On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment

2023 | Information Systems Frontiers | Citations: 1

Authors: Bacon, Emily; Williams, Michael D.; Davies, Gareth H.

Abstract: Organisations are increasingly creating inter-organisational ecosystem partnersh ... Expand

Abstract: Organisations are increasingly creating inter-organisational ecosystem partnerships to innovate openly. Despite effective knowledge management significantly supporting ecosystem infrastructures, empirical insights into the importance of and interdependencies between conditions for successful knowledge exchange across ecosystem contexts remain unexplored within existing literature. This study implements a mixed-method approach to ascertain which conditions are responsible for knowledge transfer success across innovation ecosystems. Interpretive Structural Modelling was employed to analyse questionnaires with key ecosystem stakeholders, in order to impose a hierarchical structure upon the conditions. The configurational nature of these conditions, and their combinations into solutions for success was ascertained through analysing semi-structured interviews using fuzzy-set Qualitative Comparative Analysis. Results reveal multiple, mutually exclusive pathways to knowledge transfer success, grouped into three solution types, increasing understanding of the interrelated nature of the knowledge transfer conditions. Limitations and implications for future research are provided. Collapse

Topics: knowledge sharing innovation management knowledge type open innovation digital transformation

Methods: qualitative interview survey computational algorithm literature study fuzzy set qualitative comparative analysis

Theories: complexity theory

Blockchain technology and gender equality: A systematic literature review

2023 | International Journal of Information Management | Citations: 0

Authors: Di Vaio, Assunta; Hassan, Rohail; Palladino, Rosa

Abstract: This study examines the literary corpus on the role and potential of blockchain ... Expand

Abstract: This study examines the literary corpus on the role and potential of blockchain technology in promoting gender equality through the lens of new technology-oriented corporate governance models. It investigates if and how corporate governance models can include blockchain technology to add value to gender equality and inclusion processes, in line with Sustainable Development Goal (SDG) 5. A bibliometric analysis of a database—containing 127 articles, 4 United Nations reports, 3 European institutions’ reports, 1 International Labour Office report, 1 World Economic Forum report, and 4 industry reports useful to our analysis—was conducted from 1990 to 2021, to provide a map of the knowledge generated and circulated by the literature. This study offers insights into publication activities, essential topics, citation trends, and the status of collaborations between contributors to previous research and aggregated contributions to the area of blockchain technology studies. Furthermore, the study offers a retrospective analysis of the content published in the blockchain technology field. The findings indicate that field research has focussed primarily on blockchain’s economic and financial attributes but not on social potential. This study emphasises the implementation of blockchain technology to manage gender equality and inclusion processes by orienting corporate governance models towards social and sustainable values. Collapse

Topics: blockchain database system information system use corporate governance business process management

Methods: bibliometric analysis literature sample qualitative content analysis VOSviewer literature study

Theories: institutional theory

Sharing Design Knowledge Through Codification in Interdisciplinary DSR Collaborations

2023 | HICSS | Citations: 0

Authors: Dickhaut, Ernestine; Janson, Andreas; Hevner, Alan; Leimeister, Jan

Abstract: The goals of design science research (DSR) projects are to generate novel and us ... Expand

Abstract: The goals of design science research (DSR) projects are to generate novel and useful artifacts and to produce rigorous and generalizable design knowledge. Often, DSR projects are conducted in collaborative, interdisciplinary project teams. Different disciplinary approaches to codifying design knowledge result in challenging project interactions. To study this situation, we analyze design knowledge codification in interdisciplinary teams over time. We gain insights from a survey of recent DSR papers that have been published in the AIS Senior Scholars’ Basket. We then present a detailed case study of a longitudinal project that brought to light issues of sharing design knowledge across disciplinary borders. Drawing from the survey and case study, we provide actionable guidance on how to effectively codify and share design knowledge to support researchers and practitioners to build useful artifacts and to make interdisciplinary design knowledge contributions reusable and applicable. Collapse

Topics: explicit knowledge knowledge representation database system

Methods: literature sample design artifact case study longitudinal research literature study

Theories: theory of affordance

Responsible cognitive digital clones as decision-makers: a design science research study

2023 | European Journal of Information Systems | Citations: 0

Authors: Golovianko, Mariia; Gryshko, Svitlana; Terziyan, Vagan; Tuunanen, Tuure

Abstract: This study uses a design science research methodology to develop and evaluate th ... Expand

