The main focus of this paper is to propose a method for prioritizing knowledge and technology factor of firms towards sustainable competitive advantage. The data has been gathered and analyzed from two high tech start-ups in which technology and knowledge play major role in company’s success. The analytical hierarchy model (AHP) is used to determine competitive priorities of the firms. Then knowledge and technology part of sense and respond questionnaire is used to calculate the variability coefficient i.e. the uncertainty caused by technology and knowledge factor. The proposed model is tested in terms of two start-ups. Based on the initial calculation of uncertainties, some improvement plan is proposed and the method is applied again to see if the uncertainty of knowledge and technology decreases. In both cases, the proposed model helped to have a clear and precise improvement plan and led in reduction of uncertainty.
This article presents the use of a multi-criterion Analytic Hierarchy Process (AHP) method to assess geological and mining condition nuisance in longwall mining operations in selected coal mines in Poland. For this purpose, a methodology has been developed which was used to calculate the operational nuisance indicator (WUe) in relation to the cost of mining coal in individual longwalls. Components of the aggregate operational nuisance indicator include four sub-indicators: the natural hazards indicator (UZN), an indicator describing the seam parameters (UPZ), an indicator describing the technical parameters (UT) and an environmental impact indicator (UŚ). In total, the impact of 28 different criteria, which formed particular components of the nuisance indicators were analysed. In total 471 longwalls in 11 coal mines were analysed, including 277 longwalls that were mined in the period of 2011 to 2016 and 194 longwalls scheduled for exploitation in the years 2017 to 2021. Correlation analysis was used to evaluate the relationships between nuisance and the operating costs of longwalls. The analysis revealed a strong correlation between the level of nuisance and the operating costs of the longwalls under study. The design of the longwall schedule should therefore also take into account the nuisance arising from the geological and mining conditions of the operations. Selective operations management allows for the optimization of costs for mining in underground mines using the longwall system. This knowledge can also be used to reduce the total operating costs of mines as a result of abandoning the mining operations in entire longwalls or portions of longwalls that may be permanently unprofitable. Currently, underground mines do not employ this optimization method, which even more emphasizes the need for popularizing this approach.
The difficulty of innovation risk assessment makes it necessary to use a multi-criteria analysis. Innovative projects are related to unstructured problems and the uncertainty, therefore, the use of fuzzy logic in the innovation risk assessment is analyzed. This paper proposes a method of determining the weights of criteria in order to innovation risk assessment. The weights are determined by 5 general criteria and 14 detailed criteria of innovation risk assessment. The proposed method is an extension of the fuzzy AHP method. The extension consists in taking into consideration the group decision-making approach with experts’ psychological conditions. The groups of experts have been chosen based on an elaborated form. The form makes it possible to characterize the persons within the scope of different psychological conditions. The proposed method provides objective and rational decision-making. The paper presents also a comparison of results with the fuzzy AHP method without the group decision making. The weights obtained by the proposed method are more diversified and bring out the most important criteria.