The relationship between innovation and knowledge strategies: its impact on business performance

Donate, Mario J.; Gómez, Fátima Guadamillas

doi:10.1504/ijkms.2007.012532

Cited by 9 publications

(6 citation statements)

References 58 publications

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“…KM performance reflects the outcomes that come from the implementation of KM practices and technologies. In this line, a coherent development of KM actions can produce a greater impact on the results (Donate & Guadamillas, 2007). Grant (1996) points out that the application and generation of knowledge cannot be considered in isolation.…”

Section: Km Practices and Km Performancementioning

confidence: 99%

Antecedents and consequences of knowledge management performance: the role of IT infrastructure

Roldán

Real

Ceballos

2018

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Purpose: In this paper, we assess the role of knowledge management (KM) practices as a key antecedent of KM performance. Also, we examine how Information technology (IT) infrastructure is used as a driver of KM performance, organizational performance and innovation. In addition, the effects of IT infrastructure can be indirect. Specifically, we show that KM performance is a mediator between organizational performance and innovation.Design/methodology/approach: Applying a variance-based structural equation modelling (PLS), we have carried out a study among a sample of 82 Andalusian technology-intensive innovative companies.Findings: First, KM practices and IT infrastructure are significant antecedents of KM performance. Second, KM performance has a direct influence on business performance and innovation outcomes. Third, IT infrastructure does not have a direct influence on business performance and innovation outcomes, but does have a significant indirect effect on them via KM performance.Practical implications: This research provides insights for why some firms may not be realizing benefits from investing in IT infrastructure. KM performance is strongly needed for the successful implementation of IT infrastructure in the organizations.Originality/value: The findings are important for practitioners and researchers because this study makes a contribution to the literature in KM by supporting the perspective that the business and organizational performance are function of the KM performance, a complementary resource through the value of IT infrastructure is enhanced.

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Section: Km Practices and Km Performancementioning

confidence: 99%

Antecedents and consequences of knowledge management performance: the role of IT infrastructure

Roldán

Real

Ceballos

2018

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“…Firms establish different kinds of objectives and try to attain them through the development of diverse types of strategic alternatives. The KMS of a firm is thus based on the best possible strategic design in order to create, maintain, transfer and apply organizational knowledge to achieve competitive goals (Earl, 2001;Maier & Remus, 2002;Choi & Lee, 2003;Garavelli et al, 2004;Donate & Guadamillas, 2007;Donate & Canales, 2012). The development of a KMS includes all the operations related to the creation, acquisition, integration, storage, transmission, protection and application of knowledge (Day & Wendler, 1998).…”

Section: Knowledge Management In Strategic Alliancesmentioning

confidence: 99%

Knowledge Management for Strategic Alliances

Pablo

Donate

Guadamillas

2012

International Journal of Strategic Information Technology and Applications

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Managing organizational knowledge in alliances implies establishing the best possible strategic design to create, acquire, maintain, transfer, and apply organizational knowledge developed between the partners (or acquired from partners) in order to achieve competitive goals. In this paper, the role of knowledge management strategy (KMS) in strategic alliances is analyzed in a technology-intensive company. The importance of alliances for technological companies and the necessity of designing suitable KMSs in alliances –in terms of objectives and goals, knowledge management tools, and support systems– are explained first of all. Moreover, the analysis of a case study of KMS in the strategic alliances of a company currently developing different businesses in technological settings is developed by the authors. Finally, several conclusions are discussed, based on how the implementation aspects concerning KMS in strategic alliances have been managed and the way they have contributed to the attainment of the company’s objectives and goals.

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“…It is worth emphasizing that previous contributions to KM (Wiig 1993; Ruggles 1997; Heinrichs and Lim 2005; Nonaka and Toyama 2005; Collins and Smith 2006; Donate‐Manzanares and Guadamillas‐Gomez 2007; Kautz and Kjærgaard 2007; Nielsen and Michailova 2007; Soo, Devinney, and Midgley 2007) have focused on knowledge creation, acquisition, and transference. DIPKIP goes one step further by proposing a knowledge update process, which consists of increasing existing knowledge and examining it in depth to remove obsolete and useless knowledge.…”

Section: Dipkip a Novel Knowledge Management Systemmentioning

confidence: 99%

Dipkip: A Connectionist Knowledge Management System to Identify Knowledge Deficits in Practical Cases

Herrero

Corchado

Sáiz

et al. 2010

Computational Intelligence

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This study presents a novel, multidisciplinary research project entitled DIPKIP (data acquisition, intelligent processing, knowledge identification and proposal), which is a Knowledge Management (KM) system that profiles the KM status of a company. Qualitative data is fed into the system that allows it not only to assess the KM situation in the company in a straightforward and intuitive manner, but also to propose corrective actions to improve that situation. DIPKIP is based on four separate steps. An initial "Data Acquisition" step, in which key data is captured, is followed by an "Intelligent Processing" step, using neural projection architectures. Subsequently, the "Knowledge Identification" step catalogues the company into three categories, which define a set of possible theoretical strategic knowledge situations: knowledge deficit, partial knowledge deficit, and no knowledge deficit. Finally, a "Proposal" step is performed, in which the "knowledge processes"-creation/acquisition, transference/distribution, and putting into practice/updating-are appraised to arrive at a coherent recommendation. The knowledge updating process (increasing the knowledge held and removing obsolete knowledge) is in itself a novel contribution. DIPKIP may be applied as a decision support system, which, under the supervision of a KM expert, can provide useful and practical proposals to senior management for the improvement of KM, leading to flexibility, cost savings, and greater competitiveness. The research also analyses the future for powerful neural projection models in the emerging field of KM by reviewing a variety of robust unsupervised projection architectures, all of which are used to visualize the intrinsic structure of high-dimensional data sets. The main projection architecture in this research, known as Cooperative Maximum-Likelihood Hebbian Learning (CMLHL), manages to capture a degree of KM topological ordering based on the application of cooperative lateral connections. The results of two real-life case studies in very different industrial sectors corroborated the relevance and viability of the DIPKIP system and the concepts upon which it is founded.Key words: data and knowledge visualization, connectionism and neural nets, knowledge-based systems, knowledge management applications, discovery-based science.

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The relationship between innovation and knowledge strategies: its impact on business performance

Cited by 9 publications

References 58 publications

Antecedents and consequences of knowledge management performance: the role of IT infrastructure

Antecedents and consequences of knowledge management performance: the role of IT infrastructure

Knowledge Management for Strategic Alliances

Dipkip: A Connectionist Knowledge Management System to Identify Knowledge Deficits in Practical Cases

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