Technology selection and group decision support systems: Case studies on supporting strategic technology selection processes

The objective of the dissertation is to increase understanding and knowledge in the field where group decision support system (GDSS) and technology selection research overlap in the strategic sense. The purpose is to develop pragmatic, unique and competent management practices and processes for strategic technology assessment and selection from the whole company's point of view. The combination of the GDSS and technology selection is approached from the points of view of the core competence concept, the lead user -method, and different technology types. In this research the aim is to find out how the GDSS contributes to the technology selection process, what aspects should be considered when selecting technologies to be developed or acquired, and what advantages and restrictions the GDSS has in the selection processes. These research objectives are discussed on the basis of experiences and findings in real life selection meetings. The research has been mainly carried outwith constructive, case study research methods. The study contributes novel ideas to the present knowledge and prior literature on the GDSS and technology selection arena. Academic and pragmatic research has been conducted in four areas: 1) the potential benefits of the group support system with the lead user -method,where the need assessment process is positioned as information gathering for the selection of wireless technology development projects; 2) integrated technology selection and core competencies management processes both in theory and in practice; 3) potential benefits of the group decision support system in the technology selection processes of different technology types; and 4) linkages between technology selection and R&D project selection in innovative product development networks. New type of knowledge and understanding has been created on the practical utilization of the GDSS in technology selection decisions. The study demonstrates that technology selection requires close cooperation between differentdepartments, functions, and strategic business units in order to gather the best knowledge for the decision making. The GDSS is proved to be an effective way to promote communication and co-operation between the selectors. The constructs developed in this study have been tested in many industry fields, for example in information and communication, forest, telecommunication, metal, software, and miscellaneous industries, as well as in non-profit organizations. The pragmatic results in these organizations are some of the most relevant proofs that confirm the scientific contribution of the study, according to the principles of the constructive research approach.

Strategic groupsin the European energy industry

Strategisten ryhmien teoria tarjoaa mahdollisuuden keskitason analyysiin yritysten ja toimialan välillä yritysten kilpailullisen aseman tarkasteluun. Strategiset ryhmät ovat samalla toimialalla toimivia yrityksiä, joilla on samanlaiset strategiset ominaisuudet, jotka kilpailevat samanlaisilla perusteilla tai jotka toteuttavat samanlaista strategiaa. Tässä tutkimuksessa strategisten ryhmien teoriaa on käytetty eurooppalaisten energiayritysten ryhmittelyyn. Tutkimuksessa oli mukana 104 energia-alan yritystä, jotka jaettiin viiteen strategiseen pääryhmään yritysten maantieteellisen toiminta-alueen ja koon mukaan. Jokainen ryhmä edustaa erilaista strategiaa. Muita strategisia ominaisuuksia, joita ovat diversifikaatioaste, tuotantoteknologia ja omistusmuoto, käytettiin muodostamaan alaryhmiä edellisistä pääryhmistä. Muodostettuja strategisia ryhmiä käytettiin seuraavaksi suoristuskykyerojen tutkimiseen ryhmien välillä. Suorituskykyä kuvaaviksi muuttujiksi valittiin liikevoitto-%, koko pääoman tuottoaste, vakavaraisuus-% ja current ratio. Tulokset osoittavat, että energiayritykset voidaan jakaa ryhmiin valittujen strategisten ominaisuuksien perusteella. Nämä yritysten strategiset valinnat eivät vaikuta merkittävästi yritysten taloudelliseen suorituskykyyn valittujen suorituskykymuuttujien osalta. Monikansalliset jättiläisyritykset ovat suorituskyvyltään heikoimpia ja eurooppalaiset suuryritykset parhaita ryhmiä, mutta erot eivät ole tilastollisesti merkittäviä. Ainut merkittävä ero suorituskykymuuttujissa oli vakavaraisuudessa monikansallisten ja eurooppalaisten suurten yritysten välillä. Muut suorituskykymuuttujat eivät eronneet ryhmien välillä tilastollisesti merkittävästi. Tilastollisesti merkittäviä eroja ei löydetty myöskään alaryhmien välillä.

Supporting knowledge creation and sharing in the early phases of the strategic innovation process

The driving forces of technology and globalization continuously transform the business landscape in a way which undermines the existing strategies and innovations of organizations. The challenge for organizations is to establish such conditions where they are able to create new knowledge for innovative business ideas in interaction between other organizations and individuals. Innovation processes continuously need new external stimulations and seek new ideas, new information and knowledge locating more and more outside traditional organizational boundaries. In several studies, the early phases of the innovation process have been considered as the most critical ones. During these phases, the innovation process can emerge or conclude. External knowledge acquirement and utilization are noticed to be important at this stage of the innovation process giving information about the development of future markets and needs for new innovative businessideas. To make it possible, new methods and approaches to manage proactive knowledge creation and sharing activities are needed. In this study, knowledge creation and sharing in the early phases of the innovation process has been studied, and the understanding of knowledge management in the innovation process in an open and collaborative context advanced. Furthermore, the innovation management methods in this study are combined in a novel way to establish an open innovation process and tested in real-life cases. For these purposes two complementary and sequentially applied group work methods - the heuristic scenario method and the idea generation process - are examined by focusing the research on the support of the open knowledge creation and sharing process. The research objective of this thesis concerns two doctrines: the innovation management including the knowledge management, and the futures research concerning the scenario paradigm. This thesis also applies the group decision support system (GDSS) in the idea generation process to utilize the converged knowledge during the scenario process.

