What do growing early-stage digital start-ups look like? A mixed-methods approach

2023 | International Journal of Information Management | Citations: 0

Authors: Griva, Anastasia; Kotsopoulos, Dimosthenis; Karagiannaki, Angeliki; Zamani, Efpraxia D.

Abstract: Digital entrepreneurship is one of the most important and impactful forms of ent ... Expand

Abstract: Digital entrepreneurship is one of the most important and impactful forms of entrepreneurship. However, the majority of digital start-ups fail to scale, despite their potential to achieve growth. Moreover, what constitutes growth is significantly different for start-ups as compared with established firms: they have limited financial performance, and their growth cannot be accurately measured by metrics such as customers, revenues, profits, and turnover at the early stages of the new venture creation process or before the start-up has reached sus­ tainability. Therefore, the first objective of this research is to contribute to the definition of growth by examining less tangible dimensions of growth. Moreover, the second objective is to identify the characteristics of early-stage digital start-ups experiencing growth. Based on a mixed-methods approach, which combines an adapted Delphi study, a questionnaire-based survey, and a comparative case study, our results suggest that growing digital startups exhibit a set of characteristics that include: an agile culture combining clan with adhocracy; the ability to nurture their absorptive, innovative, and adaptive capabilities effectively; and a human capital with adequate entrepreneurial skills, emotional attachment to and fitness with the start-up. Collapse

Topics: digital entrepreneurship human resource management entrepreneurship innovation management absorptive capacity

Methods: survey delphi study mixed method qualitative interview case study

Theories: dynamic capabilities theory

Enabling the Evaluation of Production Scheduling Algorithms in Complex Production Environments Using Individually Deployable Scheduling Services

2023 | DESRIST | Citations: 0

Authors: Groth, Michael; Dippel, Alexander; Schumann, Matthias

Abstract: Changes in customer demands and technological advances increase the complexity o ... Expand

Abstract: Changes in customer demands and technological advances increase the complexity of production scheduling. Hence, current production scheduling algorithms are not sufficiently good. Additionally, advances in the research of Machine Learning algorithms drive the development of new scheduling algorithms. Each algorithm’s quality is problem-dependent, making it challenging to find the best algorithm for a given production scenario. Benchmark problems only provide guidance as they do not reflect real-world situations. To address this issue, in this article, we develop the software artifact Simfia that allows researchers and practitioners to evaluate production scheduling algorithms in highly customizable experiments. To create the solution, we follow a design science research approach. We identify 30 functional requirements, develop the solution prototypically and demonstrate it in an exemplary production scenario. The artifact is developed in a service-oriented architecture where scheduling algorithms are provided as individually deployable scheduling services that Simfia manages. This solution enables researchers and practitioners to experiment with production scheduling algorithms in highly configurable production scenarios. Collapse

Topics: service oriented architecture enterprise architecture usability user interface data management

Methods: computational algorithm experiment design artifact laboratory experiment design science

Innovative theory in the digital age: Clarifying our positions

2023 | Journal of Information Technology | Citations: 0

Authors: Grover, Varun; Lyytinen, Kalle

Abstract: In this paper, we respond to Baiyere, Berente and Avital (2023) who misinterpret ... Expand

Abstract: In this paper, we respond to Baiyere, Berente and Avital (2023) who misinterpret portions of our article. In this essay, we engage in a dialog with these authors and clarify our positions and even reinforce some points the authors themselves are making. Collapse

Topics: big data media richness communication service infrastructure reference discipline IS discipline

Methods: theory development conceptual analysis synthesis

Theories: media synchronicity theory media richness theory general systems theory socio technical theory transaction cost economics

Not only data: The necessity of abstract thinking to make sense of digital phenomena

2023 | Journal of Information Technology | Citations: 1

Authors: Grover, Varun; Lyytinen, Kalle

Abstract: ... Expand

Abstract: Collapse

Topics: information system use

Methods: theory development digital trace data

Theories: organizational theory

The Pursuit of Innovative Theory in the Digital Age

2023 | Journal of Information Technology | Citations: 1

Authors: Grover, Varun; Lyytinen, Kalle

Abstract: Grover & Lyytinen (2015) urged to reassess the Information System (IS) field?s e ... Expand

