Information and Organization最新文献

High uncertainty tasks such as making a medical diagnosis, judging a criminal justice case and driving in a big city have a very low margin for error because of the potentially devastating consequences for human lives. In this paper, we focus on how humans learn from uncertainty while performing a high uncertainty task with AI systems. We analyze Tesla's autonomous driving systems (ADS), a type of AI system, drawing on crash investigation reports, published reports on formal simulation tests and YouTube recordings of informal simulation tests by amateur drivers. Our empirical analysis provides insights into how varied levels of uncertainty tolerance have implications for how humans learn from uncertainty in real-time and over time to jointly perform the driving task with Tesla's ADS. Our core contribution is a theoretical model that explains human-AI joint task performance. Specifically, we show that, the interdependencies between different modes of AI use including uncontrolled automation, limited automation, expanded automation, and controlled automation are dynamically shaped through humans' learning from uncertainty. We discuss how humans move between these modes of AI use by increasing, reducing, or reinforcing their uncertainty tolerance. We conclude by discussing implications for the design of AI systems, policy into delegation in joint task performance, as well as the use of data to improve learning from uncertainty.

Digital platforms have grown rapidly by facilitating connections among users to exchange products, services, or information. However, very few platforms have a truly global footprint given that factors such as competition, imitation, innovation, and cultural and political barriers hamper a digital platform's international growth path. The geographical scope of network effects plays a crucial role in this process, impacting users at various levels from the local to the global. We model the dynamics of international platform competition and predict its outcomes in terms of global potential market percentage through a simulation of the international growth of a two-sided platform in competition with two follower platforms in different locations (home/abroad) and different internationalization strategies (gradual/accelerated), and operating under different network effects (local/global). The model contemplates different delays in the launching of the rival platforms and different degrees of innovation (improvement) in comparison with the original platform.

Our findings highlight the crucial role of network effects, with global effects benefiting first movers and local effects favoring followers, especially if they start in a market different from the first mover's. Moreover, domestic followers must innovate, while followers in less competitive markets with local network effects have more options to increase potential market percentage, including launching a clone. These insights offer valuable suggestions for strategy development and regulatory considerations related to market share, market power, and international expansion.

The sociomaterial lens within IS research holds that agency should not be considered as a property solely of humans, or of technology, but instead arises from an emergent interaction between the two. This, emergent, account of agency deepens our understanding of unfolding IS practice, but its largely cognitive orientation remains naïve towards affectively-sensed motivations that also form part of this interaction. By implication, a sociomaterial perspective lacking an affective dimension offers an incomplete conceptualisation of information systems. In response, an affectively-informed negative ontology encourages IS researchers to extend their focus beyond the visible, to encompass how actors' receptiveness towards material objects (discourses, technologies) is shaped by deep, affectively-derived motivations of which they are not focally aware, but which nonetheless acquire agency in contributing to a sociomaterial outcome. A central argument, and illustrative empirical vignette, demonstrate how the concepts of sociomateriality, affect, and negative ontology combine to offer researchers an enhanced understanding of relational agency. A discussion follows, exploring some initial ontological, epistemological and methodological implications of an affectively-informed negative ontology for IS research.

To reduce technical and task interdependencies, modularization has been considered important in OSS development. However, the existing literature implicitly takes a static view that software structure and organizational structure are established early on and change slowly over time, if at all. Such a view does not fully reflect the complex and dynamic nature of software development and tends to overlook the role played by human agents as they ramp involvement up and down over time. This study considers that coordination practice plays an important role in altering technical interdependencies in OSS development. This study investigates coordination practices that result in changes in software coupling—in particular, increases in software coupling. This study automatically analyzes the code in 72 software releases and 1033 task episodes of three successful OSS projects—GNU grep, IPython, and Scikit-image. This study takes a fine-grained practice-oriented perspective that views the way that the work is done as constituting the organization. In our conceptualization, OSS contributors use a configuration of multiple organizational elements, enacted and varying across specific episodes of practice. In line with this perspective, this study takes a configurational approach, uses fuzzy-set qualitative comparative analysis (fsQCA) to analyze episodes that led to decreases, no changes, and increases in software coupling during the inter-release periods in which the level of software coupling increased significantly, which we call focal period. We find that co-work involving multiple individuals tends to result in code that adds technical dependencies (increases in software coupling) during the focal period. To illustrate this beyond our fuzzy-set analysis, we present and discuss three episodes in narrative detail. The fine-grained, configurational analysis in this study supports the idea that the organizing process is ongoing enactment. In this study, OSS systems are an amalgam of code that builds up in different episodes each possibly different organizational configurations, rather than thinking of the OSS systems or projects as static or singular.