Abstract: This study uses a design science research methodology to develop and evaluate the Pi-Mind agent, an information technology artefact that acts as a responsible, resilient, ubiquitous cognitive clone – or a digital copy – and an autonomous representative of a human decision-maker. Pi-Mind agents can learn the decision-making capabilities of their “donors” in a specific training environment based on generative adversarial networks. A trained clone can be used by a decision-maker as an additional resource for one’s own cognitive enhancement, as an autonomous representative, or even as a replacement when appropriate. The assumption regarding this approach is as follows: when someone was forced to leave a critical process because of, for example, sickness, or wanted to take care of several simultaneously running processes, then they would be more confident knowing that their autonomous digital representatives were as capable and predictable as their exact personal “copy”. The Pi-Mind agent was evaluated in a Ukrainian higher education environment and a military logistics laboratory. In this paper, in addition to describing the artefact, its expected utility, and its design process within different contexts, we include the corresponding proof of concept, proof of value, and proof of use. Collapse

Topics: artificial intelligence decision making digital transformation legal context information system use

Methods: design artifact machine learning binary classification design science design principle

Guidance in Business Intelligence & Analytics Systems: A Review and Research Agenda

2023 | European Conference On Information Systems | Citations: 0

Authors: Gunklach, Jonas; Nadj, Mario

Abstract: While the data amount grows exponentially, the number of people with analytical ... Expand

Abstract: While the data amount grows exponentially, the number of people with analytical and technical skills is only slowly increasing. This skill gap is putting pressure on the labor market and increasing the need for personnel with these skills. At the same time, companies are forced to think of alternative ways to empower their less-skilled workforce to take on Business Intelligence and Analytics (BI&A) tasks. One promising attempt to address these challenges may turn to the concept of guidance. However, the current body of research on guidance in BI&A systems is scattered and lacks a structured investigation from which future research avenues can be derived. To address this gap, this article analyzes five categories, namely BI&A phases, guidance degree, guidance generation, user roles, and interactivity form. Reviewing 82 articles, our contribution is to synopsize articles on guidance in BI&A systems and to suggest five research avenues. Collapse

Topics: analytical information system data visualization data quality business intelligence artificial intelligence

Methods: exploratory data analysis machine learning literature sample time series analysis longitudinal research

The Recursive Theory of Knowledge Augmentation: Integrating human intuition and knowledge in Artificial Intelligence to augment organizational knowledge

2023 | Information Systems Frontiers | Citations: 0

Authors: Harfouche, Antoine; Quinio, Bernard; Saba, Mario; Saba, Peter Bou

Abstract: Artificial intelligence (AI) has increased the ability of organizations to accum ... Expand

Abstract: Artificial intelligence (AI) has increased the ability of organizations to accumulate tacit and explicit knowledge to inform management decision-making. Despite the hype and popularity of AI, there is a noticeable scarcity of research focusing on AI's potential role in enriching and augmenting organizational knowledge. This paper develops a recursive theory of knowledge augmentation in organizations (the KAM model) based on a synthesis of extant literature and a four-year revised canonical action research project. The project aimed to design and implement a human-centric AI (called Project) to solve the lack of integration of tacit and explicit knowledge in a scientific research center (SRC). To explore the patterns of knowledge augmentation in organizations, this study extends Nonaka's SECI (socialization, externalization, combination, and internalization) model by incorporating the human-in-the-loop Informed Artificial Intelligence (IAI) approach. The proposed design offers the possibility to integrate experts' intuition and domain knowledge in AI in an explainable way. The findings show that organizational knowledge can be augmented through a recursive process enabled by the design and implementation of human-in-the-loop IAI. The study has important implications for research and practice. Collapse

Topics: artificial intelligence organizational memory explicit knowledge human in the loop human computer interaction

Methods: computational algorithm action research qualitative interview participant observation statistical hypothesis test

Theories: SECI model of knowledge dimensions organizational knowledge creation

Facilitators and Barriers of Artificial Intelligence Adoption in Business – Insights from Opinions Using Big Data Analytics

2023 | Information Systems Frontiers | Citations: 0

Authors: Kar, Arpan Kumar; Kushwaha, Amit Kumar

Abstract: Data-driven predictions have become an inseparable part of business decisions. A ... Expand

Abstract: Data-driven predictions have become an inseparable part of business decisions. Artificial Intelligence (AI) has started helping the product and support teams perform more accurate experiments in various business settings. This study proposes a framework for businesses based on inductive learnings related to success and barriers shared on social media platforms. Our goal is to analyse the signals emerging from these conversational opinions from the early adoption of AI, with a focus towards facilitators and barriers faced by teams. Factors like efficiency, innovation, business research, product novelty, manual intervention, adaptability, emotion, support, personal growth, experiential learning, fear of failure and fear of upgradation have been identified based on an exploratory study and then a confirmatory study. We present the learnings through a roadmap for practitioners. This study contributes to the IS literature by delineating AI as a determinant of success and introduces a lot of organizational factors into the model. Collapse

