The Influences of Public and Institutional Pressure on Firms’ Cybersecurity Disclosures

2022 | Journal of the Association for Information Systems | Citations: 0

Authors: D'Arcy, John; Basoglu, Asli

Abstract: Cybersecurity disclosures in reports filed with the US Securities and Exchange ... Expand

Abstract: Cybersecurity disclosures in reports filed with the US Securities and Exchange Commission (SEC) inform investors about firms' cybersecurity incidents, risks, and related risk management efforts. Firms have traditionally chosen to communicate such information on a quarterly or annual basis, if at all, and prior research on the topic has largely focused on regulatory factors as driving forces. In this paper, we focus on timely disclosures (via 8-K filings) and derive hypotheses regarding the influences of two alternate forms of pressure as drivers of cybersecurity disclosures-(1) public pressure following a firm's data breach and (2) pressure arising from the breaches of industry peers, which we cast as "institutional pressure." We also theorize on how the source of the breach (internal or external) influences these forms of pressure. Our results suggest that firms' cybersecurity disclosure practices are influenced by public pressure following a data breach and that this pressure is more acute for external breaches than for internal breaches. By contrast, breaches by industry peers, as a form of institutional pressure, appear to prompt fewer cybersecurity disclosures, except when the focal firm suffers its own external breach. From a theoretical perspective, our study supports a nuanced application of legitimacy theory in the cybersecurity disclosure context, especially in the midst of public and institutional pressure, such that the source of a data breach determines whether firms attempt to address the resultant legitimacy gap. From a practical perspective, our results may be viewed as alarming in that firms are not reacting to internal breaches with the same degree of communicative effort about cybersecurity as for external breaches, at least in terms of the timely disclosures we consider in this study. Our findings also point to certain levers that can promote timely cybersecurity disclosures, and thus have important policy implications. Collapse

Topics: IT security data breach website Google+ internet technology

Methods: theory development statistical hypothesis test instrumental variables estimation regression analysis method statistical power analysis

Theories: institutional theory institutional isomorphism theory

Mining Reusable Software Components from Object-Oriented Source Code using Discrete PSO and Modeling Them as Java Beans

2020 | Information Systems Frontiers | Citations: 0

Authors: Rathee, Amit; Chhabra, Jitender Kumar

Abstract: Object-based software development in the IT-industry during the last decade has ... Expand

Abstract: Object-based software development in the IT-industry during the last decade has focused on reusing the already developed elements. Current software development models and technologies promote software reuse by utilizing component-oriented programming. Component-oriented programming provides more effective reuse as compared to its object-oriented language counterpart. This is because a component provides more abstractness in terms of the functionality in contrast to the object-oriented software element (e.g. class/ interface). The component-based development is highly dependent on the availability of the component library that contains well-defined and already tested functionality in terms of the available components. However, the suitable availability of such component library is still a problem. The lack of a suitable component library is tackled either by designing new components from scratch or by identifying them from the existing software systems. These identified components must be transformed as per component models, such as a Java Bean, in order to increase software reuse and faster software development, and little research has been carried out in this direction. Although many approaches have been proposed to identify components from existing systems and build a component library. But, such approaches lack in transforming the identified components as per specifications of a component model. Further identification of reusable elements also needs to be more accurate and efficient. Accuracy is dependent on the structural and semantic properties of a component. A component can consist of a single or a group of individual elements of the software, and thus identifying components from a set of all elements becomes an exponentially growing problem. Such problems can be more efficiently solved using metaheuristic algorithms. Therefore, this paper targets identifying accurately the components from a singular existing software system and transform those identified components to the Java Bean component model standard. The component identification approach of this paper is based on clustering the underlying software system by utilizing a metaheuristic search-based PSO algorithm. The clusters are identified as a group containing 2/ 3/ 4 software elements. Moreover, the used fitness function is based on the structural (based on usage for member variables) and semantic relations belonging to a software. Since the PSO algorithm is generally applied to continuous problems, whereas our formulated component identification problem is discrete (due to the representation of particles) in nature. Therefore, we have also provided a mechanism through which the PSO algorithm is modified to become applicable to discrete problems. From the obtained clusters (components), the interfaces of the components are identified by identifying independent chains in call-graphs of the underlying components. Finally, these components are transformed as per the Java Bean component model specifications. The proposed approach is validated experimentally on 7 open-source object-oriented Java software systems and results are compared with competitive approaches. The obtained results confirm the correctness of the transformed component and hence their reusability. Collapse

Topics: Java source code open source system quality application programming interface

Methods: cluster analysis computational algorithm machine learning literature study experiment

An Architectural Design for Learning Analytics in Remote Education Environments

2018 | Americas Conference on Information Systems | Citations: 0

Authors: Verma, Sameer; Gros, Andreas; Dluhos, Martin

Abstract: Improving education through technology has grown steadily. It is an ongoing chal ... Expand

