When Reflection Hurts: The Effect of Cognitive Processing Types on Organizational Adaptation to Discontinuous Change

2023 | Organization Science | Citations: 1

Authors: Alves, Marlon Fernandes Rodrigues; Vastola, Vincenzo; Vasconcelos Ribeiro Galina, Simone; Zollo, Maurizio

Abstract: Technological breakthroughs, institutional disruptions, and natural disasters of ... Expand

Abstract: Technological breakthroughs, institutional disruptions, and natural disasters often alter the course of organizations and entire industries. Such discontinuous changes threaten organizations’ survival by affecting the value of the knowledge accumulated in routines and capabilities. Although it is widely acknowledged that managerial cognition is a critical antecedent of organizational responses to discontinuous change, the role of type 1 (intuitive) and type 2 (reflective) processing in the adaptation of shared patterns of behavior, that is, routines, remains understudied. Drawing on dual-process theory, we propose that particular features of type 1 processing render this approach superior to type 2 processing, especially in highly ambiguous environments in which information is limited and difficult to verify. We tested our hypotheses in a longitudinal experiment linking individual-level factors with organizational-level practices of routine adaptation. Experienced managers, paired in 80 groups, developed routines in a first round of a simulation game; in a second round, we then introduced a discontinuous change making previous routines obsolete in order to observe how they adapted. The data show that priming type 1 processing facilitates organizational adaptation more than type 2 processing by providing faster, more routinized, efficiently coordinated, and optimal responses. In addition, type 1 appears to be more functional in highly ambiguous environments, whereas type 1 and type 2 processes yield similar levels of performance under low levels of ambiguity. Overall, our study advances the understanding of the nondeliberative dimension of organizational adaptation to discontinuous change.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Finance Code 001).Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1517. Collapse

Topics: decision making strategic management innovation management problem solving task productivity

Methods: experiment longitudinal research parametric test ANOVA statistical hypothesis test

Theories: dual-system theory dynamic capabilities theory

Decision support tool to define the optimal pool testing strategy for SARS-CoV-2

2023 | Decision Support Systems | Citations: 0

Authors: Barracosa, Bruno; Felício, João; Carvalho, Ana; Moreira, Leonilde M.; Mendes, Filipa; Verde, Sandra Cabo; Pinto-Varela, Tânia

Abstract: This work proposes a holistic decision support tool to be used by diverse stakeh ... Expand

Abstract: This work proposes a holistic decision support tool to be used by diverse stakeholders and decision-makers, integrating experimental data. Considering the characteristics of each region, the tool aids in defining the most suitable testing strategies per country or region: number of tests, time, cost, type of pool strategy based on prevalence rate interval, and the use of centralization vs. decentralization of testing strategies. The tool con­ tributes to the field of decision support systems theoretically by introducing a novel model for testing decisions in extreme situations within a specific region, and practically, by demonstrating how laboratory data can be applied to real-life decision-making in that same region. This tool has been validated with two real case studies (Portugal and France) and has applied, as input data, real experimental results. The results suggested tree- and matrixbased strategies for low and high prevalence rates. A decentralized testing strategy improves the financial and time gains introduced by pool testing; however, centralizing the decisions shows a more straightforward implementation and resource management of the pool testing system with a low-performance loss. Therefore, there might be a solution to consider overcoming operational restrictions. Collapse

Topics: decision support system pandemic

Methods: case study optimization model experiment simulation machine learning

CONFIDENCE MATTERS: A SIMULATION-BASED STABILITY ANALYSIS OF ALGORITHMIC STABLECOINS

2023 | European Conference On Information Systems | Citations: 0

Authors: Baumeister, Alexander; Hägele, Sascha

Abstract: ... Expand

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Topics: stablecoin Ethereum cryptocurrency

Methods: simulation Monte Carlo simulation agent based simulation

Team Performance: Nature and Antecedents of Nonnormal Distributions

2023 | Organization Science | Citations: 0

Authors: Bradley, Kyle J.; Aguinis, Herman

Abstract: Team research typically assumes that team performance is normally distributed: t ... Expand

