The purpose of this paper is threefold: to adapt the innovation diffusion models to describe and predict the diffusion of private pension provision; to evaluate the suitability of diffusion models based on the historical data from the Romanian and Ukrainian voluntary pension systems; and to compare the diffusion parameters of private pension provision in these countries. The study proven that diffusion models, such as the Rogers model and the Bass model, can reproduce the diffusion of innovations in the field of pensions. The Rogers diffusion parameters for Romania and Ukraine are almost identical; this gives grounds for a conclusion about the similar behavioral patterns in post-socialist countries. However, some limitations on models use are noted. During the crisis and when using the nudge mechanism, models are not always well-fitting, but when new pension schemes are introduced or new pension funds are opened, models can be used in “guessing by analogy”.
The aims of this research is to contribute to the literature and the conceptual model of the effect of relational capital on network advantage and business performance, the effect of network competence on network advantage and business performance, the effect of knowledge sharing on network advantage and business performance and the effect of network advantage and business performance. The number of samples in this study examined was 289 sample SMEs Furniture on Central Java Indonesia. The purposive sampling technique was used to the data collection methods. The results of this study showed that relational capital is a significant negative effect on business performance and positive significance on network advantage. Network competence is a significant effect on business performance and negative impact on network advantage. Network competency is a significant effect on business performance and network advantage. Relational capabilities is a significant effect on business performance and network advantage. Network advantage is a significant effect on business performance.
Rui Pedro Brito, Helder Sebastião and Pedro Godinho
This paper analyzes empirically the performance gains of using high frequency data in portfolio selection. Assuming Constant Relative Risk Aversion (CRRA) preferences, with different relative risk aversion levels, we compare low and high frequency portfolios within mean-variance, mean-variance-skewness and mean-variance-skewness-kurtosis frameworks. Using data on fourteen stocks of the Euronext Paris, from January 1999 to December 2005, we conclude that the high frequency portfolios outperform the low frequency portfolios for every out-of-sample measure, irrespectively to the relative risk aversion coefficient considered. The empirical results also suggest that for moderate relative risk aversion the best performance is always achieved through the jointly use of the realized variance, skewness and kurtosis. This claim is reinforced when trading costs are taken into account.
Rapid development of technology, particularly in the field of artificial intelligence, has fuelled the concept of Industry 4.0 among all types of businesses across the globe. This has driven sustainable growth for those businesses as well as promoted economic prosperity in the countries where they operate in. In view of this information, it is of absolute importance that the entire business landscape in Turkey avails itself to greater awareness and education about the benefits of embracing a comprehensive Industry 4.0 philosophy. It is also important to shed the light on the problems these businesses may face in transition from the old industrial philosophies to the new philosophy of Industry 4.0. Therefore, the aim of this study is to measure the level of Industry 4.0 awareness among businesses in Turkey. The research also seeks to determine how targeted Industry 4.0 educational programs and policies vary in relation to the demographic characteristics among some business operators in Turkey. A multiple case study design governed this entire research. Thus, views and in-depth data from 32 companies based in Turkey were collected by questionnaire and subsequently analysed in a detailed format. At the end of the study, the findings revealed that Industry 4.0 awareness differed depending on the employees’ levels of education. The researchers also discovered that the status or extent of relationships these companies had with foreign partners abroad has a significant impact on the awareness levels of Industry 4.0.
Contemporary third-party logistics (3PL) companies tend to broaden their competences in different fields and apart from traditional logistics services provide various value-added services to their customers. A systematic approach of 3PL resource management, as well as performance and quality indicator measurement are needed to forecast development of key performance indicators of a company. The purpose of this study is to discover contemporary tendencies of 3PL with regard to resources, performance and quality related issues, to determine resources, processes and quality indicators of 3PL, and to develop a system dynamics model for optimization of internal resources and processes of a company. The paper provides a systematic review of literature related to management of 3PL resources, quality and performance measurement. A model of management and optimization of 3PL resources and internal processes is developed by applying System Dynamics. The developed model consists of six blocks, namely, commercial activities, operations, procurement, administration, personnel management and quality management, representing different areas of internal activities of 3PL.
