Knowledge creation in the automotive industry: Analysing obeya-oriented practices using the SECI model

Canonico, Paolo; Nito, Ernesto De; Esposito, Vincenza; Iacono, Mauro; Consiglio, Stefano

doi:10.1016/j.jbusres.2019.11.047

Cited by 35 publications

(33 citation statements)

References 29 publications

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“…Right knowledge environment is an inevitable element of lean product development (Araci et al, 2020;Canonico et al, 2020). Some researchers use SECI model (Socialisation, Externalisation, Combination, Internalisation)…”

Section: Trade-off Curves Within the Lean Product Development Conceptmentioning

confidence: 99%

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Physics-based trade-off curves to develop a control access product in set-based concurrent engineering environment

Araci

Al-Ashaab²,

Almeida

2021

IJLSS

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Purpose This paper aims to present a process to generate physics-based trade-off curves (ToCs) to facilitate lean product development processes by enabling two key activities of set-based concurrent engineering (SBCE) process model that are comparing alternative design solutions and narrowing down the design set. The developed process of generating physics-based ToCs has been demonstrated via an industrial case study which is a research project. Design/methodology/approach The adapted research approach for this paper consists of three phases: a review of the related literature, developing the process of generating physics-based ToCs in the concept of lean product development, implementing the developed process in an industrial case study for validation through the SBCE process model. Findings Findings of this application showed that physics-based ToC is an effective tool to enable SBCE activities, as well as to save time and provide the required knowledge environment for the designers to support their decision-making. Practical implications Authors expect that this paper will guide companies, which are implementing SBCE processes throughout their lean product development journey. Physics-based ToCs will facilitate accurate decision-making in comparing and narrowing down the design-set through the provision of the right knowledge environment. Originality/value SBCE is a useful approach to develop a new product. It is essential to provide the right knowledge environment in a quick and visual manner which has been addressed by demonstrating physics knowledge in ToCs. Therefore, a systematic process has been developed and presented in this paper. The research found that physics-based ToCs could help to identify different physics characteristics of the product in the form of design parameters and visualise in a single graph for all stakeholders to understand without a need for an extensive engineering background and for designers to make a decision faster.

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Section: Trade-off Curves Within the Lean Product Development Conceptmentioning

confidence: 99%

“…which is a theoretical framework for practices in creating knowledge (Canonico et al, 2020). Nonaka and Takeuchi (1995) proposed this framework to explain the secret of Japanese automobile producers in innovating dynamically and securing their competitive advantage.…”

Section: Trade-off Curves Within the Lean Product Development Conceptmentioning

confidence: 99%

Physics-based trade-off curves to develop a control access product in set-based concurrent engineering environment

Araci

Al-Ashaab²,

Almeida

2021

IJLSS

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“…Transfer pengetahuan di berbagai bidang, baik untuk pengetahuan tacit maupun explicit, Model SECI dalam membentuk Knowledge Management System pada sebuah organisasi sangat membantu proses alur transfer pengetahuan [2], [21] dan [22]. Transfer pengetahuan tacit ke tacit dalam bentuk sosialisasi, tacit ke eksplisit dalam bentuk eksternalisasi, eksplisit ke eksplisit dalam bentuk kombinasi dan eksplisit ke tacit dalam bentuk internalisasi.…”

Section: Data Mining Sebagai Alat Bantu Manajemen Pengetahuanunclassified

“…Pendekatan kualitatif untuk menganalisis materi empiris dikumpulkan. Pengumpulan data dilakukan dengan memanfaatkan berbagai sumber, termasuk wawancara semi terstruktur, penyebaran kuisioner dan pengolahan dokumen internal [2]. Namun untuk data yang berjumlah kecil atau tanpa menggunakan alat bantu khusus, peneliti kesulitan dalam mengeksplor pengetahuan.…”

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Desain Model Data Mining pada Model SECI untuk Pemetaan dan Ekstraksi Pengetahuan Kompetensi Lulusan