Abstract: Grover & Lyytinen (2015) urged to reassess the Information System (IS) field?s exclusive dependence on reference theories and to engage more in blue-ocean theorizing. From its inception, such need has been latent in the field, because it deals with novel, fast changing, complex, and systemic phenomena that is hard to account with received theory. We note in this essay that the need for innovative theorizing is heightened given the unprecedented, pervasive digitalization of contemporary society, accelerated by ongoing COVID-19 pandemic. In this essay, we scrutinize further the idea of blue-ocean theorizing and review the characteristics, impediments, and merits of developing innovative theory. We define endeavors toward such theory as collectively endorsed cognitive processes which increase variance and novelty of theoretical accounts of IS phenomena. These push to deviate from the field?s established theoretical (canonical) core by relaxing six assumptions that guide dominant, legitimate forms of the field?s theorizing. We identify and review institutional barriers that curb the development of innovative theory. In conclusion, we offer guidelines for how the field and its stakeholders can productively engage in developing and evaluating innovative theory. Collapse

Topics: pandemic reference discipline mobile application outsourcing online review

Methods: theory development design artifact literature study literature sample

Theories: transaction cost economics information systems theory

AI UNCERTAINTY IN EXPERT DECISION-MAKING: A QUALITATIVE EVIDENCE SYNTHESIS

2023 | European Conference On Information Systems | Citations: 0

Authors: Grundstrom, Casandra; Mohanty, Pooja; Parmiggiani, Elena

Abstract: As Artificial Intelligence (AI) is becoming more prevalent in everyday work set ... Expand

Abstract: As Artificial Intelligence (AI) is becoming more prevalent in everyday work settings, the Information Systems (IS) discipline is perfectly poised to study the sociotechnical repercussions of AI supported decision-making part of expert's knowledge work. As expert know-how is tacit and socially situated, there are difficulties in capturing the nuances of the emerging human-machine collaborations. In this article, we review how epistemic uncertainty is evident in experts' decision-making practices when using AI tools. Building on rich primary studies, a qualitative evidence synthesis (QES) approach was used to synthesize relevant literature on this topic. Our findings unravel sources of expert uncertainty which point to strategies experts use to cope with uncertainty, and what attitudes experts have towards uncertainty when making complex decisions with AI-tools. Collapse

Topics: artificial intelligence decision making decision support knowledge sharing implicit knowledge

Methods: literature sample synthesis computational algorithm structured literature research literature filtering

A Configurational Set-Theoretic Approach to an Innovation Capability Maturity Model

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Gräubig, Dix; Bley, Katja

Abstract: Constantly evolving economic demands caused by phenomena such as digital transf ... Expand

Abstract: Constantly evolving economic demands caused by phenomena such as digital transformation necessitate businesses and their underlying models to adapt. One possible solution for enhancing innovation potential and increasing revenue is implementing an innovation capability maturity model. This research replicates an existing maturity model development approach, which accounts for the unique characteristics of a class of companies based on their size and sector. Thus, by using a data-driven method, we provide an innovation capability maturity model for small industrial companies. We identified 21 combinations of factors that can affect innovation capability maturity, grouped into a knowledge and organizational dimension. Using a set-theoretic approach, we identified configurations of these factors that lead to low, medium, and high levels of innovation capability maturity. Based on these findings, we support an empirically driven, set-theoretic approach for developing a maturity model that can be used for higher applicability and representativity in individual classes of companies. Collapse

Topics: innovation management research and development fuzzy logic business model business process management

Methods: structured literature research descriptive statistic design science longitudinal research maturity model

Theories: fuzzy set theory knowledge based theory of the firm balance theory

Introduction to the Minitrack on Software Development for Mobile Devices, the Internet-of-Things, and Cyber-Physical Systems

2023 | HICSS | Citations: 0

Authors: Grønli, Tor-Morten; Kaindl, Hermann; Majchrzak, Tim A.