This research aims to answer the question if e-commerce favoured in a special way the growth of low-cost carriers within the civil aviation market. After defining low-cost and traditional carriers’ business models, data on transported passengers were collected for three countries (Italy, Germany and Spain) and confronted with the number of e-consumers. Despite a significant correlation in all the three markets, only in Italy our hypothesis has been supported by Granger causality, and the regression analysis allows to forecast a future characterized by a growing dominance of LCCs. Although the definition of an econometric model will require further studies, the distinctive features of the Italian market might represent a starting point for future research on the complex relationship between e-commerce and air transport.
Francisco Flores Muñoz, Diego Valentinetti, María Mora Rodríguez and Ángel Mena Nieto
This paper proposes a measurement method for assessing the extent to which the XBRL digital standard eXtensible Business Reporting Language can assist firms in implementing their reporting when applying EMAS The EU Eco-Management and Audit Scheme. A specific survey based on the work of (Bunker et al., 2007), which uses Value Compatibility, was carried out at the most important firms in Southern Spain. Different sectors were involved in the study: public hospital, copper manufacturing facilities, petrochemical plant and pulp and renewable energy production. The results reveal some concordances between EMAS using XBRL as a reporting technology, and the cultural, organisational and technical working environment of the analysed firms, specifically those related to the Structural Dimension. By contrast, some discordance is highlighted related to the Practical Dimension. The paper proposes for the first time the application of the global financial standard XBRL for a non financial purpose like the widely accepted EMAS, to actual potential uses in real scenarios. The empirical research combined heavy industry with services, privately owned firms with public entities, private and public sector, in the analysis of this technology. The paper represents a necessary landmark for a subsequent longitudinal study.
Zuzana Brinčíková, Marek Kálovec, Colin W. Lawson and Eva Muchová
Fourteen Slovak state-owned enterprises were studied, using published data and structured interviews with management. A novel methodology is used to assess SOE autonomy, effectiveness, accountability and governance. Variations in operating conditions reflect different government objectives and different ownership models. Mixed state-private firms performed more like competitive firms than did wholly state-owned SOEs. This information was fed into an assessment of Slovak SOEs’ compliance with the 2015 OECD Guidelines on SOE Corporate Governance. There are many differences between Slovak practice and the Guidelines. This may reflect a choice to favour government interests, rather than the OECD’s inclusion of a wider group of stakeholders. One cost is foregone efficiency gains. Another is the perception that the present highly opaque governance system hides corruption.
Marijana Zekić-Sušac, Rudolf Scitovski and Adela Has
Although energy efficiency is a hot topic in the context of global climate change, in the European Union directives and in national energy policies, methodology for estimating energy efficiency still relies on standard techniques defined by experts in the field. Recent research shows a potential of machine learning methods that can produce models to assess energy efficiency based on available previous data. In this paper, we analyse a real dataset of public buildings in Croatia, extract their most important features based on the correlation analysis and chi-square tests, cluster the buildings based on three selected features, and create a prediction model of energy efficiency for each cluster of buildings using the artificial neural network (ANN) methodology. The main objective of this research was to investigate whether a clustering procedure improves the accuracy of a neural network prediction model or not. For that purpose, the symmetric mean average percentage error (SMAPE) was used to compare the accuracy of the initial prediction model obtained on the whole dataset and the separate models obtained on each cluster. The results show that the clustering procedure has not increased the prediction accuracy of the models. Those preliminary findings can be used to set goals for future research, which can be focused on estimating clusters using more features, conducted more extensive variable reduction, and testing more machine learning algorithms to obtain more accurate models which will enable reducing costs in the public sector.
The transfer market of European football can be classified as a system. In this system, the effectiveness of participant teams can depend on the activity in players’ transfers. This article assesses the utility of network analysis in analysing connections between the mentioned concepts. The hypothesis is that there is causality between a club’s activity in the transfer market and its profit from transfers. This research is based on empirical transfer data of major soccer teams, which have had a significant role in the last 12 years in Europe. It is assumed that the most active clubs in the transfer system have more financial power in the transfer market, while teams which are not active in transfers have less profit from transfers. In the network analysis, the teams can be defined as a set of nodes and connected by edges (interactions). The thickness of the edges and the size of the nodes depend on the volume of transfers among clubs. The number of interactions and the amount of the transfer price can measure this volume also. Considering the results of network indices, the relationships between the two phenomena were reviewed. In order to explore these relationships, the correlations among all of the relevant variables in the transfer market were also measured.