Abstract: Team research typically assumes that team performance is normally distributed: teams cluster around average performance, performance variability is not substantial, and few teams inhabit the upper range of the distribution. Ironically, although most team research and methodological practices rely on the normality assumption, many theories actually imply nonnormality (e.g., performance spirals, team composition, team learning, punctuated equilibrium). Accordingly, we investigated the nature and antecedents of team performance distributions by relying on 274 performance distributions including 200,825 teams (e.g., sports, politics, firefighters, information technology, customer service) and more than 500,000 workers. First, regarding their overall nature, only 11% of the distributions were normal, star teams are much more prevalent than predicted by normality, the power law with an exponential cutoff is the most dominant distribution among nonnormal distributions (i.e., 73%), and incremental differentiation (i.e., differential performance trajectories across teams) is the best explanation for the emergence of these distributions. Second, this conclusion remained unchanged after examining theory-based boundary conditions (i.e., tournament versus nontournament contexts, performance as aggregation of individual-level performance versus performance as a team-level construct, performance assessed with versus without a hard left-tail zero, and more versus less sample homogeneity). Third, we used the team learning curve literature as a conceptual framework to test hypotheses and found that authority differentiation and lower temporal stability are associated with distributions with larger performance variability (i.e., a greater proportion of star teams). We discuss implications for existing theory, future research directions, and methodological practices (e.g., need to check for nonnormality, Bayesian analysis, outlier management). Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1619. Collapse

Topics: team productivity customer service anonymity systems development virtual teamwork

Methods: meta analysis statistical hypothesis test Bayesian analysis descriptive statistic chi squared test

Organizing Entrepreneurial Teams: A Field Experiment on Autonomy over Choosing Teams and Ideas

2023 | Organization Science | Citations: 1

Authors: Boss, Viktoria; Dahlander, Linus; Ihl, Christoph; Jayaraman, Rajshri

Abstract: Scholars have suggested that autonomy can lead to better entrepreneurial team pe ... Expand

Abstract: Scholars have suggested that autonomy can lead to better entrepreneurial team performance. Yet, there are different types of autonomy, and they come at a cost. We shed light on whether two fundamental organizational design choices—granting teams autonomy to (1) choose project ideas to work on and (2) choose team members to work with—affect performance. We run a field experiment involving 939 students in a lean startup entrepreneurship course over 11 weeks. The aim is to disentangle the separate and joint effects of granting autonomy over choosing teams and choosing ideas compared with a baseline treatment with preassigned ideas and team members. We find that teams with autonomy over choosing either ideas or team members outperform teams in the baseline treatment as measured by pitch deck performance. The effect of choosing ideas is significantly stronger than the effect of choosing teams. However, the performance gains vanish for teams that are granted full autonomy over choosing both ideas and teams. This suggests the two forms of autonomy are substitutes. Causal mediation analysis reveals that the main effects of choosing ideas or teams can be partly explained by a better match of ideas with team members’ interests and prior network contacts among team members, respectively. Although homophily and lack of team diversity cannot explain the performance drop among teams with full autonomy, our results suggest that self-selected teams fall prey to overconfidence and complacency too early to fully exploit the potential of their chosen idea. We discuss the implications of these findings for research on organizational design, autonomy, and innovation.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: The authors are grateful for funding from the Innovation Growth Laboratory, the Peter Curtius Foundation, and the Deutsche Forschungsgemeinschaft [Grant CRC TRR 190].Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1520. Collapse

Topics: team productivity entrepreneurship missing data intrinsic motivation evaluation criteria

Methods: experiment experimental group survey causal mediation analysis field experiment

Adversarial Outlier Detection Methods for Health Care Fraud

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Ekin, Tahir

Abstract: Outlier detection is widely used for identification of unusual suspicious patte ... Expand

Abstract: Outlier detection is widely used for identification of unusual suspicious patterns in health care fraud detection. However, the impact of adversarial perturbations on outliers and the related decisions are not well studied. In the health care fraud detection domain, standard practice does not consider health care billings being subject to intentional data manipulations. This paper presents a decision theoretic approach for outlier detection in adversarial environments. Proposed adversarial risk analysis-based framework allows incomplete information and adversarial perturbations on the data inputs. While the work with actual health care fraud data is ongoing, the proposed novel adversarial outlier detection method has the potential to support health care fraud audit decision support systems. KeywordsAdversarial unsupervised learning, adversarial risk analysis, health care fraud, fraud analytics, Bayesian. Collapse

Topics: fraud detection

Methods: anomaly detection unsupervised learning Monte Carlo simulation machine learning

Theories: game theory

What makes a Tweet so sweet: The neurocognitive effects of hedonic information consumption

2023 | Information & Management | Citations: 0

Authors: Fadel, Kelly J.; Meservy, Thomas O.; Kirwan, C. Brock

Abstract: Hedonic information consumption (HIC) refers to the consumption of information f ... Expand

