How “What you think you know about cybersecurity” can help users make more secure decisions

2023 | Information & Management | Citations: 0

Authors: Fard Bahreini, Amir; Cavusoglu, Hasan; Cenfetelli, Ronald T.

Abstract: The increasing use of information technology artifacts in daily life makes secur ... Expand

Abstract: The increasing use of information technology artifacts in daily life makes security a shared responsibility of both users and companies. In recent years, increasing a user’s objective (i.e., actual) security knowledge and providing applications with more secure default settings appear among the most ubiquitous tools companies use to broaden their efforts to help users make more secure decisions. Examining both solutions matters because they are widely used, cost effective, and understood by many security practitioners. Additionally, default settings and users’ objective knowledge provide anchors for decision-making. However, human errors and insecure default settings are increasing and raising further questions about the efficacy of such efforts. Using the theory of bounded ra­ tionality, we investigated the role of objective, subjective (i.e., self-assessed) security knowledge, and default settings security level on the overall decision security. We found that objective security knowledge can lead to secure decisions when paired with high subjective security knowledge. In the absence of the latter, objective security knowledge is unable to lead to better security decisions. Furthermore, subjective security knowledge reduces the extent to which users fully accept default security settings, thereby mitigating bias toward insecure default settings. Collapse

Topics: mobile application data security decision making self efficacy mobile application market

Methods: survey descriptive statistic structural equation modeling literature study post-hoc analysis

Theories: theory of bounded rationality

On the Same Page? What Users Benefit from a Desktop View on Mobile Devices

2023 | Information Systems Research | Citations: 0

Authors: Fink, Lior; Papismedov, Daniele

Abstract: The presentation of online content is routinely adapted to the smaller screens o ... Expand

Abstract: The presentation of online content is routinely adapted to the smaller screens of mobile devices by implementing an information architecture (IA) that hierarchically restructures the information being presented to users, in conjunction with layout and size adaptations. Despite the understanding that users of mobile devices are likely to experience lower usability and higher load without such adaptations, a recent trend is to offer these users the ability to opt out of content adaptation and revert to a desktop view. The prevailing justification for this trend is the existence of websites that fail to provide an optimal mobile experience. In this work, we show that a desktop view may benefit mobile users by increasing the accuracy of their decisions. Focusing on the difference between a desktop IA, where information is presented on a single page, and a mobile IA, where information is hierarchically distributed across pages, we hypothesize that mobile users exhibit lower decision accuracy when a mobile IA is implemented. We theoretically anchor this hypothesis in the effort-accuracy framework, which views decision behavior as contingent on the trade-off between effort and accuracy. This hypothesis is supported in two laboratory experiments in which participants are faced with the multiattribute choice task of making an online hotel reservation. The experiments also highlight a boundary condition for the negative effect of the mobile IA on decision accuracy, depending on whether the mobile IA is congruent with user preferences. The findings suggest that content adaptation on mobile devices deserves greater research attention, particularly from the perspective of adaptive decision behavior.History: Anandasivam Gopal, Senior Editor; Likoebe Maruping, Associate Editor.Funding: The authors thank the Israel Science Foundation [Grant 604/18] for providing funding in support of this research.Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1140. Collapse

Topics: mobile system information storage and retrieval system decision making website smartphone

Methods: experiment descriptive statistic regression analysis method survey statistical hypothesis test

Theories: theory of bounded rationality

Prior Experience of Managers and Maladaptive Responses to Performance Feedback: Evidence from Mutual Funds

2023 | Organization Science | Citations: 0

Authors: Gaba, Vibha; Lee, Sunkee; Meyer-Doyle, Philipp; Zhao-Ding, Amy

Abstract: In this study, we examine how the prior experiences of decision makers systemati ... Expand

Abstract: In this study, we examine how the prior experiences of decision makers systematically influence their assessment of and responses to negative performance feedback. We posit that, although greater and more specialized experiences enable managers to build relevant knowledge and expertise in specific domains, they also make them overconfident in their abilities and strategies. Such experience-induced overconfidence further leads to distortions in the performance assessment process, hindering a firm’s ability to recognize and respond to poor performance. We empirically test these arguments in the context of U.S. mutual fund managers making investment decisions in response to fund performance below aspirations. As hypothesized, we find that more experienced and more specialized fund managers change their investment decisions less when faced with negative performance feedback than managers who are less experienced and less specialized. In additional analyses, we further show that the lower responsiveness of more experienced (specialized) managers is associated with the fund’s lower future performance, supporting our proposed theoretical mechanism (overconfidence). This study augments existing performance feedback research by showing how decision makers’ prior experience can impede problem-solving behavior in organizations. It also contributes to the literature on human capital and organizational learning by documenting an unintended consequence of accumulated human capital on firm adaptive behavior. Funding: This work was supported by INSEAD research & development funds. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1605. Collapse