Abstract: Applications for mobile devices (apps) have facilitated the success of smartpho ... Expand

Abstract: Applications for mobile devices (apps) have facilitated the success of smartphones and tablets. By using apps, the multi-purpose hardware of modern devices can be utilized to the full extent. Despite much progress in development methods, software development kits, and frameworks, app development poses many challenges. This is even more so for novel mobile devices such as wearables and for the hardware that constitutes the Internet-of-Things (IoT) and Cyber-Physical Systems (CPS). Compatibility, performance, battery-saving, and security and safety are only some of the issues that are mainly driven by the quality of the used software. A satisfying level of this quality in many cases is very hard to achieve and proper techniques for testing and formal verification are needed.Experiences and methods from classical software development can only be utilized to some degree. Moreover, the inherent challenges of the respective new devices ask for novel solutions. The challenges sketched above are reinforced by the conditions that development activities meet. Typical particularities include the need for multi-platform development, device fragmentation, context-sensitivity, low computational power, little memory, energy conservation requirements, and the heterogeneity of users. With the emergence of multi-platform and multi-device, the new golden standard are applications not only across software ecosystems, but across hardware platforms such as laptop, mobile, tablets, embedded devices, sensors, and wearables. Therefore, new threads of research are needed to tackle these issues and to pave the way for improved software development, better business producibility and improved user experience (UX). Collapse

Topics: cyber-physical system

Methods: meta analysis

Artificial Intelligence, Technostress and Work Outcomes in Healthcare: A Power Perspective on AI Characteristics

2023 | International Conference on Information Systems | Citations: 0

Authors: Grüning, Maximilian; Henkenjohann, Richard; Santos, Daniel Pinto dos; Trenz, Manuel

Abstract: Artificial intelligence (AI) has emerged as a powerful tool for complex decisio ... Expand

Abstract: Artificial intelligence (AI) has emerged as a powerful tool for complex decision-making. However, little is known about how AI-based systems should be integrated into clinical practice to improve patient and provider outcomes. We argue that AI-based systems are no longer passive tools and can assume certain responsibilities for tasks. A novel aspect of our study is the exploration of the power relationship between AI and physicians, which can significantly impact medical care. Therefore, we aim to shed light on how configurations of power in AI interactions influence technostress and work outcomes. We outline a lab-in-the-field experiment on diagnosis and reporting by physicians using AI. Our study aims to uncover (1) the differential effects of power configurations in AI on physicians' positive and negative technostress levels, and (2) their psychological and behavioral outcomes. We aim to contribute to information systems research and practice by highlighting the power implications of AI. Collapse

Topics: artificial intelligence technostress decision making explainable artificial intelligence health information system

Methods: experiment field experiment survey statistical hypothesis test partial least squares path modeling

Disentangling the Tension Between Automation and Augmentation with Artificial Intelligence in Healthcare

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Grüning, Maximilian; Trenz, Manuel; Santos, Daniel Pinto dos

Abstract: Artificial Intelligence (AI) has the potential to be a powerful tool for the fu ... Expand

Abstract: Artificial Intelligence (AI) has the potential to be a powerful tool for the future of medical professionals. However, we recognize a tension between AI independence (automation) and human involvement (augmentation) in medical decision-making. To resolve this tension, we conducted a systematic literature review to gain an overview of the current knowledge of AI in healthcare. In this systematic literature review, we search and analyze the leading journals in management and information systems for a period from 2012 to 2022. We find that several tasks related to diagnosis, treatment, or administrative work can be effectively automated or augmented with AI. We contribute to information systems research by highlighting possible scenarios for the effective use of AI in medical decision-making. Understanding and mitigating these tensions are particularly important for medical decision-makers, regulators, and managers who are struggling with guidelines for the appropriate use of AI and certification of accountability. Collapse

Topics: artificial intelligence decision making robotic expert system robotic process automation

Methods: literature sample structured literature research literature study artificial neural network business process modeling