In this paper one research will be presented, which is focusing on the factors of decision making in the tourism sector. Health and wellness tourism have become a major trend in the past years, since more and more consumer care about their health.
The stressful life, people live nowadays also lead to increased health risk which justifies the growing need for relaxation during the holidays as well. In the study we also present the factors of an analysis and the key motivators when deciding about the destination.
As they say, money can’t buy happiness. However, the lack of it can make people’s lives much harder. From the moment we open our first bank account, we have to make lots of financial decisions in our life. Should I save some money or should I spend it? Is it a good idea to ask for a loan? How to invest my money? When we make such decisions, unfortunately we sometimes make mistakes, too. In this study, we selected seven common decision making biases - anchoring and adjustment, overconfidence, high optimism, the law of small numbers, framing effect, disposition effect and gambler’s fallacy – and tested them on the Hungarian population via an online survey. In the focus of our study was the question whether the presence of economic knowledge helps people make better decisions? The decision making biases found in literature mostly appeared in the sample as well. It proves that people do apply them when making decisions and in certain cases this could result in serious and costly errors. That’s why it would be absolutely important for people to learn about them, thus increasing their awareness and attention when making decisions. Furthermore, in our research we did find some connection between decisions and the knowledge of economics, people with some knowledge of economics opted for the better solution in bigger proportion
Adebayo Owolabi Oyetubo, Oluwaseyi Joseph Afolabi and Muhammed Etudaiye Ohida
Road traffic accident is one of the major causes of death in Nigeria. Road accidents have taken away so many lives in Nigeria today that hardly does any single disease match its mortality prowess. People have died prematurely and properties worth several millions of Naira have been lost as a result of road traffic accident. This paper gives a full discussion on road traffic safety issues and the methodology used were through the collection of data using questionnaire and accident information from the Nigeria Police Force, FRSC etc. The primary information for this research was sourced through the use of structured questionnaire, personal observation and interviews of road users in the study area. Secondary data emanated from published and unpublished sources such as government records, internet, journals, books etc. The findings were presented in descriptive and inferential form using frequencies, percentages, tables, mean and chi-square analytical techniques. The findings from the study revealed among many others; that Male involved more in road accident compare to female counterpart in Minna Niger State. Private car had more accident compare to Taxi, The number of accident in each zone does not depend on the population of that zone, etc.
Daniel Adrian Doss, David Mcelreath, Rebecca Goza, Raymond Tesiero, Balakrishna Gokaraju and Russ Henley
This research examined quantitatively in-port grain loading levels during the periods preceding and succeeding selected human-made and natural disasters among U.S. Gulf Coast ports. The array of selected disasters consisted of the 2010 British Petroleum oil spill, the 2011 Mississippi River flood, Hurricane Katrina, Hurricane Gustav, and Hurricane Isaac. The outcomes of the analyses showed that the examined in-port Gulf Coast grain loading activities have not fully recovered and achieved the level of normalcy that existed before the examined cataclysms.
This paper applies a non-parametric method to provide level technical efficiency for 7 Tunisian ports during 18 years (1998-2015). These ports represent different data set. The use of the model of variable returns to scale (VRS) has led to interesting results. The results show that the most ports are characterized by low levels of technical efficiency, with the exception port of Rades. In addition, the result shows the variation of variable returns to scale and constant returns to scale of technical port’s efficiency. Furthermore, we concluded that the panel data improves the efficiency estimates.
Olusogo Ogunleye, Akinyemi Ajibola, Oluwafemi Enilolobo and Olufolakemi Shogunle
The study investigated the effects of road transport infrastructure on agricultural sector development in Nigeria from 1985 to 2014, using secondary annual time series data on agricultural development (proxy by gross domestic product in the Agric sector) road transport infrastructure (proxy by length of paved road per square kilometer of area) export and capital, all obtained from the Central Bank of Nigeria (CBN) , and National Bureau of Statistics (NBS) , statistical bulletins. The data were analyzed using Granger Causality test and Ordinary Least Square estimation techniques. The study concluded that a positive and statistically significant relationship exists between road transport infrastructures (LRT) also evidence was found of a unidirectional causality from agricultural sector development to transport infrastructure. The study, therefore, recommends that adequate and timely maintenance of existing roads should be carried out as well as enacting appropriate regulations that ensure proper implementation and completion of new road construction contracts in the country in order to boost agricultural sector development, reduce wastage of farm produce and increase the possibility of economic diversification.
