Search Results (6)

The relationship between Nile flood variability and Egyptian political stability has been studied since Barbara Bell’s pioneering work in the 1970s, yet precise causal mechanisms linking environmental stress to societal crisis have remained elusive due to chronological limitations. This paper presents a methodological framework achieving annual to decadal resolution through volcanic forcing of the East African Monsoon. Large volcanic eruptions disrupt atmospheric circulation, suppressing monsoon rainfall over the Ethiopian Highlands and reducing Nile summer floods with impacts precisely dated through ice core chronologies (±1–2 years). Applied to Ptolemaic Egypt (305–30 BCE), this methodology demonstrates that volcanic-induced flood failures significantly increased revolt probability (p < 0.02) and correlated with land sales, warfare cessations, and economic stress indicators. Statistical validation distinguishes causal relationships from chance correlations, while comparative analysis of early versus late Ptolemaic responses reveals how political legitimacy, fiscal capacity, and institutional strength determined societal resilience versus vulnerability to environmental shocks. This approach achieves temporal resolution beyond the century-scale resolution of previous studies, determining temporal sequence essential for establishing causation. The methodology is replicable across historical contexts where documentary sources overlap with ice core volcanic chronologies, offering a template for integrating paleoclimatic precision with historical analysis to understand human–environment interactions in past societies. Full article

The growing demand for ecological products is in line with the trend towards the ecologisation of consumption, which has become key in times of striving to achieve sustainable development that aims to satisfy consumer needs while respecting the natural environment and future generations. The shaping of pro-ecological attitudes and behaviours in consumers requires continuous monitoring of such behaviours on the market of ecological products and investigation of the factors that influence consumers’ decisions and market choices. The aim of the article is to present the motives behind the purchase of ecological products, and the factors that shape the purchasing decisions of these products by Polish consumers. The article is based on an in-depth study of the literature and the results of proprietary empirical quantitative research conducted on a national sample of 1032 respondents, of whom 509 had purchased an ecological product within the last 3 months, and 523 had not made such a purchase in this period. Analysis of the results revealed the motives for purchasing ecological products, divided into egotistical motives and altruistic motives. The variation in these motives was also indicated depending on the socio-demographic characteristics of the consumers studied. It was shown that there is a dependency between consumers’ self-assessment of their level of knowledge on the functioning of the natural environment and the effect of humankind on it, and the purchase of ecological products. Analysis was also conducted of the factors perceived by consumers as restricting the purchase of ecological products, as well as the likelihood of a growth in the demand for and consumption of such products. There was shown to be a dependency between the reasons perceived by respondents for restricting the purchase of ecological products or the decision not to make such purchases, and consumer attitudes towards ecology. Full article

The intention of this paper is to provide new academic insights regarding an economically explainable valuation of transfer prices for European football players based on mathematical modeling. Football is the most popular sport in the world followed by approximately 3.5 billion people. The increasing commercialization and professionalization of the industry implies that every area of a football club is constantly put to the test for improvements. Especially after suffering financially under the consequences of the worldwide pandemic, clubs focus not only on sporting success but also on financial survival. Only financially stable clubs have the resources to be more successful. An expensive team does not have to be successful in terms of sports performance. However, a successful team in sports is expensive in the long run. Increasing digitalization offers new revenue potentials for football clubs that focus on selling merchandise in addition to gameday revenues and its media exploitation rights. However, player transfers have become increasingly important because these costs and revenues increased substantially in the relevance of a club’s financial situation. Regarding transfer costs, the question arises as to how transfer fees are determined and which factors have a major influence here. Clubs try to find new ways of evaluating the potential profit of player transfers to lower the risk of failed player investments. The aim of this article is to quantify the popularity of a football player in terms of his merchandising potential to amortize his transfer price. The mathematically formulated relationship calculates a reference value for a player, taking performance, age, number of customers purchasing merchandise, and player position into account. The information gained can be used by managers of European football clubs as a guide in transfer negotiations. For 6907 players of the European top leagues, we analyzed data in the period from 2003 to 2019. For 409 players in the season of 2018/2019 complete data sets were available, so that a model for calculating a theoretical transfer fee for a player during that season could be determined. The results of the study and the developed model suggest that, based on the available data, a football club should offer either one-year or three-year contracts to a transferred player, depending on the anticipated profit margin of merchandise sales and the quota of potential buyers of the products representing a percentage of the number of customers purchasing merchandise. This information gives football club’s management the chance to make better transfer decisions for the individual situation of the player and the club itself. Due to the increased importance of transfers on a football club’s financial performance, better transfer decision making leads to an improved financial stability of the respective clubs and eventually to sporting success. Full article

A Long Short Term Memory (LSTM) based sales model has been developed to forecast the global sales of hotel business of Travel Boutique Online Holidays (TBO Holidays). The LSTM model is a multivariate model; input to the model includes several independent variables in addition to a dependent variable, viz., sales from the previous step. One of the input variables, “number of active bookers per day”, is estimated for the same day as sales. This need for estimation requires the development of another LSTM model to predict the number of active bookers per day. The number of active bookers is variable, so the predicted is used as an input to the sales forecasting model. The use of a predicted variable as an input variable to another model increases the chance of uncertainty entering the system. This paper discusses the quantum of variability observed in sales predictions for various uncertainties or noise due to the estimation of the number of active bookers. For the purposes of this study, different noise distributions such as normalized, uniform, and logistic distributions are used, among others. Analyses of predictions demonstrate that the addition of uncertainty to the number of active bookers via dropouts as well as to the lagged sales variables leads to model predictions that are close to the observations. The least squared error between observations and predictions is higher for uncertainties modeled using other distributions (without dropouts) with the worst predictions being for Gumbel noise distribution. Gaussian noise added directly to the weights matrix yields the best results (minimum prediction errors). One possibility of this uncertainty could be that the global minimum of the least squared objective function with respect to the model weight matrix is not reached, and therefore, model parameters are not optimal. The two LSTM models used in series are also used to study the impact of corona virus on global sales. By introducing a new variable called the corona virus impact variable, the LSTM models can predict corona-affected sales within five percent (5%) of the actuals. The research discussed in the paper finds LSTM models to be effective tools that can be used in the travel industry as they are able to successfully model the trends in sales. These tools can be reliably used to simulate various hypothetical scenarios also. