Knowledge Management Systems and Artificial Intelligence Adoption for Increasing Business Sustainability

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Al Halbusi, Hussam; Hassani, Abdeslam; Mosconi, Elaine; Bayiz, Ahmad

Abstract: Sustainable business success is essential for achieving performance in a market ... Expand

Abstract: Sustainable business success is essential for achieving performance in a market in the contemporary technology age. Worldwide, businesses should overcome a number of challenges by using an innovative practices and technologies to achieve long-term business sustainability. This study intended to inspect the relationship between knowledge management systems (KMS) and sustainable business, and to examine the moderating role of artificial intelligence (AI) adoption in the relationship. To achieve this objective, we collect data from Iraqi firms. Using structural equation modelling, the finding of this study show that knowledge management systems significantly increased sustainable business. In addition, AI adoption moderates the relationship between KMS and sustainable business. Hence, this research makes significant implications to literature and policymakers regarding applying and understanding knowledge management systems and AI adoption to enhance sustainable business. Collapse

Topics: artificial intelligence knowledge management system information technology infrastructure computer supported cooperative work technology adoption

Methods: survey partial least squares path modeling structural equation modeling partial least squares regression statistical hypothesis test

From transformation to normalisation: An exploratory study of a large-scale agile transformation

2023 | Journal of Information Technology | Citations: 0

Authors: Carroll, Noel; Conboy, Kieran; Wang, Xiaofeng

Abstract: Following the highly pervasive and effective use of agile methods at the team le ... Expand

Abstract: Following the highly pervasive and effective use of agile methods at the team level, many software organisations now wish to replicate this success at the organisational level, adopting large-scale agile methods. However, an analysis of extant literature reveals (i) a lack of theoretically grounded studies of large-scale agile transformations; (ii) weak assumptions underpinning those that do exist; and (iii) an overly simplistic and often problematic over-reliance on simple adherence to agile methods. In addition, there is a lack of insights on why large-scale agile transformations fail. To explore this, we apply normalisation process theory (NPT) to examine key challenges in normalising (i.e. the process of embedding and sustaining) large-scale agile methods. We present an in-depth case study of large-scale agile transformation and demonstrate how failing to normalise a large-scale agile method can unravel an organisation’s transformation efforts. There are four key contributions from this research. First, this study shows that the standard focus on initial adoption is one of the main reasons for the widespread failure of digital transformations and in this case a large-scale agile transformation. Second, this is the first study to introduce and empirically apply NPT to information system development (ISD) as an illustrative guide for those across information systems field to follow. Third, we present key recommendations based on NPT to guide researchers and practitioners on the normalisation of large-scale transformations. Fourth, we present an agenda for future research on large-scale agile transformations. Collapse

Topics: Spotify digital service agile software development sensemaking digital transformation

Methods: case study design methodology qualitative interview qualitative coding literature study

Theories: information systems theory sociological theory dynamic capabilities theory

Automated Deductive Content Analysis of Text: A Deep Contrastive and Active Learning Based Approach

2023 | International Conference on Information Systems | Citations: 0

Authors: De Oliveira Silveira, Alysson; Ray, Arindam; Ebrahimi, Mohammadreza; Bhattacherjee, Anol

Abstract: Content analysis traditionally involves human coders manually combing through t ... Expand

Abstract: Content analysis traditionally involves human coders manually combing through text documents to search for relevant concepts and categories. However, this approach is time-intensive and not scalable, particularly for secondary data like social media content, news articles, or corporate reports. To address this problem, the paper presents an automated framework called Automated Deductive Content Analysis of Text (ADCAT) that uses deep learning-based semantic techniques, an ontology of validated construct measures, a large language model, human-in-the-loop disambiguation, and a novel augmentation-based weighted contrastive learning approach for improved language representations, to build a scalable approach for deductive content analysis. We demonstrate the effectiveness of the proposed approach to identify firm innovation strategies from their 10-K reports to obtain inferences reasonably close to human coding. Collapse

Topics: knowledge representation human in the loop human computer interaction innovation management organizational innovation

Methods: ontological modelling machine learning language model large language model qualitative content analysis

Bridging the Gap: Evidence from the Return Migration of African Scientists

2023 | Organization Science | Citations: 0

Authors: Fry, Caroline Viola

Abstract: Although prior research has highlighted the benefits that accrue to brokers in i ... Expand

Abstract: Although prior research has highlighted the benefits that accrue to brokers in innovation networks, much less attention is devoted to understanding who benefits from associating with a broker. This study focuses on the impact of associating with a specific kind of broker—a core/periphery bridge—that is, one that spans central and peripheral actors. I argue that actors associated with a core/periphery bridge benefit more when they have no central connection, or are outsiders in the network, due to their greater need for sponsorship from the broker. I explore this idea in the context of the return migration of American-trained scientists to African institutions, who span the core and the periphery of the global scientific network. I evaluate the impact of their return on the publication outcomes of nonmigrant scientists based in African institutions and find that following the arrival of a returnee in their institution, the nonmigrants who are not already connected to scientists in top global institutions have a greater publication output through improved access to central knowledge and connections. The findings contribute to a better understanding of how brokers can influence innovation systems more broadly. Supplemental Material: The online appendices available at https://doi.org/10.1287/orsc.2022.1580. Collapse

Topics: IT career social capital accounting anonymity interorganizational relationship

Methods: longitudinal research robustness check descriptive statistic experimental group regression analysis method

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

Digital nudging for technical debt management at Credit Suisse

2023 | European Journal of Information Systems | Citations: 0

Authors: Haki, Kazem; Rieder, Annamina; Buchmann, Lorena; W.Schneider, Alexander

Abstract: Technical debt (TD) is a technical compromise wherein the ability to maintain in ... Expand

Abstract: Technical debt (TD) is a technical compromise wherein the ability to maintain information technology (IT) applications over the long term is sacrificed for short-term goals. TD occurs when software development teams undergo constant pressure to release applications swiftly, on a tight schedule. The accumulation of TD, which often leads to a significant cost surplus, presents a ubiquitous challenge in technology-driven organisations. To keep TD levels under control, many organisations implement top-down mechanisms that impose enterprise-wide principles on software development teams. This clinical research presents a complementary but distinct approach to managing TD. A digital nudge was introduced at Credit Suisse, a global financial services company, to help raise awareness and understanding, and stimulate actions related to TD decision-making in software development teams. This paper reports on the nudge’s clinical design, implementation, impact, and evaluation. As the nudge was effective in reducing TD in IT applications after one year of use, we demonstrate that digital nudges are viable means for guiding collective decisions in complex decision environments like that of TD management. Our findings have several implications for research and practice. Collapse

Topics: systems development decision making software developer IT manager agile software development

Methods: survey qualitative interview focus group personal interview design methodology

Theories: boundary objects theory nudge theory

MaCuDE IS Task Force Phase II Report: Views of Industry Leaders on Big Data Analytics and AI

2023 | Communications of the Association for Information Systems | Citations: 2

Authors: Lyytinen, Kalle; Topi, Heikki; Tang, Jing

Abstract: This paper represents the Phase II report of the Management Curriculum for the ... Expand

Abstract: This paper represents the Phase II report of the Management Curriculum for the Digital Era (MaCuDE) disciplinary task force on information systems (IS). Aligned with the current work of the AIS (Association for Information Systems) and ACM (Association for Computing Machinery), we focus on the current and future industry driven educational needs and requirements posed by big data analytics (BDA), artificial intelligence (AI), machine learning (ML), and related innovations. In this report, we probe and report on the views of industry leaders regarding BDA/AI education needs. We conducted 18 rich semi-structured interviews with a representative sample of industry leaders situated around key changes and issues related to workforce demands in digital transformation and associated educational needs. We performed a grounded theory based analysis of key themes in reported education needs. We note the shifting meaning of AI and BDA phenomena and identify three main organizational level needs for the digital eracapability improvement and transformation, decision-making strategies and tactics, and changes in operations or products -and connect them to three individual professional competencies necessary to deliver them: fundamental environmental competencies, data information and content, and system design competencies. Based on the analysis we outline several novel competency-based IS curriculum recommendations for the master's and undergraduate level IS education.Architecting for cloud: "And so the thing I noticed, a lot of these companies, when their data is growing so big and their database costs are running so high, they think about going towards Open Source Software, Open Source databases to store all the data and, hence, that creates a demand on the workforce to actually know how to use those. "Understanding data structures, architectures, and governance: "So that's his role, and the key requirement for that role again is Data Architecture, data Engineering and Data Management" Building and managing machine learning models: "Second, of course, is strong competency in the use of Machine Learning packages or models. This field is evolving aggressively." "For developing or programming our own AI solutions, our employees have no deep knowledge of mathematical models and how to build mature and value-creating AI applications." IS management and operations: "The talent sort of wars out there are really, really tough, and finding people who understand that, (how to) generate the data, use the data, think about the data, manipulate it are really, really important. I agree. It used to be you had to have people with Project Management. That was critical and that was everyone competed for that, and now it's that plus the data, the Machine Learning."Based on the data collected in this study, we cannot offer a clear answer to the questions of how BDA and AI affect areas that do not belong to the two main areas of the study. Given, however, how quickly BDA and AI have grown and how substantial related resource requirements are in organizations, it is clear that they already have an impact on several competency needs such as programming language selection, selection of BDA and AI tools based on cloud-based solutions, data architecture, data governance, service repertoires available on platform environments, and special characteristic of BDA and AI projects and how they affect education for project management needs and competencies. Summary of Findings Related to Individual CompetenciesGenerally, we observe a strong alignment and continuity between the recent information systems curriculum recommendations and the findings of this study. The data highlights the continued importance of IS core topics covered in all past curricula, such as data management, systems development, IT infrastructure and architecture (including security), and IS (project) management.The results also highlight also multiple areas that need more emphasis and careful design decisions when schools plan and implement their BDA and AI based programs: Integration of business and technology competencies in ways that allow seamless communication with both business and technology experts  A stronger emphasis on multiple life cycle models and concepts related to data management and data science than in the recent model curricula focused on system life cycles  Heightened focus on new dimensions of data analytics competencies (including communication-related elements such a storytelling and visualization)  The growing importance of ethics as a foundation for ensuring privacy and security of BDA and AI models  Need for more skills in statistics  Understanding the novel requirements that AI solutions set up for IT infrastructure  The importance of competencies in AI systems development and deployment. Collapse

