Wissen 4.0 – Wissensmanagement im digitalen Wandel

North, Klaus; Maier, Ronald

doi:10.1365/s40702-018-0426-6

Cited by 36 publications

(6 citation statements)

References 31 publications

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“…For managers, these differences impact how a B2B firm can turn to artificial intelligence to create, organize and share knowledge, i.e. intangible assets and resources that may result in a sustained competitive advantage or superior organizational performance (Grant, 1996, 2002; North and Maier, 2018; Kogut and Zander, 1992). For scholars, construct diversity allows an investigation of how existing theories and extant understanding in the literature may or may not apply to the knowledge enabled by artificial intelligence.…”

Section: Implications Of Artificial Intelligence For Market Knowledge In B2b Marketingmentioning

confidence: 99%

Artificial intelligence (AI) and its implications for market knowledge in B2B marketing

Paschen

Kietzmann

2019

JBIM

231

158

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Purpose The purpose of this paper is to explain the technological phenomenon artificial intelligence (AI) and how it can contribute to knowledge-based marketing in B2B. Specifically, this paper describes the foundational building blocks of any artificial intelligence system and their interrelationships. This paper also discusses the implications of the different building blocks with respect to market knowledge in B2B marketing and outlines avenues for future research. Design/methodology/approach The paper is conceptual and proposes a framework to explicate the phenomenon AI and its building blocks. It further provides a structured discussion of how AI can contribute to different types of market knowledge critical for B2B marketing: customer knowledge, user knowledge and external market knowledge. Findings The paper explains AI from an input–processes–output lens and explicates the six foundational building blocks of any AI system. It also discussed how the combination of the building blocks transforms data into information and knowledge. Practical implications Aimed at general marketing executives, rather than AI specialists, this paper explains the phenomenon artificial intelligence, how it works and its relevance for the knowledge-based marketing in B2B firms. The paper highlights illustrative use cases to show how AI can impact B2B marketing functions. Originality/value The study conceptualizes the technological phenomenon artificial intelligence from a knowledge management perspective and contributes to the literature on knowledge management in the era of big data. It addresses calls for more scholarly research on AI and B2B marketing.

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Section: Implications Of Artificial Intelligence For Market Knowledge In B2b Marketingmentioning

confidence: 99%

Artificial intelligence (AI) and its implications for market knowledge in B2B marketing

Paschen

Kietzmann

2019

JBIM

231

158

View full text Add to dashboard Cite

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“…It is also essential to establish the connection between humans and digital systems and to ensure the adequate sharing of technical information and knowledge (Mourtzis et al, 2019). North & Maier (2018) assumed that utilising digital technologies enhancing value creation through knowledge sharing.…”

Section: Knowledge Management Perspectivementioning

confidence: 99%

Examining Industry 4.0 through the lens of human resource and knowledge management: Implications for SMEs

Csizmadia

Obermayer-Kovács

Bogdány

et al. 2023

Management &Amp; Marketing

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The change caused by Industry 4.0 (I4.0) has fundamentally changed our lives and operations of organisations. The objective of the article is to reveal whether I4.0 implementation supports human workforces, knowledge sharing and knowledge storage in case of Hungarian small and medium-sized enterprises (SMEs). The data were obtained from 122 completed questionnaires out of 152 requests. The analysis is based on quantitative methodology, relationship analyses (Cramer’s V) were used. The study was conducted in 2021 with the participation of Hungarian SMEs’ leaders. Based on the results it can be concluded that the implementation of I4.0 technologies supports human workforces in SMEs. In addition, our study reveals that collaborative technologies and social media were implemented to support knowledge sharing in SMEs. At the same time, knowledge storage is not the primary purpose of implementing I4.0 technologies in SMEs. From a theoretical perspective, it contributes to enriching the empirical evidence on implementing I4.0 technologies and their impact on supporting human resources. From a practical point of view, the research identifies those I4.0 technologies that support SMEs in knowledge sharing. Collaborative technologies and social media can be implemented in order to advance the fields of Collaboration, Communication and Connecting. The originality of our research is given by the fact that, to the best of our knowledge, this is the first study that examines the aspects of I4.0 technologies in terms of human resource and knowledge sharing and storage in Hungarian SMEs.

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“…The training process is a highly automated and computationally intensive process that requires extreme computing power to develop the AI models (van Giffen et al, 2020). The integration of AI-based applications into products, services, processes, and business models requires both the backing of and anchoring in senior management, and comprehensive AI knowledge in the organization (Kreutzer and Sirrenberg, 2019). Ulrich and Bachlechner also note that IT departments generally have a major influence on the use of AI (Ulrich and Bachlechner, 2020).…”

Section: Artificial Intelligence (Ai)mentioning

confidence: 99%

“…The use of artificial intelligence (AI) is repeatedly mentioned as one way of achieving this goal. If the competencies of humans and intelligent systems are bundled with the goal of maximizing customer value relative to the competition, competitive advantages can be realized (North and Maier, 2018). However, AI can only be deployed where digital infrastructures exist and enable its use.…”

Section: Introductionmentioning

confidence: 99%

Barriers to the Use of Artificial Intelligence in the Product Development – A Survey of Dimensions Involved

2023

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Artificial intelligence (AI) is seen as a great opportunity to secure future competitiveness in many corporate sectors. Potential for its use also exists in product development (PD) activities due to the amount of data generated and processed. Nevertheless, there are problems in applying the technology. This paper addresses current challenges based on a literature review, considering three disciplines that are necessary for the scope of this paper as a minimum: AI itself, information technology infrastructures (ITI) in context of digital transformation (DT), and PD as an application area. Building on the basic considerations of the state of the art, a link between the domains is established by outlining a possible reference framework towards the utilization of AI applications in PD. This enables an expanded interdisciplinary understanding. Key obstacles appear specifically to be difficult collaboration conditions between the disciplines of PD and AI applications development due to communication problems. Reasons for this include: – Meta models of PD do not provide a sufficient information base– Lack of standardized process models for the deployment of AI

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Wissen 4.0 – Wissensmanagement im digitalen Wandel

Cited by 36 publications

References 31 publications

Artificial intelligence (AI) and its implications for market knowledge in B2B marketing

Artificial intelligence (AI) and its implications for market knowledge in B2B marketing

Examining Industry 4.0 through the lens of human resource and knowledge management: Implications for SMEs

Barriers to the Use of Artificial Intelligence in the Product Development – A Survey of Dimensions Involved

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