Business-IT alignment as a coevolution process: An empirical study

2023 | Journal of Strategic Information Systems | Citations: 0

Authors: Amarilli, Fabrizio; Van Den Hooff, Bart; Van Vliet, Mario

Abstract: In this paper, we provide a detailed insight into the complex coevolution dynami ... Expand

Abstract: In this paper, we provide a detailed insight into the complex coevolution dynamics that shape the alignment process by analyzing how different mechanisms and factors are mutually related in complex networks of feedback loops. We combine insights from the literature on alignment as a (coevolution) process with literature on alignment as a state to identify the different components of the organization’s socio-technical system that influence alignment, the relationships between these components, and the role that different factors play. In our empirical analysis (based multiple case studies) we then focus on the actual interplay between relevant factors. Using a causal loop diagramming approach - based on system dynamics – we analyze how these factors mutually influence each other through various feedback loops and thus shape the alignment process. We extend previous literature on the alignment process by identifying the way that the complex interplay between different factors shapes this process. By identifying the feedback loops between relevant factors, we also provide more insight into the complex bottom-up and top-down dynamics that shape the process, and that provide explanations for why this process is charac­ terized by transitions between alignment and misalignment. For practice, our paper provides a deeper understanding of the alignment process, which is a precondition for improving alignment practices in organisations. Collapse

Topics: Chief Information Officer IT alignment strategic management IT project enterprise information system

Methods: qualitative interview case study multiple case study theoretical contribution system dynamics

Theories: co-evolution theory socio technical theory complex adaptive system

Design of a Novel Information System for Semi-automated Management of Cybersecurity in Industrial Control Systems

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Ameri, Kimia; Hempel, Michael; Sharif, Hamid; Lopez, Juan; Perumalla, Kalyan

Abstract: There is an urgent need in many critical infrastructure sectors, including the e ... Expand

Abstract: There is an urgent need in many critical infrastructure sectors, including the energy sector, for attaining detailed insights into cybersecurity features and compliance with cybersecurity requirements related to their Operational Technology (OT) deployments. Frequent feature changes of OT devices interfere with this need, posing a great risk to customers. One effective way to address this challenge is via a semi-automated cyber-physical security assurance approach, which enables verification and validation of the OT device cybersecurity claims against actual capabilities, both pre- and post-deployment. To realize this approach, this article presents new methodology and algorithms to automatically identify cybersecurity-related claims expressed in natural language form in ICS device documents. We developed an identification process that employs natural language processing (NLP) techniques with the goal of semi-automated vetting of detected claims against their device implementation. We also present our novel NLP components for verifying feature claims against relevant cybersecurity requirements. The verification pipeline includes components such as automated vendor identification, device document curation, feature claim identification utilizing sentiment analysis for conflict resolution, and reporting of features that are claimed to be supported or indicated as unsupported. Our novel matching engine represents the first automated information system available in the cybersecurity domain that directly aids the generation of ICS compliance reports. Collapse

Topics: IT security database system website Python electronic authentication

Methods: computational algorithm sentiment analysis natural language processing BERT language model

Strategic Investments for Platform Launch and Ecosystem Growth: A Dynamic Analysis

2023 | Journal of Management Information Systems | Citations: 0

Authors: Anderson Jr., Edward G.; Parker, Geoffrey G.; Tan, Burcu

Abstract: Multi-sided platforms must make decisions on both pricing and engineering invest ... Expand

Abstract: Multi-sided platforms must make decisions on both pricing and engineering investment and must continually adjust them as the platform scales over its lifecycle. Engineering investments can be allocated to features that improve a platform's standalone value, social features to take advantage of same-side network effects, or integration tools and boundary resources to facilitate third-party content creation. Guidance in the academic or practitioner literature is not granular. Moreover, relevant normative economic models that consider externalities are rarely dynamic. Hence, there is a gap in knowledge about how to best balance tradeoffs between different strategic decisions throughout the entire platform lifecycle. To begin to address this gap, we explore normative strategies for coordinating pricing and engineering investment decisions on a continuous basis under different ecosystem conditions. We build a simulation model informed by economics and marketing theory and perform extensive sensitivity analyses on key parameters in different ecosystem scenarios over a multi-period lifecycle. We find that pricing and investment strategies must continuously change to perform optimally. In particular, strategies that are most effective at launch often differ from those that are most effective during scaling as well as those most effective at maturity. We also find that the optimal strategy depends strongly on the monetization model and market aversion to price changes. Lastly, we specifically examine four different industry segments: mobile platforms, social media, the sharing economy, and business-to-business. The results provide evidence that the trajectory of platform pricing and investment strategies should greatly differ depending on industrial context. Collapse