Are Evaluation of ICTs Investment Using Decision Support Systems:Case Applications from Distributor's and End User's Perspective Group Decision

The evaluation of investments in advanced technology is one of the most important decision making tasks. The importance is even more pronounced considering the huge budget concerning the strategic, economic and analytic justification in order to shorten design and development time. Choosing the most appropriate technology requires an accurate and reliable system that can lead the decision makers to obtain such a complicated task. Currently, several Information and Communication Technologies (ICTs) manufacturers that design global products are seeking local firms to act as their sales and services representatives (called distributors) to the end user. At the same time, the end user or customer is also searching for the best possible deal for their investment in ICT's projects. Therefore, the objective of this research is to present a holistic decision support system to assist the decision maker in Small and Medium Enterprises (SMEs) - working either as individual decision makers or in a group - in the evaluation of the investment to become an ICT's distributor or an ICT's end user. The model is composed of the Delphi/MAH (Maximising Agreement Heuristic) Analysis, a well-known quantitative method in Group Support System (GSS), which is applied to gather the average ranking data from amongst Decision Makers (DMs). After that the Analytic Network Process (ANP) analysis is brought in to analyse holistically: it performs quantitative and qualitative analysis simultaneously. The illustrative data are obtained from industrial entrepreneurs by using the Group Support System (GSS) laboratory facilities at Lappeenranta University of Technology, Finland and in Thailand. The result of the research, which is currently implemented in Thailand, can provide benefits to the industry in the evaluation of becoming an ICT's distributor or an ICT's end user, particularly in the assessment of the Enterprise Resource Planning (ERP) programme. After the model is put to test with an in-depth collaboration with industrial entrepreneurs in Finland and Thailand, the sensitivity analysis is also performed to validate the robustness of the model. The contribution of this research is in developing a new approach and the Delphi/MAH software to obtain an analysis of the value of becoming an ERP distributor or end user that is flexible and applicable to entrepreneurs, who are looking for the most appropriate investment to become an ERP distributor or end user. The main advantage of this research over others is that the model can deliver the value of becoming an ERP distributor or end user in a single number which makes it easier for DMs to choose the most appropriate ERP vendor. The associated advantage is that the model can include qualitative data as well as quantitative data, as the results from using quantitative data alone can be misleading and inadequate. There is a need to utilise quantitative and qualitative analysis together, as can be seen from the case studies.

Strategic groups and performance: an empirical analysis of strategic groups in the wind energy industry in Europe

The strategic group theory provides an intermediate level of analysis between a single company and the whole industry for identifying issues about the company's competitive position and strategic choices. Strategic groups are companies within an industry with similar strategic characteristics or competing on similar bases. Strategic choices are aligned with the firms’ resources. The purpose of this study was to identify the strategic groups in the wind energy industry in Europe, and study, whether a certain group membership results in financial performance differences. Altogether 80 European wind energy companies were included in the study, which were clustered into four strategic groups according to their age and growth rate. Each group corresponds to a different strategy. The results show that the wind energy companies can be clustered according to the chosen strategic characteristics. Strategic decisions were investigated with characteristic variables. Performance variables were used in the analysis measuring profitability, liquidity and solvency of the groups. These strategic choices of the companies did not have a significant influence on the firms’ performance. The more mature and slower growing group proved to be the most successful. However, the differences between groups were generally not statistically significant. The only statistically significant difference found was in the solvency ratio between Mature Slow and Young Rapid groups. Measured with these variables, more mature and slower growing companies performed better. Therefore, a certain strategic group membership results in performance differences.

Engendering Group Support Based Foresight for Capital Intensive Manufacturing Industries - Case Paper and Steel Industry Scenarios by 2018

In recent times of global turmoil, the need for uncertainty management has become ever momentous. The need for enhanced foresight especially concerns capital-intensive industries, which need to commit their resources and assets with long-term planning horizons. Scenario planning has been acknowledged to have many virtues - and limitations - concerning the mapping of the future and illustrating the alternative development paths. The present study has been initiated to address both the need of improved foresight in two capital-intensive industries, i.e. the paper and steel industries and the imperfections in the current scenario practice. The research problem has been approached by engendering a problem-solving vehicle, which combines, e.g. elements of generic scenario process, face-to-face group support methods, deductive scenario reasoning and causal mapping into a fully integrated scenario process. The process, called the SAGES scenario framework, has been empirically tested by creating alternative futures for two capital-intensive industries, i.e. the paper and steel industries. Three scenarios for each industry have been engendered together with the identification of the key megatrends, the most important foreign investment determinants, key future drivers and leading indicators for the materialisation of the scenarios. The empirical results revealed a two-fold outlook for the paper industry, while the steel industry future was seen as much more positive. The research found support for utilising group support systems in scenario and strategic planning context with some limitations. Key perceived benefits include high time-efficiency, productivity and lower resource-intensiveness. Group support also seems to enhance participant satisfaction, encourage innovative thinking and provide the users with personalised qualitative scenarios.