Innovation are considered as the engine of sustainability and economic growth. Innovations are an integral part of the business that is expressed in scientific and research activities. If a company want to gain competitive advantage, it must do the business activities in accordance with economic, environmental, social and institutional factors. Business activities in this area are reflected in macroeconomic indicators of the country. This article deals with innovations and sustainable development issues. The main goal of research is testing interaction between innovations and sustainable development through the selected indicators. Summary Innovation Index (SII) represents innovations and sustainable development is represented by the set of indicators from four areas: economic, environmental, social and institutional. The analysis is based on values of the Summary Innovation Index proposed by the European Commission to measure the competitiveness of European countries in terms of innovation activity and values of sustainable development indicators such as GDP per capita, energy intensity of the economy, migration, transport performance, greenhouse gas emissions, application of environmental management system, mining and consumption of mineral resources, etc. The research is carried out on the case of Slovakia with application of mathematical-statistical apparatus (correlation analysis). The main benefit of research lies in the identification of strengths and weaknesses of Slovakia in analysed areas and determining the expected development.
Research purpose. The aim of the paper is to create a model that allows building an optimal brand portfolio, allowing an organisation to achieve its goals. The created model is based on the bivalent programming theory. A mathematical model of optimum brand portfolio is created based on linear programming with restricting conditions being the maximum acceptable risk level and budget. The basic types of resources and basic types of relations between brands are explained, which are part of the process of brand portfolio optimization.
Design / Methodology / Approach. Knowledge and many years of experience of mainly economic disciplines were used for the selection of characteristics for brand portfolio specified in this article. Our assumptions were based mainly on project portfolio management, operational analysis and linear programming as well as tools and methods of graph theory.
Findings. Brand portfolio management such as creating, planning, organising and then maintaining a successful brand is a costly and long-term process involving effective marketing strategies and decisions. The prerequisite for brand portfolio creation is deciding on the number and type of brands. A properly constructed brand portfolio is a prerequisite for achieving business goals.
Originality / Value / Practical implications. Brand portfolio optimisation requires sufficient attention; however, rather than the selection of the highest number of brands, it should be based on compilation of a set, according to pre-defined priorities, which would provide the best possible means to meet the company’s goals for the current limitations. It should be implemented upon objective rules (in our case maximum allowable risk level and available budget). Frequent changes in the brand portfolio structure are not beneficial since they reduce the ability for the company to achieve its targets and represent excessive use of resources. In addition, qualitative brand characteristics have to be respected in the brand portfolio management, but this was not covered in our research.
In May 2007, the Ministry of Education, Science, Research and Sport of the Slovak Republic approved the National Program for Learning Regions. It states that the long-term strategic objective for the development of Slovak regions is the gradual reduction of disparities in living standards in regions and to improve regional economic performance. One of the tools for achieving this goal is considered the learning region concept. The main aim of this article is to streamline the presentation and monitoring of the partial progress made in achieving the objectives of the National Program for Learning Regions in the Slovak Republic to policy-makers and to make this relatively complex issue accessible to a wider audience through one aggregated index and two partial indices; the PCA method was used. The results showed relatively large differences between regions. The highest value of the aggregated LR index was reached by the Trnava region, followed by the Bratislava region; these two regions seems to be in accordance with reaching the objectives of the National Program for Learning Regions. The lowest values were found in the Banská Bystrica, Prešov and Košice regions. Moreover, we found a positive correlation between aggregated and economical-innovative indices with average GDP during the years 2008–2014 at the NUTS 3 level.
Customers are key in the brand-building process. Many times, this term is applied very broadly, especially in segmentation and planning. Knowing the customer buying behaviour and customer decision-making process is important for brands, especially today, when customers are informed much better and get information over the Internet faster. In this paper, we present theory that deals with the purchasing behaviour of customers and emphasize the analysis of the sales cycle of the individual phases in the current conditions, when segmentation based on socio-demographic data is not enough. It is much better to define the psychological factors, which influence the customer and motivate him to buy in combination with the buyer’s decision-making speed. Thus, the article discusses the basic four types of customers according to the major research work carried out by Eisenberg brothers. Based on this analysis, we can determine the percentage of individual customers. The article offers a survey that was conducted to find the most important factors in the decision-making process when buying a car. In addition to the criteria, we also asked our respondents about the importance of these factors. We have used the multiple criteria decision analysis as it is one of the methods of complex evaluation and it minimizes the degree of subjectivity in choosing a suitable variant. Based on our survey, we have used analysis to estimate trends that brands operate in automotive sector could use to communicate in order to address the type of customer that belongs to their target audience. The primary aim of the paper is to prove that there is a growing trend of humanistic customers through study about their preferences and criteria during the decision-making process that leads them to buy a new car. Moreover, we determinate communication strategies for all four types of customers based on theory provided by Eisenbergs.
Background and Purpose: The field of innovation represents for small and medium enterprises (SMEs) a fundamental challenge. If the number of innovative SMEs is to rise, it is necessary to identify key factors determining their innovation activity and eliminate the innovation barriers. The main purpose of the paper is to present the results of primary research focused on identification (evaluation) of key factors and barriers determining innovation activities in Slovak SMEs. The division of SMEs into three groups of enterprises: innovation leaders, modest innovators and non-innovators enables to identify the differences in managers’ perception of the main factors and barriers determining innovation activities in various types of SMEs and to formulate policy implications for Slovak SMEs.
Design/Methodology/Approach: Results of the empirical research were processed using MS Excel and the statistical analysis of the data in R3.2.4. statistical system was done. For statistical tests we assumed significance level (α = 0.1).
Results: Evaluating the importance of the key factors a majority of enterprises (64.71%) indicated financial resources as the most important factor for the innovations. There is no statistically significant difference in individual (analysed) factors between innovation leaders, non-innovators and innovation followers (modest innovators). The results gained from Fisher exact test (p-value = 0.11) indicated a small difference in evaluating the significance of individual barriers between innovation leaders, non-innovators and modest innovators. Majority of enterprises also see as the main barriers to develop innovation activities bureaucracy and corruption and inappropriate state support of innovation activities.
Conclusion: The main implications (conclusion) coming from the research are basic recommendations for state policy makers as well as SME’s managers to foster innovation activities in enterprises. They refer to the areas of financial resources, high-quality human resources, cooperation and participation of SMEs in different networks and clusters, systematic institutional support to SMEs, well-created vision and clearly formulated aims, and willingness of enterprises to innovate. Recommendations are summarised following the results of factor’s and barrier’s evaluation.