Abstract: Hedonic information consumption (HIC) refers to the consumption of information for non-task-oriented purposes such as entertainment or pleasure. With the explosive growth of information availability through online channels such as social media, HIC has become a common and growing phenomenon; however, most information systems research to date has focused on factors surrounding information consumption for utilitarian rather than hedonic purposes. In this paper, we take an initial step to inform theory in this area by applying a NeuroIS lens to explore HIC behavior. We postulate that information is more likely to be hedonically consumed when it is appraised as interesting, and that certain characteristics of the information involved in HIC, namely its novelty and valence, play a role in determining its interestingness. Moreover, we hypothesize that HIC is driven by the neurobiological reactions that take place in response to information novelty and valence. We report the results of a behavioral and an fMRI experiment designed to measure the relationship between these information dimensions and neu­ rocognitive responses in the context of a popular social media platform. Our results provide preliminary evidence for differential processing patterns related to novelty and valence that can inform ongoing theory building surrounding HIC behaviors. Collapse

Topics: Twitter social media social media site database system decision making

Methods: experiment functional magnetic resonance imaging theory development NeuroIS magnetic resonance imaging

Theories: theory of information information systems theory

Extended Generativity Theory on Digital Platforms

2023 | Information Systems Research | Citations: 2

Authors: Fürstenau, Daniel; Baiyere, Abayomi; Schewina, Kai; Schulte-Althoff, Matthias; Rothe, Hannes

Abstract: The assumption that generativity engenders unbounded growth has acquired an almo ... Expand

Abstract: The assumption that generativity engenders unbounded growth has acquired an almost taken-for-granted position in information systems and management literature. Against this premise, we examine the relationship between generativity and user base growth in the context of a digital platform. To do this, we synthesize the literature on generativity into two views, social interaction (expansion of ecosystem boundaries) and product view (expansion of product boundaries), that jointly and individually relate to user base growth. Both views help us explain how opening a platform relates to the emergence and resolution of conflicting expectations in a platform ecosystem that result in new functions and expanded use. We adopt a panel vector autoregressive approach combining data from six large transaction platforms that engaged with open-source developer communities. We found that the dominant narrative of generativity engendering growth, although generally supported by our analysis, obscures the fact that the inverse is also true; that is, growth can lead to expansion of product boundaries (inverse generativity) and that generativity can be bounded; that is, growth can stabilize ecosystem boundaries (bounded generativity). Against this background, we propose an extended generativity theory that presents generativity and growth in an integrative view and raises awareness about the limitations of the “unbounded growth” claim. We conclude that there is value in separating the two views of generativity conceptually and analytically, along with their relationship to user base growth, and we call for research on the pathways through which generativity produces growth. History: Ola Henfridsson, Senior Editor; Robert Wayne Gregory, Associate Editor. Collapse

Topics: digital platform innovation management open source electronic commerce accounting

Methods: longitudinal research Granger causality time series analysis Student's t-test parametric test

Do Early Words from New Ventures Predict Fundraising? A Comparative View of Social Media Narratives

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Havakhor, Taha; Golmohammadi, Alireza; Sabherwal, Rajiv; Gauri, Dinesh

Abstract: Online equity markets have significantly changed the dynamics of connecting ang ... Expand

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. Collapse

Topics: Twitter social media social media analytics social capital website

Methods: machine learning chi squared test latent dirichlet allocation robustness check theoretical contribution

Theories: lemon market theory

Managing Uncertainty: An Experiment on Delegation and Team Selection

2023 | Organization Science | Citations: 0

Authors: Hamman, John R.; Martínez-Carrasco, Miguel A.

Abstract: We study how organizations use team selection and delegation of authority jointl ... Expand

Abstract: We study how organizations use team selection and delegation of authority jointly to navigate uncertain environments. To do so, we model a managerial decision environment in which a manager both determines the skill heterogeneity of the workers and determines whether to retain or delegate the ability to allocate tasks. Delegation enables better-informed workers to allocate tasks more efficiently when uncertainty is high relative to the incentive conflict between manager and worker. Our novel approach allows us to illustrate that this conflict is endogenously determined by the team selection decision. Experimental data support—although not globally—the direction of our theoretical hypotheses and offer insight into how and why choices deviate from expected behavior. Notably, we identify behavioral characteristics that aid decisions along each dimension. Deliberative thinking improves all decisions under low uncertainty and improves team selection regardless of the level of uncertainty. Risk tolerance improves all decisions in highly uncertain situations and helps managers optimally delegate decision rights in all settings. The results highlight potentially costly ways in which managers seek to simplify their decisions but show how deliberative thinking and risk tolerance can improve performance in a complementary manner.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: The authors thank Florida State University and the Barcelona Graduate School of Economics for financial support.Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/orsc.2021.1545. Collapse

Topics: organization structure environmental uncertainty data quality decision making task interdependence

Methods: experiment regression analysis method logistic regression descriptive statistic parametric test

Theories: organizational theory transaction cost economics agency theory theory of bounded rationality