Mardiani¹

2021

JATISI

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Manajemen pengetahuan menggunakan Model SECI membantu dalam transfer pengetahuan tacit dan eksplisit. Keterbatasan kemampuan sumber daya manusia dalam transfer pengetauan membutuhkan alat bantu dalam prosesnya. Ekstraksi pengetahuan dapat dilakukan dengan implementasi data mining. Hasil keluaran data mining yang besar akan dimanfaatkan oleh dunia pendidikan untuk tujuan strategis, misalnya evaluasi penyusunan profil lulusan dari hasil analisis kompetensi lulusan. Kurikulum Program Studi disusun berdasarkan profil Lulusan dan Program Studi membutuhkan pemetaan kebutuhan dari data alumni dalam menyusun kurikulum, sementara alumni membutuhkan mata kuliah yang mendukung setelah selesai kuliah. Manajemen Pengetahuan menampung pengetahuan dari lulusannya, sementara Data mining digunakan sebagai alat dalam mengolah data. Transfer pengetahuan dan pengolahan data kompetensi lulusan, dan memungkinkan munculnya pengetahuan baru bagi perguruan tinggi yang bisa dimanfaatkan dalam proses penyusunan kurikulum berikutnya. Model yang digunakan adalah SECI dikombinasikan dengan algoritma klasifikasi dan clustering. Model SECI yang sudah dipetakan alat bantu teknologinya pada setiap prosesnya, dibuat lebih jelas dan spesifik pengelompokkannya dengan implementasi Data Mining pada setiap kuadran Model SECI. Desain model SECI yang dikombinasikan dengan teknologi Data Mining akan memperbaiki kekurangan yang terdapat pada model sebelumnya.

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“…For example, the study on understanding of knowledge creation in the context of knowledge-intensive business processes by Little and Deokar (2016), by Hubers et al (2016) in the context of educational science, W. Zhang and Zhang (2018) on knowledge creation through industry chain (chemical) in resource-based industry, and Li et al (2018) that proposed new knowledge creation model, Grey SECI (G-SECI), the enhancement of SECI model in the complex product systems development. Canonico et al (2019) and Tsai and Huili (2007) also posited about the conditions that can facilitate the creation of knowledge and how to encourage the process and Chen et al (2012) added about the organizational mechanisms that will allow personnel to create knowledge within the organization. However, recent studies are almost none on exploring knowledge creation in the military context especially on the navy fleet.…”

Section: Knowledge Creationmentioning

confidence: 99%

Evaluating knowledge creation processes in the Royal Malaysian Navy (RMN) fleet: Personnel conceptualization, participation and differences

Rusland

Jaafar

Sumintono

2020

Cogent Business & Management

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This article analyses the Royal Malaysian Navy (RMN) fleet personnel's responses to survey questionnaire items on the knowledge creation processes, in order to identify the current extent of processes within the fleet. Through knowledge creation, new knowledge is created, starting with the discovery of knowledge and eventually, new and additional knowledge creation. Saving this created knowledge from dissipating is crucial to remain relevant. Hence, a survey was conducted on 214 of the fleet's personnel utilizing the Knowledge Creation Process SECI Model. The results revealed that knowledge creation processes are being practised in the fleet. However, the extent varied and most of the RMN fleet personnel participated at a moderate level in the processes. Socialization and internalization process dimensions are more actively utilized than externalization and combination process dimensions in knowledge creation within the fleet. Respondents with different demographic profiles had differences in their opinions, perceptions, and attitudes towards the knowledge creation processes. This needs to be looked into further since a sophisticated fleet with state-of-the-art inventories

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Knowledge creation in the automotive industry: Analysing obeya-oriented practices using the SECI model

Cited by 35 publications

References 29 publications

Physics-based trade-off curves to develop a control access product in set-based concurrent engineering environment

Physics-based trade-off curves to develop a control access product in set-based concurrent engineering environment

Desain Model Data Mining pada Model SECI untuk Pemetaan dan Ekstraksi Pengetahuan Kompetensi Lulusan

Evaluating knowledge creation processes in the Royal Malaysian Navy (RMN) fleet: Personnel conceptualization, participation and differences

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