Abstract: Improving education through technology has grown steadily. It is an ongoing challenge to implement education technologies in remote environments. It is increasingly difficult to gain feedback from such remote environments as these tend to be disconnected from the Internet. In this paper, we examine a remote education environment implemented through the One Laptop per Child (OLPC) project. We design an architecture and develop a learning analytics platform that allows various stakeholders to gain feedback from education environments across connected, intermittent, and disconnected Internet infrastructures. Collapse

Topics: CouchDB laptop computer database system backup cloud computing

Methods: qualitative interview descriptive statistic

“Computing” Requirements for Open Source Software: A Distributed Cognitive Approach

2018 | Journal of the Association for Information Systems | Citations: 0

Authors: Xiao, Xuan; Lindberg, Aron; Hansen, Sean; Lyytinen, Kalle

Abstract: Most requirements engineering (RE) research has been conducted in the context of ... Expand

Abstract: Most requirements engineering (RE) research has been conducted in the context of structured and agile software development. Software, however, is increasingly developed in open source software (OSS) forms which have several unique characteristics. In this study, we approach OSS RE as a sociotechnical, distributed cognitive process where distributed actors “compute” requirements—i.e., transform requirements-related knowledge into forms that foster a shared understanding of what the software is going to do and how it can be implemented. Such computation takes place through social sharing of knowledge and the use of heterogeneous artifacts. To illustrate the value of this approach, we conduct a case study of a popular OSS project, Rubinius—a runtime environment for the Ruby programming language—and identify ways in which cognitive workload associated with RE becomes distributed socially, structurally, and temporally across actors and artifacts. We generalize our observations into an analytic framework of OSS RE, which delineates three stages of requirements computation: excavation, instantiation, and testing-in-the-wild. We show how the distributed, dynamic, and heterogeneous computational structure underlying OSS development builds an effective mechanism for managing requirements. Our study contributes to sorely needed theorizing of appropriate RE processes within highly distributed environments as it identifies and articulates several novel mechanisms that undergird cognitive processes associated with distributed forms of RE. Collapse

Topics: agile software development electronic mail blog open source systems development

Methods: qualitative interview archival research design artifact qualitative coding experiment

Theories: socio technical theory theory of distributed cognition

Adapting Carsharing Vehicle Relocation Strategies for Shared Autonomous Electric Vehicle Services

2017 | International Conference on Information Systems | Citations: 3

Authors: Brendel, Alfred Benedikt; Lichtenberg, Sascha; Nastjuk, Ilja; Kolbe, Lutz M.

Abstract: New mobility services based on the sharing economy are emerging. One prominent e ... Expand

Abstract: New mobility services based on the sharing economy are emerging. One prominent example is the emergence of shared vehicle services, which are seen as a sustainable mobility solution. However, the problem of insufficient vehicle distribution has stood as a barrier to growth in the vehicle sharing service economy. Given this, it is not surprising to find a constantly growing body of research on vehicle relocation in carsharing, resulting in new and improved vehicle relocation strategies and information system solutions. Collapse

Topics: ride sharing platform decision support system autonomous driving system Ruby Python

Methods: simulation design theory discrete event simulation literature study design artifact

Effects of Social Structures in Requirements Quality of Open Source Software Project Development

2017 | International Conference on Information Systems | Citations: 0

Authors: Gopal, Deepa; Lyytinen, Kalle

Abstract: There is a growing interest in the requirements engineering (RE) practices of op ... Expand

Abstract: There is a growing interest in the requirements engineering (RE) practices of open source software (OSS) projects that are starkly different from those in traditional software development contexts. OSS projects are viewed as self-organizing collaborative social networks wherein OSS RE is a socio-technical distributed cognitive activity. With OSS projects exhibiting diverse social structures, the effects of such variations on the RE quality is unknown. The current study aims to fill this gap via a qualitative comparative study of three OSS projects – RubyonRails, Django and Bootstrap. The initial analysis expose that OSS projects with a lower communication centrality produce more veracious and less vague requirements while projects with a higher ratio of core to periphery members are associated with lesser variance in requirements. A quantitative analysis of OSS projects housed in SourceForge repository is suggested as a future extension to test the resulting hypotheses proposed through this qualitative study. Collapse

Topics: systems development requirements analysis electronic mail social network Ruby

Methods: qualitative interview multiple case study case study triangulation literature study

Promoting the System Integration of Renewable Energies: Toward a Decision Support System for Incentivizing Spatially Diversified Deployment

2017 | Journal of Management Information Systems | Citations: 4

Authors: Piel, Jan-Hendrik; Hamann, Julian F.H.; Koukal, André; Breitner, Michael H.

