhade ◽  
◽  
John Qi Dong ◽  

Firms’ investment in information technology (IT) has been widely considered to be a key enabler of innovation. In this study, we integrate prior findings on the augmenting pathways (where IT investment supports innovation) with a new theory explaining the suppressing pathways (where dynamic adjustment costs associated with large IT investment can be detrimental to innovation) to propose an overall inverted U-shaped relationship between IT investment and commercialized innovation performance (CIP). To test our theory, we analyze a unique panel dataset from the largest economy in Europe and discovered a curvilinear relationship between IT investment and CIP for firms across a broad spectrum of industries. Our research presents empirical evidence corroborating the augmenting and suppressing pathways linking IT investment and CIP. Our findings serve as a cautionary signal to executives, discouraging overinvestment in IT.


MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1483-1500
Author(s):  
Mike Teodorescu ◽  
◽  
Lily Morse ◽  
Yazeed Awwad ◽  
Gerald Kane ◽  
...  

Machine learning (ML) tools reduce the costs of performing repetitive, time-consuming tasks yet run the risk of introducing systematic unfairness into organizational processes. Automated approaches to achieving fair- ness often fail in complex situations, leading some researchers to suggest that human augmentation of ML tools is necessary. However, our current understanding of human–ML augmentation remains limited. In this paper, we argue that the Information Systems (IS) discipline needs a more sophisticated view of and research into human–ML augmentation. We introduce a typology of augmentation for fairness consisting of four quadrants: reactive oversight, proactive oversight, informed reliance, and supervised reliance. We identify significant intersections with previous IS research and distinct managerial approaches to fairness for each quadrant. Several potential research questions emerge from fundamental differences between ML tools trained on data and traditional IS built with code. IS researchers may discover that the differences of ML tools undermine some of the fundamental assumptions upon which classic IS theories and concepts rest. ML may require massive rethinking of significant portions of the corpus of IS research in light of these differences, representing an exciting frontier for research into human–ML augmentation in the years ahead that IS researchers should embrace.


MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1213-1248
Author(s):  
Tingting Nian ◽  
◽  
Yuyuan (Anthony) Zhu ◽  
Vijay Gurbaxani ◽  
◽  
...  

Powered by digital technologies, many peer-to-peer platforms, or what is called the sharing economy, have emerged in the past decade. Although the impact of the sharing economy has received considerable attention over the past few years, extant research has not fully documented the impact of the sharing economy on consumers, workers, industry, or society as a whole. In this study, we exploit the geographical and temporal variation in Uber’s entry to examine its impact on the personal bankruptcy rate as well as on other consumer credit default rates. We empirically document the changes in personal bankruptcy filings after Uber’s entry, and show that personal bankruptcy filings under Chapter 7 experience a drop of 0.047 per 1,000 people after Uber enters a county, which translates to a 3.26% reduction in quarterly bankruptcy filings. Uber’s entry also leads to a reduction in Chapter 13 personal bankruptcy filings, but to a smaller degree (0.018 cases per 1,000 people per quarter). We check the validity of our estimates using business bankruptcy filings, which we find are uncorrelated with Uber’s entry.


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