Topics: price management digital platform social media decision making business-to-business

Methods: simulation sensitivity analysis system dynamics optimization model conjoint analysis

Theories: control theory marketing theory

Maximal Mixed-Drove Co-occurrence Patterns

2023 | Information Systems Frontiers | Citations: 0

Authors: Andrzejewski, Witold; Boinski, Pawel

Abstract: One of the interesting types of spatio-temporal patterns is the Mixed-Drove Co-o ... Expand

Abstract: One of the interesting types of spatio-temporal patterns is the Mixed-Drove Co-occurrence Pattern (MDCOP), which represents types of objects frequently located together in both space and time. To discover such patterns, methods based on the well-known Apriori strategy are widely used. They involve determining multi-element MDCOPs by building them up iteratively starting with the two-element patterns and then successively adding another element in each iteration. This approach can be very costly, particularly when the data is dense enough to form patterns of significant size. In this paper, we introduce a definition of a new pattern type called a Maximal Mixed-Drove Co-occurrence Pattern. We also propose a new algorithm MAXMDCOP-Miner, which resigns from popular Apriori strategy of generating candidates and, therefore, can discover long pattern without processing all their subsets. Experiments performed on synthetic and real datasets show that MAXMDCOP-Miner has high performance, in particular for dense datasets or tasks with low user-defined thresholds of spatial or time prevalence. Collapse

Methods: computational algorithm experiment machine learning literature study association rule learning

From Groups to Communities: A Resource Mobilization Theory Perspective on the Emergence of Communities

2023 | Information Systems Frontiers | Citations: 1

Authors: Angelopoulos, Spyros; Canhilal, Kubra S.; Hawkins, Matthew A.

Abstract: Groups and communities have been key topics in the information systems (IS) rese ... Expand

Abstract: Groups and communities have been key topics in the information systems (IS) research agenda. While communities are assumed to emerge at the intersection of overlapping groups and their practices, prior research has mainly focused on their dynamics and evolution. This has resulted to limited empirical support regarding the emergence of communities. We address that lacuna by tracing the emergence of communities through the prism of resource mobilization theory. In doing so, we make use of a unique longitudinal dataset and incorporate Topic Modelling, Bipartite Network Analysis, and Community Detection. We show that new communities are formed at the intersection of overlapping groups and practices. In addition, we contribute to the IS literature by demonstrating that their emergence occurs due to resource mobilization that gives rise to a shared mindset. We also reveal that multiple resources are incorporated into the practices of an emerging community. By combining large datasets and innovative computational approaches, we help IS theory and practice to move away from traditional "what" questions towards the more insightful "how" ones. We discuss the theoretical and practical implications of our work and delineate an agenda for future research on the topic. Collapse

Topics: accounting identity theft database system

Methods: longitudinal research theoretical contribution theory development network analysis topic model

Theories: information systems theory

“Collaborating” with AI: Taking a System View to Explore the Future of Work

2023 | Organization Science | Citations: 0

Authors: Anthony, Callen; Bechky, Beth A.; Fayard, Anne-Laure

Abstract: In the wake of media hype about artificial intelligence (AI)/human collaboration ... Expand

Abstract: In the wake of media hype about artificial intelligence (AI)/human collaboration, organizations are investing considerable resources into developing and using AI. In this paper, we draw on theories of technology in organizations to frame new directions for the study of what it means to work “with” AI. Drawing on prior literature, we consider how interactions between users and AI might unfold through theoretical lenses which cast technology as a tool and as a medium. Reflecting on how AI technologies diverge from technologies studied in the past, we propose a new perspective, which considers technology as a counterpart in a system of work that includes its design, implementation, and use. This perspective encourages developing a grounded understanding of how AI intersects with work, and therefore ethnography, building on thick descriptions, is an apt approach. We argue that relational ethnographic approaches can assist organization theorists in navigating the methodological challenges of taking a counterpart perspective and propose several strategies for future research. Collapse

Topics: artificial intelligence spreadsheet human AI collaboration human computer interaction information system use

Methods: ethnography computational algorithm qualitative interview experiment theory development

Theories: theory of distributed cognition actor network theory

TEA-IS: A hybrid DEA-TOPSIS approach for assessing performance and synergy in Chinese health care

2023 | Decision Support Systems | Citations: 0

Authors: Antunes, Jorge; Hadi-Vencheh, Abdollah; Jamshidi, Ali; Tan, Yong; Wanke, Peter

