- About
-
The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
Search results
Showing 1 to 2 of 2 (0.043 seconds)Spelling suggestions: "subject:"tech enterprise"" "subject:"tech interprise""
| 1 |
Knowledge transfer in requirements engineering in collaborative product developmentDistanont, A. (Anyanitha) 07 January 2013 (has links)
Abstract
At present, collaborative strategies are an important part of developing the capabilities to be able to compete in the 21st Century since knowledge or innovations cannot develop entirely within a single firm. Collaboration provides invaluable resources that a firm cannot create through knowledge transfer mechanisms. The purpose of this doctoral dissertation is to enhance understanding of knowledge transfer in requirements engineering in the context of collaborative product development. The research is qualitative by nature and utilises the case study methodology. Data collection was conducted through interviews and surveys with informants in high-tech enterprises. The results indicate that collaboration in product development is very important and acts as a means of obtaining external resources, especially knowledge. However, collaboration is not an easy practice; it involves many challenges. In order to improve the practice of collaboration, it is necessary to manage and leverage the transfer of knowledge. According to the results, in order to increase the effectiveness of knowledge transfer over enterprise interfaces, each knowledge type needs to be transferred through the suitable transfer channel at the right time. The results also indicate that the individual relationships among buyers and suppliers are an essential element for long-term collaboration and common platforms or tools need to be developed to support collaborative product development over enterprise interfaces. / Tiivistelmä
Kiristyvän kilpailun tilanteessa yritykset etsivät keinoja tehostaakseen toimintaansa. Yksi keino tähän on yhteistyökumppanina toimivien yritysten hyödyntäminen tuotekehityksessä. Yhteistyökumppanien hyödyntämisellä yritykset pyrkivät muun muassa tukemaan innovatiivisuutta ja täydentämään tuotekehityksessä tarvittavia kyvykkyyksiä. Tähän pyritään hankkimalla lisää resursseja, erityisesti tietämystä ja osaamista, jota yrityksellä ei itsellään ole tai joka on ulkoistettu aiemmin. Tässä väitöskirjassa perehdytään yritysyhteistyötä hyödyntävään tuotekehitystoimintaan ja tutkimuksen tavoitteena on lisätä ymmärrystä osaamisen siirrosta erityisesti vaatimusten hallinnan prosessissa.
Tämä väitöskirjatyö on laadullinen tapaustutkimus. Tutkimuksen empiirinen aineisto on hankittu haastatteluilla ja kyselyillä korkeanteknologian yrityksistä. Tutkimustulosten mukaan yritysten välinen yhteistyö tuotekehityksessä on merkittävässä roolissa moderneissa yrityksissä. Tällöin voidaan puhua ulkopuolisten resurssien, erityisesti ulkoisen osaamisen hyödyntämisestä tuotekehityksessä.
Tulosten mukaan on kuitenkin huomioitava, että yritysyhteistyö on varsin monimutkaista ja haastavaa toteuttaa. Yritysten tulee paremmin johtaa osaamisen siirtoa yhteistyökumppaneiden välillä ja panostaa osaamisen siirtoon liittyviin toimintatapoihin ja työkaluihin. Yritysten välisen osaamisen siirron tehokkuuden lisäämiseksi tulee huomioida, että erityyppinen osaaminen tulee siirtää sille ominaisen kanavan kautta juuri oikeaan aikaan. Tulosten mukaan yrityksissä toimivien henkilöiden väliset suhteet ovat keskeisessä roolissa pitkän aikavälin yritysyhteistyölle. Tukeakseen paremmin yritysyhteistyötä tuotekehityksessä yritysten tulisi kehittää yhteisiä alustoja tai työkaluja osaamisen siirtoon.
|
| 2 |
Introducing Generative Artificial Intelligence in Tech Organizations : Developing and Evaluating a Proof of Concept for Data Management powered by a Retrieval Augmented Generation Model in a Large Language Model for Small and Medium-sized Enterprises in Tech / Introducering av Generativ Artificiell Intelligens i Tech Organisationer : Utveckling och utvärdering av ett Proof of Concept för datahantering förstärkt av en Retrieval Augmented Generation Model tillsammans med en Large Language Model för små och medelstora företag inom TechLithman, Harald, Nilsson, Anders January 2024 (has links)
In recent years, generative AI has made significant strides, likely leaving an irreversible mark on contemporary society. The launch of OpenAI's ChatGPT 3.5 in 2022 manifested the greatness of the innovative technology, highlighting its performance and accessibility. This has led to a demand for implementation solutions across various industries and companies eager to leverage these new opportunities generative AI brings. This thesis explores the common operational challenges faced by a small-scale Tech Enterprise and, with these challenges identified, examines the opportunities that contemporary generative AI solutions may offer. Furthermore, the thesis investigates what type of generative technology is suitable for adoption and how it can be implemented responsibly and sustainably. The authors approach this topic through 14 interviews involving several AI researchers and the employees and executives of a small-scale Tech Enterprise, which served as a case company, combined with a literature review. The information was processed using multiple inductive thematic analyses to establish a solid foundation for the investigation, which led to the development of a Proof of Concept. The findings and conclusions of the authors emphasize the high relevance of having a clear purpose for the implementation of generative technology. Moreover, the authors predict that a sustainable and responsible implementation can create the conditions necessary for the specified small-scale company to grow. When the authors investigated potential operational challenges at the case company it was made clear that the most significant issue arose from unstructured and partially absent documentation. The conclusion reached by the authors is that a data management system powered by a Retrieval model in a LLM presents a potential path forward for significant value creation, as this solution enables data retrieval functionality from unstructured project data and also mitigates a major inherent issue with the technology, namely, hallucinations. Furthermore, in terms of implementation circumstances, both empirical and theoretical findings suggest that responsible use of generative technology requires training; hence, the authors have developed an educational framework named "KLART". Moving forward, the authors describe that sustainable implementation necessitates transparent systems, as this increases understanding, which in turn affects trust and secure use. The findings also indicate that sustainability is strongly linked to the user-friendliness of the AI service, leading the authors to emphasize the importance of HCD while developing and maintaining AI services. Finally, the authors argue for the value of automation, as it allows for continuous data and system updates that potentially can reduce maintenance. In summary, this thesis aims to contribute to an understanding of how small-scale Tech Enterprises can implement generative AI technology sustainably to enhance their competitive edge through innovation and data-driven decision-making.
|
Page generated in 0.0593 seconds