Topics: IT career organizational productivity human resource management unintended consequence problem solving

Methods: robustness check descriptive statistic theory development qualitative content analysis SEC EDGAR

Theories: theory of bounded rationality behavioral theory of the firm

Challenges in the Model Development Process: Discussions with Data Scientists

2023 | Communications of the Association for Information Systems | Citations: 0

Authors: Gerhart, Natalie; Torres, Russell; Giddens, Laurie

Abstract: Businesses are increasingly seeking out analytics to improve decision-making pr ... Expand

Abstract: Businesses are increasingly seeking out analytics to improve decision-making processes, although often with hesitations. Decision makers often do not have the sophisticated analytical skills needed to fully understand the analytics process. Contrastingly, data scientists may lack the business acumen needed to fully grasp the business context of the decision. In this research, we consider the perspective of the data scientist through a series of interviews to draw out challenges in the analytics process. We use principal-agent theory as a lens to shape our understanding of the conflict that arises due to goal misalignment and information asymmetry between the principal and agent. Findings are presented in the CRISP-DM process and a future research agenda is proposed. Collapse

Topics: decision making implicit knowledge data quality organizational impact organizational memory

Methods: Cross-Industry Standard Process for Data Mining qualitative interview theory development mathematical model literature study

Theories: agency theory lemon market theory theory of bounded rationality

Iterative Coordination and Innovation: Prioritizing Value over Novelty

2023 | Organization Science | Citations: 0

Authors: Ghosh, Sourobh; Wu, Andy

Abstract: An innovating organization faces the challenge of how to prioritize distinct goa ... Expand

Abstract: An innovating organization faces the challenge of how to prioritize distinct goals of novelty and value, both of which underlie innovation. Popular practitioner frameworks like Agile management suggest that organizations can adopt an iterative approach of frequent meetings to prioritize between these goals, a practice we refer to as iterative coordination. Despite iterative coordination’s widespread use in innovation management, its effects on novelty and value in innovation remain unknown. With the information technology firm Google, we embed a field experiment within a hackathon software development competition to identify the effect of iterative coordination on innovation. We find that iterative coordination causes firms to implicitly prioritize value in innovation: Although iteratively coordinating firms develop more valuable products, these products are simultaneously less novel. Furthermore, by tracking software code, we find that iteratively coordinating firms favor integration at the cost of knowledge-creating specialization. A follow-on laboratory study documents that increasing the frequency and opportunities to reprioritize goals in iterative coordination meetings reinforces value and integration, while reducing novelty and specialization. This article offers three key contributions: highlighting how processes to prioritize among multiple performance goals may implicitly favor certain outcomes; introducing a new empirical methodology of software code version tracking for measuring the innovation process; and leveraging the emergent phenomenon of hackathons to study new methods of organizing.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Funding: The authors gratefully acknowledge financial support from Google LLC, the Harvard Business School Division of Research and Faculty Development, and the National Science Foundation [Grant 1122374].Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1499. Collapse

Topics: innovation management Google+ productivity systems development application programming interface

Methods: experiment survey field experiment descriptive statistic laboratory experiment

Theories: theory of bounded rationality behavioral theory of the firm organizational theory

Machine economies

2023 | Electronic Markets | Citations: 0

Authors: Hartwich, Eduard; Rieger, Alexander; Sedlmeir, Johannes; Jurek, Dominik; Fridgen, Gilbert

Abstract: This fundamentals article discusses efficient machine economies in which non-hum ... Expand

Abstract: This fundamentals article discusses efficient machine economies in which non-human agents can autonomously exchange information and value. We first identify criteria for achieving Pareto efficiency in such economies by drawing on the Coase Theorem. We then translate these economic criteria to technical requirements before developing a framework that characterizes four types of machine economies. We discuss real-life examples for each type to highlight key challenges in achieving Pareto efficiency. In particular, we highlight that machine economies with human involvement in economic interactions and governance face significant challenges regarding perfect information, rationality, and transaction costs. Machine economies without human involvement, in turn, promise a high degree of Pareto efficiency, but there are still many open questions, particularly regarding machine-enforced governance. We conclude with opportunities for future research on the interactions and governance in machine economies. Collapse

Topics: anonymity smart contract public good

Theories: transaction cost economics theory of bounded rationality lemon market theory economic 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

The Impact of Human-Artificial Intelligence Partnerships on Organizational Learning