Abstract: This paper presents an assessment of the Chinese healthcare system in 31 provinc ... Expand

Abstract: This paper presents an assessment of the Chinese healthcare system in 31 provinces for a 10-year period in light of relevant physical and human resource variables. First, a novel TEA-IS (Trigonometric Envelopment Analysis for Ideal Solutions) model is developed to assess healthcare efficiency at the province level. Machine learning methods are also employed to predict high-low performance and the synergistic Chinese healthcare province in terms of contextual variables. The results indicate that synergy has played a pivotal role in the Chinese healthcare systems, not only by triggering higher performance levels due to the progressive adoption of best practices over the course of time, but also by being closely related to different socioeconomic and demographic variables, such as the illiteracy rate. It is possible to claim that healthcare performance has remained stable in China over the past two decades, performance and synergy at the province level are still heterogeneous. Collapse

Topics: health information system IT productivity human resource management service quality productivity

Methods: TOPSIS trade-off analysis method machine learning artificial neural network literature study

Detecting Privacy Threats with Machine Learning: A Design Framework for Identifying Side-Channel Risks of Illegitimate User Profiling

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Anwar, Raja Hasnain; Zou, Yi (Zoe); Raza, Muhammad Taqi

Abstract: Privacy leakage has become prevalent and severe with the increasing adoption of ... Expand

Abstract: Privacy leakage has become prevalent and severe with the increasing adoption of the internet of things (IoT), artificial intelligence (AI), and blockchain technologies. Such data-intensive systems are vulnerable to side-channel attacks in which hackers can extract sensitive information from a digital device without actively manipulating the target system. Nevertheless, there is a scarcity of IS research on how businesses can effectively detect and safeguard against side-channel attacks. This study adopts the design science paradigm and lays the groundwork for systematic inquiry into the assessment of privacy risks related to side-channels. In this paper, we a) highlight the privacy threats posed by side-channel attacks, b) propose a machine learning-driven design framework to identify side-channel privacy risks, and c) contribute to the literature on privacy analytics using machine learning techniques. We demonstrate a use case of the proposed framework with a text classification model that uses keystroke timings as side-channel. Collapse

Topics: privacy IT security data breach information system use

Methods: design framework machine learning design science time series analysis longitudinal research

Digitalization and Early Internationalization- Systematic Literature Review Analyses

2023 | HICSS | Citations: 0

Authors: Appiah, Emmanuel; Gabrielsson, Peter

Abstract: Substantial anecdotal evidence has been garnered to make it uncontentious to con ... Expand

Abstract: Substantial anecdotal evidence has been garnered to make it uncontentious to concede to studies that stress on the influence of digital technology on early internationalization of firms. Having an interest to study how studies on this phenomenon has progressed overtime. The present paper systematically evaluates internationalization literature in which issues of digitalization feature as a component underlying the causes, processes, and outcomes of early internationalization. This enables us to outline the development of major research areas in terms of themes, theoretical and methodological approaches. We contribute by proposing several future research directions. Collapse

Topics: information technology capability internet technology electronic business mobile system marketing management

Methods: literature sample structured literature research theory development cross sectional research literature study

ICT-Based Country-Level Determinants of Social Media Diffusion

2023 | Information Systems Frontiers | Citations: 0

Authors: Arayankalam, Jithesh; Krishnan, Satish

Abstract: There is a broad consensus that social media platforms have become critical tool ... Expand

Abstract: There is a broad consensus that social media platforms have become critical tools for policymakers in achieving various policy objectives in a country. Therefore, an in-depth understanding of the ICT-based country-level determinants of social media diffusion has become necessary. To this end, we propose a government-people-technology (GTP) framework for categorizing the ICT-based country-level determinants of social media diffusion into three dimensions. Using this framework and utilizing archival data from 107 countries, we examine the roles of ICT in the government's vision, ICT law maturity, Internet bandwidth, ICT cost, ICT skill, and capacity to own ICT in influencing social media diffusion. A quantile panel data regression results reveal that ICT in the government's vision, ICT law maturity, Internet bandwidth, and capacity to own ICT were positively associated with social media diffusion. In contrast, ICT cost was negatively associated with it. Thus, by offering a new framework, we contribute to the technology diffusion literature by emphasizing the role of government, people, and supportive technologies in driving social media diffusion at the country level. Collapse

Topics: social media IT investment internet technology IT skill technology diffusion

Methods: longitudinal research regression analysis method post-hoc analysis cross sectional research archival research

Theories: theory of everything