Successful companies are continually striving to streamline costs and optimize processes, enabling them to grow progress, develop and ensure competitiveness on the market. A large part of the costs arises in warehouses, where up to 55% of total costs are generated by order-picking, which makes it important and interesting in terms of research. The paper explores “picker to part” order-picking concept, which enables flexible work and is the optimal choice for most companies. The concept is associated with a high level of work-related injuries and work-related illnesses. Work requires physical efforts resulting from handling heavy goods, performing repetitive movements and using manipulative means. Human as the main actor of the concept affects the costs caused by picking and the quality of work done, which depends on technological support, physically and psychologically capable and motivated people. Due to the high costs of service, the focus on time planning and productivity increases. Contrary, the lack of attention is paid to the working conditions and the health status of the pickers. To overcome this gab, a review of scientific and professional literature on ergonomic principles in picking concept »picker to part« was carried out, followed by a quantitative survey of ergonomic properties in warehousing activities. Results revealed that more than 60% of the surveyed order-pickers associate problems with health with the characteristics of work, about 24% of them associate health problems with the use of a particular means of transport, and all agree that provided measures to reduce physical effort and greater support of technologies influence on increased speed of work and better health status of order-pickers.
Currently, we are witnessing the emergence and abundance of many different data repositories and archival systems for scientific data discovery, use, and analysis. With the burgeoning of available data-sharing platforms, this study addresses how scientists working in the fields of natural resources and environmental sciences navigate these diverse data sources, what their concerns and value propositions are toward multiple data discovery channels, and most importantly, how they perceive the characteristics and compare the functionalities of different types of data repository systems. Through a user community research of domain scientists on their data use dynamics and insights, this research provides strategies and discusses ideas on how to leverage these different platforms. Furthermore, it proposes a top–down, novel approach to the processes of searching, browsing, and visualizing for the dynamic exploration of environmental data.
The identification and tracking of technology trends in an industry is crucial for effective information management, as well as for companies to maintain their competitive edge in a changing technological environment. A novel method that combines patentometrics, time series analysis, and social network analysis is proposed to capture the evolution of technology topics and to monitor the vicissitudes of dominators. Taking patents in the solar cell field as an example, a total of 3,820 patents issued between 1997 and 2011 were collected from the United States Patent and Trademark Office database. We divided the examined time span into five 3-year periods, during which the technology dominators, who are the major contributors of patents in a technological field, were identified. These key assignees were also classified as stable, appearing, or exiting based on their transition patterns from one time period to the next. Results show that solar cell patents can be grouped into eight major technology communities, and that the frequency of change in technology dominators across the years varied for each community. We further examined the relationship between a technology dominator’s transition pattern and the changes in its patent characteristics. The appearing technology dominators were found to have increased values for several patent characteristics, including science linkage, pendency period, originality index, and endogeneity index, while their technology cycle time decreased; the stable technology dominators exhibited decreasing science linkage and originality index values; and exiting technology dominators showed trends in patent characteristics that were opposite to that of the appearing technology dominators. By using the methodology proposed in this study, companies can gain critical insights into the major trends of a technological field, which would be invaluable to the planning and assessment of a company’s research-and-development strategies.
The Simple Protocol and RDF Query Language (SPARQL) query language allows users to issue a structural query over a resource description framework (RDF) graph. However, the lack of a spatiotemporal query language limits the usage of RDF data in spatiotemporal-oriented applications. As the spatiotemporal information continuously increases in RDF data, it is necessary to design an effective and efficient spatiotemporal RDF data management system. In this paper, we formally define the spatiotemporal information-integrated RDF data, introduce a spatiotemporal query language that extends the SPARQL language with spatiotemporal assertions to query spatiotemporal information-integrated RDF data, and design a novel index and the corresponding query algorithm. The experimental results on a large, real RDF graph integrating spatial and temporal information (> 180 million triples) confirm the superiority of our approach. In contrast to its competitors, gst-store outperforms by more than 20%-30% in most cases.