2023 | European Conference On Information Systems | Citations: 0

Authors: Hendriks, Patrick; Sturm, Timo; Olt, Christian; Buxmann, Peter

Abstract: To make sense of their increasingly digital and complex environments, organizat ... Expand

Abstract: To make sense of their increasingly digital and complex environments, organizations strive for a future in which machine learning (ML) systems join humans in collaborative learning partnerships to complement each other's learning capabilities. While these so-called artificial assistants enable their human partners (and vice versa) to gain insights about unique knowledge domains that would otherwise remain hidden from them, they may also disrupt and impede each other's learning. To explore the virtuous and vicious dynamics that affect organizational learning, we conduct a series of agent-based simulations of different learning modes between humans and artificial assistants in an organization. We find that aligning the learning of humans and artificial assistants and allowing them to influence each other's learning processes equally leads to the highest organizational performance. Collapse

Topics: organization learning organizational memory knowledge base human AI collaboration artificial intelligence

Methods: simulation agent based simulation

Theories: theory of bounded rationality

Numerological Heuristics and Credit Risk in Peer-to-Peer Lending

2023 | Information Systems Research | Citations: 0

Authors: Hu, Maggie Rong; Li, Xiaoyang; Shi, Yang; Zhang, Xiaoquan (Michael)

Abstract: Heuristics are mental shortcuts that have ubiquitous influences on decision maki ... Expand

Abstract: Heuristics are mental shortcuts that have ubiquitous influences on decision making. We investigate whether and how different heuristics have distinct effects in the context of peer-to-peer (P2P) lending. Drawing on theories on the roles that heuristics play in decision making, we conjecture that when borrowers use different heuristics based on distinct motives to set their loan amounts, their funding success and repayment performance also differ. Using detailed P2P lending data from a Chinese P2P lending platform, we examine two important numerological heuristics, the round-number heuristic and the lucky-number heuristic, which are observable in over 80% of the submitted loan amounts. We find that round-number loans are less likely to get funded and exhibit poor repayment performance after being funded, whereas lucky-number loans exhibit the opposite pattern. These findings, which we attribute to the different motives behind the borrowers’ heuristic choices, challenge the conventional understanding that generally treats all heuristics as behavioral biases. Our results are robust to various identification strategies, including coarsened exact matching and instrumental variable estimation. Our paper sheds new light on the heterogeneity of heuristics and their distinctive implications for the credit market. History: Sam Ransbotham, Senior Editor; Tianshu Sun, Associate Editor. Funding: This work was supported by the Research Grants Council, University Grants Committee [Grants GRF 14500521, GRF 14501320, GRF 165052947, TRS:T31-604/18-N]. Supplemental Material: The internet appendices are available at https://doi.org/10.1287/isre.2023.1202. Collapse

Topics: crowdsourcing internet technology peer-to-peer lending peer-to-peer model decision making

Methods: instrumental variables estimation machine learning Student's t-test parametric test survival analysis

Theories: theory of bounded rationality

Getting Trapped in Technical Debt: Sociotechnical Analysis of a Legacy System’s Replacement

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Rinta-Kahila, Tapani; Penttinen, Esko; Lyytinen, Kalle

Abstract: Organizations replace their legacy systems for technical, economic, and operatio ... Expand

Abstract: Organizations replace their legacy systems for technical, economic, and operational reasons. Replacement is a risky proposition, as high levels of technical and social inertia make these systems hard to withdraw. Failure to fully replace systems results in complex system architectures involving manifold hidden dependencies that carry technical debt. To understand how a process for replacing a complex legacy system unfolds and accumulates technical debt, we conducted an explanatory case study at a local manufacturing site that had struggled to replace its mission-critical legacy systems as part of the larger global company’s commercial-off-the-shelf (COTS) system implementation. We approach the replacement as a sociotechnical change and leverage the punctuated sociotechnical information system change model in combination with the design-moves framework to analyze how the site balanced creating digital options, countering social inertia, and managing (architectural) technical debt. The findings generalize to a two-level (local/global) system-dynamics model delineating how replacing a deeply entrenched mission-critical system generates positive and negative feedback loops within and between social and technical changes at local and global levels. The loops, unless addressed, accrue technical debt that hinders legacy system discontinuance and gradually locks the organization into a debt-constrained state. The model helps managers anticipate challenges that accompany replacing highly entrenched systems and formulate effective strategies to address them. Collapse

Topics: systems implementation enterprise resource planning IT governance enterprise architecture information system use

Methods: qualitative interview case study system dynamics triangulation archival research

Theories: socio technical theory theory of bounded rationality