Decreased consumer trust, increased unemployment rate, increased availability of technology for hosting an online market drives the growth of sharing economy. The sharing economy provides an ideal lens to explore and contribute to the sustainable development nature. While the sharing economy can contribute to sustainable development and has plenty of room to develop practical issues in driving sustainability there is a lack of sharing economy sustainability empirical studies. This article seeks to provide an approach how to address and estimate sharing economy business models sustainability. This approach aims to determine key sustainability perspectives by using Circles of Sustainability. Key sustainability perspectives have been taken as input to estimate the level of sustainability. This practice can be served as a useful methodology to support decisions toward to sharing economy business models sustainability transition

The main purpose of the paper is to distinguish theoretical characteristics of city attractive for investments and to prove these attributes by investigating the judgements of enterprisers. This paper is based on systemic, comparative and logical analysis of scientific economic literature, the survey method for drawing practical results.The description of investment attractive city and the factors forming the investment attractiveness are provided in this research. Summing up the theoretical and identified by the entrepreneurs characteristics of the city's attractiveness for investment, it can be said that in many cases the choice of the city for investment is influenced by the accessibility of skilled workforce and its costs, the resource price and competition in the market

The implementation of Industry 4.0 concept brings many risks mainly for small and medium-sized enterprises (SMEs). The objective of the study is a diagnosis and comparison of the perception of selected risk issues connected with Industry 4.0 implementation in Slovak and Polish SMEs, which have knowledge or experience with cluster cooperation. This category of SMEs is specific due to the fact, that not all of the SMEs have experience with cluster cooperation or know this form of doing business. For this purpose, the questionnaire survey of 787 respondents was conducted, focused on the risks of Industry 4.0 that are the most important for SMEs included in three categories: technical readiness, risks of innovation and risks of information. The statistical analysis of the survey results with the application of software STATISTICA and Social Science Statistics calculator leads to the conclusion that, except for the kind of risk of “New products and services”, all the observed risks are perceived as higher by Slovak SMEs than by Polish SMEs. The novelty of this research and its contribution to the body of knowledge lies in identification and evaluation of most important risks for specific group of SMEs related to Industry 4.0 implementation compared in two countries. The results of this research provide useful information for the practical fine-tuning of the policy aimed at transfer to Industry 4.0 in specific field – cluster cooperation, depending on the size of the enterprise.

In modern global market organizations striving for survive and successful compete have not only to satisfy needs of customers but to perform it with the least costs. Specialists of quality management determined that quality costs make a big part of total factor costs, taking about 30 % (Srivastava, 2008). Reducing of quality costs allows reducing of total organizational costs that would result in reducing of price of goods manufactured or services supplied, increase of customers’ satisfaction or improved oeganization performance (Juran, 1951; Crosby, 1979; Heagy, 1991; Tsai, 1998; Moen, 1998; Malchi & McGurk, 2001; Prickett & Rapley, 2001; Love & Irani, 2003; Tannock & Saelem, 2007; Sower, Quarles & Broussard, 2007; Wu et all, 2011). Organizations that have prepared the programs of quality costs accounting adapted to their specific activity and paying more attention to implementation of quality programs, can identify, set in underlying order, evaluate and select quality investments more easy (Bottorff, 1997). Also quality costs programs allow calculation of return of investment to quality, help to find out how development is going (Gray, 1995), determine where highest costs appear and allow to find out what is the loss due to poor quality (Bottorff, 1997). Unfortunately, many organizations don’t know their quality costs (Yang, 2008). Between the reasons determining the absence of quality costs accounting in the organization, following are indicated: use of many types of different accounting systems (Harry & Schroeder, 2000), traditional costs accounting systems are not adapted to identify quality costs data (Chiadamrong, 2003), lack of adequate methods to determine the results of poor quality (Chen & Yang, 2002). Studies performed by Viger & Anandarajan (1999) show that organizations that are calculating and analyzing quality costs, are making efficient decisions more often than those not calculating quality costs. Having calculated the loss due to poor quality and determined where its appearance is the largest, organizations can make decisions allowing optimization of quality costs. While optimizing quality costs, benefit increases (Fine & Charles, 1986; Freiesleben, 2005). Also, optimization of quality costs is a condition necessary to survive and anchor in the market. Quality costs programs were implemented and used worldwide (Carr, 1992, Schiffauerova & Thomson, 2006a. However, both the scientific literature and enterprises’ practice still are having questions how to calculate all constituents of categories of quality costs in details in striving for maximal benefit from the system of accounting of quality costs. In the article there is discussion about the problems of quality costs accounting in striving for detailed calculation of all quality costs, a problem of lack of hidden failure quality costs accounting methodology analyzed, a review of literature on quality costs accounting models presented, the studies performed by other authors discussed, suggestions how to calculate hidden failure quality costs presented. An empirical study was performed in Lithuanian organization where methodology of accounting of constituents of hidden failure quality costs was tested.DOI: http://dx.doi.org/10.5755/j01.ee.24.3.1186

Authors of the article elaborate economic factors and using calculations indicate the influence of these factors on the development of rural tourism. The research results revealed that the number of guests in rural farmsteads (values of correlation coefficient are ranging from 0.73 to 0.91) is strongly affected by all economic factors (excluding inflation) analysed in the research: GDP per capita, average monthly gross earnings, foreign direct investments, government expenditure and revenue, tangible investments per capita. Meanwhile, the development of rural farmsteads are firmly influenced on average gross monthly earnings, foreign direct investments, government expenditure (correlation coefficient is above 0.9)