Abstract: The system integration of intermittent renewable energies (RE) poses an importan ... Expand

Abstract: The system integration of intermittent renewable energies (RE) poses an important challenge in the transition toward sustainable energy systems. Their intermittency introduces variability into electricity generation, leading to high ancillary service costs and technical issues impairing grid stability and supply reliability. These issues can be mitigated through spatially diversified capacity deployment, as RE intermittency can be geographically smoothed over sufficiently large regions. Following a design science research approach, we develop a model for the quantification of location-based investment incentives in RE support mechanisms to foster spatially diversified capacity deployment. We evaluate the modeling approach in a simulation study with focus on diversifying wind energy deployment in Mexico under an idealized auction mechanism and demonstrate how location-based investment incentives reduce resource-dependent competition among projects. Our research contributes a nascent design theory that combines the kernel theories for identifying favorable spatial distributions of RE capacity with current policy designs to support capacity expansion management Collapse

Topics: database system grid computing decision making decision support system system integration

Methods: simulation design artifact kernel theory design theory design science

Exploring Emerging Hacker Assets and Key Hackers for Proactive Cyber Threat Intelligence

2017 | Journal of Management Information Systems | Citations: 67

Authors: Samtani, Sagar; Chinn, Ryan; Chen, Hsinchun; Nunamaker, Jay F.

Abstract: Cyber attacks cost the global economy approximately $445 billion per year. To mi ... Expand

Abstract: Cyber attacks cost the global economy approximately $445 billion per year. To mitigate attacks, many companies rely on cyber threat intelligence (CTI), or threat intelligence related to computers, networks, and information technology (IT). However, CTI traditionally analyzes attacks after they have already happened, resulting in reactive advice. While useful, researchers and practitioners have been seeking to develop proactive CTI by better understanding the threats present in hacker communities. This study contributes a novel CTI framework by leveraging an automated and principled web, data, and text mining approach to collect and analyze vast amounts of malicious hacker tools directly from large, international underground hacker communities. By using this framework, we identified many freely available malicious assets such as crypters, keyloggers, web, and database exploits. Some of these tools may have been the cause of recent breaches against organizations such as the Office of Personnel Management (OPM). The study contributes to our understanding and practice of the timely proactive identification of cyber threats. Collapse

Topics: source code IT security threat spyware social network database system

Methods: support vector machine social network analysis machine learning natural language processing latent dirichlet allocation

Reconstructing Open Source Software Ecosystems: Finding Structure in Digital Traces

2016 | International Conference on Information Systems | Citations: 10

Authors: Eck, Alexander; Uebernickel, Falk

Abstract: We report on the computational reconstruction of 273 open source software ecosys ... Expand

Abstract: We report on the computational reconstruction of 273 open source software ecosystems, consisting of 41,388 artifacts and couplings between them, extracted from digital traces of 34.4 million software artifacts. We argue that digital traces are a new kind of data source, and propose ‘exploratory data loops’ to exploit the benefits of digital trace data in early stages of a research program. We apply this schema to systematically assess data quality, inform sample selection, and detect patterns. Empirically, we show that highly distributed networks are unlikely to follow a hierarchically modular structure, despite popular belief. As is shown visually with two examples, very distinct structures can emerge from autonomous behavior. The results indicate that different, yet similarly effective, strategies may exist to organize for distributed innovation in digital ecosystems. The paper is concluded by outlining how follow-up work will harness the reconstructed ecosystems for detecting behavioral patterns in distributed networks. Collapse

Topics: open source innovation management data quality application programming interface digital ecosystem

Methods: digital trace data design artifact computational algorithm theory development descriptive statistic

Theories: co-evolution theory

Improving Case Management via Statistical Text Mining in a Foster Care Organization

2014 | DESRIST | Citations: 0

Authors: Castillo, Alfred; Castellanos, Arturo; Tremblay, Monica Chiarini

Abstract: Every year more than 800,000 children in the U.S. spend time in foster care with ... Expand

Abstract: Every year more than 800,000 children in the U.S. spend time in foster care with 35% being on psychotropic medication. An increasing ratio of foster care children per case worker makes it challenging to balance their multiple roles during the lifecycle of a case. Although there are review boards for identifying cases that require special attention, scanning through all the unstructured data is time-consuming and is further complicated by poorly written, or incomplete, case note entries from the overwhelmed case workers. As part of a larger comprehensive study of a technology-centric foster care organization, we investigate a challenging nationwide problem of over-prescription of psychotropic drugs, which can lead to unnecessary deaths. We demonstrate how text mining techniques can significantly reduce the administrative requirements for auditing case notes by providing a smaller sample that is manageable yet be sensitive to exclusion of children showing evidence of psychotropic drug use. This should significantly lighten the load for case managers as they investigate possible cases. Collapse

Topics: logistics management user interface website Ruby structured query language

Methods: machine learning computational algorithm natural language processing naïve bayes Cross-Industry Standard Process for Data Mining