Topics: artificial intelligence Twitter innovation management big data social media

Methods: topic model literature study synthesis regression analysis method data transformation

Theories: organizational theory organizational behavior theory management theory technology acceptance model organizational learning theory

Visual Analytics: Transferring, Translating and Transforming Knowledge from Analytics Experts to Non-technical Domain Experts in Multidisciplinary Teams

2023 | Information Systems Frontiers | Citations: 0

Authors: Marjanovic, Olivera; Patmore, Greg; Balnave, Nikola

Abstract: Today’s complex problems call for multidisciplinary analytics teams comprising o ... Expand

Abstract: Today’s complex problems call for multidisciplinary analytics teams comprising of both analytics and non-technical domain (i.e. subject matter) experts. Recognizing the difference between data visualisaion (DV) (i.e. static visual outputs) and visual analytics (VA) (i.e. a process of interactive visual data exploration, guided by user’s domain and contextual knowledge), this paper focuses on VA for non-technical domain experts. By seeking to understand knowledge sharing from VA experts to non-technical users of VA in a multidisciplinary team, we aim to explore how these domain experts learn to use VA as a thinking tool, guided by their knowing-in-practice. The research described in this paper was conducted in the context of a long-term industry-wide research project called the ‘Visual Historical Atlas of the Australian Co-operatives’, led by a multidisciplinary VA team who faced the challenge tackled by this research. Using Action Design Research (ADR) and the combined theoretical lens of boundary objects and secondary design, the paper theorises a three-phase method for knowledge transfer, translation and transformation from VA experts to domain experts using different types of VA-related boundary objects. Together with the proposed set of design principles, the three-phase model advances the well-established stream of research on organizational use of analytics, extending it to the emerging area of visual analytics for non-technical decision makers. Collapse

Topics: knowledge sharing data visualization implicit knowledge knowledge management participatory design

Methods: kernel theory design science action design research exploratory data analysis theory development

Theories: boundary objects theory

Perceived Fairness of Human Managers Compared with Artificial Intelligence in Employee Performance Evaluation

2023 | Journal of Management Information Systems | Citations: 0

Authors: Qin, Shaojun; Jia, Nan; Luo, Xueming; Liao, Chengcheng; Huang, Ziyao

Abstract: Human managers are increasingly challenged by artificial intelligence (AI) techn ... Expand

Abstract: Human managers are increasingly challenged by artificial intelligence (AI) technologies in performing managerial functions. We undertook a field experiment that used AI vis-à-vis human managers to perform structured, data-intensive evaluations of employee performance. We generate two sets of insights. First, employees considered AI to be both fairer and more accurate in evaluating their performance than the average human manager. Second, to catch up with AI, human managers' fairness perceived by employees played a first-order role by (a) helping human managers, to a greater extent than those managers' evaluation accuracy, to close the performance gap of the employees evaluated by them compared with that of those evaluated by AI, and (b) constraining the effect of human managers' perceived accuracy of evaluations on employees' performance. Thus, facing the competition from AI, it is all the more important for human managers to treat employees fairly and build positive interpersonal relationships with employees. Collapse

Topics: artificial intelligence individual productivity implicit knowledge electronic finance organization learning

Methods: experiment survey field experiment computational algorithm survey design

Theories: organizational theory behavioral theory

Knowledge management mechanisms and common knowledge impacts on the value of knowledge at individual and organizational levels

2023 | International Journal of Information Management | Citations: 0

Authors: Sabherwal, Rajiv; Steelman, Zach; Becerra-Fernandez, Irma

Abstract: Knowledge management (KM) impacts have typically been examined on the value of k ... Expand

Abstract: Knowledge management (KM) impacts have typically been examined on the value of knowledge to organizations but not individuals. This paper uses survey data (186 employees) and qualitative data (300 + employees) at the National Aeronautics and Space Administration to examine the effects of four KM mechanisms (social learning, learning from others through IT, learning from IT, and IT-based knowledge substitution) and common knowledge on the individual and organizational value of knowledge. The results indicate that common knowledge and the two interpersonal mechanisms (social learning, learning from others through IT) enhance the perceived value of knowledge at both levels, but both mechanisms that rely on IT for the knowledge (learning from IT, IT-based knowledge substitution) reduce the perceived knowledge value at one level and have no significant effect at the other level. Further, common knowledge strengthens the positive effects of both interpersonal mechanisms, and weakens the negative effects of IT-based knowledge substitution, on perceived value of knowledge at both levels. Collapse

Topics: organizational value explicit knowledge IS impact knowledge sharing service desk

Methods: qualitative interview chi squared test focus group structural equation modeling design artifact

Theories: assimilation theory of learning