Topics: artificial intelligence big data analytical information system data management decision making

Methods: qualitative interview machine learning meta learning field study personal interview

HUMAN-AI COLLABORATION IN CONCEPTUALIZING DESIGN SCIENCE RESEARCH STUDIES: PERCEIVED HELPFULNESS OF GENERATIVE LANGUAGE MODEL'S SUGGESTIONS

2023 | European Conference On Information Systems | Citations: 0

Authors: Memmert, Lucas; Cvetkovic, Izabel; Bittner, Eva

Abstract: Solving complex problems was named a new challenge for research on human-AI col ... Expand

Abstract: Solving complex problems was named a new challenge for research on human-AI collaboration. In our study we focus on a particular means to solving complex problems: design science research (DSR). We investigate whether AI, more specifically, generative language models (GLM), can support an individual in conceptualizing DSR studies by making helpful suggestions. To do so we use extracts of a published DSR study and have GPT-3, a GLM provide suggestions for aspects of this study. These suggestions are then evaluated in a survey (n=33) regarding their helpfulness. Results show that GLM suggestions are perceived to be helpful, with some variation depending on expertise. Reported interest in using such a tool in the future was high. Describing how GLMs can offer helpful suggestions we contribute toward a DSR tool support ecosystem and, more generally, towards knowledge on how humans and (generative) AI systems can team up to solve complex problems. Collapse

Topics: artificial intelligence human computer interaction human AI collaboration generative AI system support

Methods: survey design requirement design principle correlation analysis descriptive statistic

Innovative Concepts within Knowledge Management

2023 | HICSS | Citations: 0

Authors: Schenk, Johannes

Abstract: In our increasingly knowledge-based society the need for innovative concepts wit ... Expand

Abstract: In our increasingly knowledge-based society the need for innovative concepts within the discipline of Knowledge Management (KM) becomes clear. Therefore, this article aims to shed light on current and uprising innovative technologies and concepts within the discipline of KM. This study conveys recent and previous scientific literature on the relevance of uprising innovative concepts within the various dimensions of KM. We conducted a systematic literature review (SLR) on various literature sources to cover the whole spectrum of innovative KM approaches. All 37 reviewed articles originate from acknowledged sources and were written in English. The findings show, which innovative concepts show relevance within KM, how they are classified into the three innovation categories social, technological, and organizational, how they manifest within KM and what to expect from future KM innovations. Collapse

Topics: innovation management artificial intelligence virtual reality knowledge management gamification

Methods: structured literature research design artifact synthesis literature sample literature study

How Board of Directors’ Social Capital Enhances the Effectiveness of IT and R&D Resources Toward More Effective Innovation

2023 | HICSS | Citations: 0

Authors: Shekarian, Naser; Ramirez, Ronald; Tallon, Paul; Shekarian, Mansoor

Abstract: A board of directors (BOD) plays a critical governance and strategic oversight r ... Expand

Abstract: A board of directors (BOD) plays a critical governance and strategic oversight role in an organization; acting as a fiduciary for shareholders, advising strategic decision making, and providing supportive resources and information to key decision makers. Especially critical is the role and contribution of corporate governance in guiding firm innovation. Such guidance has implications for investment in new products and services. In this paper, we examine the synergistic relationship between a firm’s BOD and technology and R&D inputs to innovation. We focus on the influence of the social capital of a BOD on different types of innovation. Our longitudinal findings show IT, R&D, and BOD social capital individually contribute to innovation performance, reflected in exploitative and exploratory innovation productivity. Moreover, BOD social capital enhances innovation enabled by IT activities. However, the combination of R&D activities and dimensions of BOD social capital leads to both negative and positive innovation performance. Collapse

Topics: innovation management social capital research and development knowledge creation productivity

Methods: longitudinal research White test Breusch-Pagan test archival research econometric modeling

Theories: organizational knowledge creation