AI systems are increasingly being deployed in organizations to support customer service (CS) departments. However, in practice, the introduction of AI tools often fails to meet these expectations and results in negative consequences, such as worker resistance and dissatisfaction. Yet we have little understanding of the process of how and why initially positive design intentions of AI tools result in negative consequences. Building on a qualitative in-depth case study of a Chinese firm introducing an AI tool in sales, we found that whereas the AI tool's initial design seemingly intended to lead to salespeople's empowerment and first achieved respective outcomes, over time the tool was appropriated for managerial control. We show that this devolution emerged organically from a growing managerial awareness of the affordances that the AI tool offered managers to perform their work better. Our study contributes to the literature on AI by highlighting the potential dangers of AI tools and emphasizing the importance of including workers in the AI tool's design and implementation phases.

Firms are increasingly adopting digital transformation as a strategic priority. However, the path to successful transformation remains uncertain for many organizations. This paper examines the establishment and evolution of competency centers in two case study organizations, historically used in enterprise systems, in addressing the complexity and challenges of digital transformation. The interactions within these competency centers are analyzed through assemblage theory to understand the emergent relations between heterogeneous parts (technology, people, and organization) and the dynamic processes of new configurations. The insights from this research show the critical role of the competency center in any enterprise system's success and how it could continue playing a central role in future digital transformation initiatives. By providing a new lens to examine these issues, the assemblage theory provided a new theoretical perspective to the IS field and a new alternative empirical setting to the organizational literature.

Consumers play an increasingly central role in born digital organisations, including driving new approaches to consumer interaction, communication, and marketing. However, we know little about how born digital organise internally to manage and respond to consumer demands. In this paper, we studied an organisation providing online travel services where its aim was to reorganise internally, in relation to consumers, through developing a set of ‘search’ practices. The role of search is particularly salient for born digitals, giving rise to new roles and expertise where organisations attempt to pre-empt user actions. Through qualitative research, we show how a born digital organisation creates new practices that we label pre-emptive, reactive, reflective and adaptive. Our main finding is that rapidly and constantly reconfiguring practices, what these new experts call ‘constructive disruption’, is essential for born digitals to manage relationships with consumers. Our paper contributes by providing a better understanding of practices within born digital organisations, and specifically the practices born digitals use to navigate unpredictable emerging changes and produce constant novelty for customers. We also contribute to the concept of search and provide examples of how it might be employed to better understand digital organising and digital transformation.

Small business revenues worldwide were drastically affected by lockdowns during the COVID-19 pandemic. As a result, many small businesses introduced new functionality through the adoption of digital technologies. However, little is known about the nature of these digital technology innovations, including whether they differed across industry sectors. Through a modified case study approach, we examine digital technology responses to the pandemic by small businesses that were identified in Google News. We introduce a new framework designed to describe the nature of the responses. Most small businesses that were examined introduced digital responses by offering new e-commerce facilities and/or converting their existing services to ‘e-services’, with some important cross sector exceptions. Practical suggestions for small businesses are provided.

The diffusion of disinformation via social media has become a pressing societal concern for business leaders and policy makers. In recent years, online disinformation has been implicated as a source of field-level institutional change across a variety of societal contexts. To better understand how online disinformation changes institutional issue fields, we explore how digital materiality affords users opportunities to create and propagate disinformation. We introduce and define three social media material features: modular content, content flow, and manifold network structures. From these digital materiality elements, we articulate three disinformation affordances: crafting, amplifying, and partitioning. We rely on several vignettes – far-right political conspiracy group, QAnon, anti-vaccination (i.e., anti-Vaxxers), and flat Earth beliefs – to illustrate how social media users exploit digital materiality and enact disinformation affordances. Our theoretical development also contributes to our understanding of how online disinformation disrupts institutional issue fields. In particular, we highlight several potential changes to institutional issue fields regarding power centralization, subfield structures, and institutional infrastructure. We conclude by offering recommendations for future research and social media policy.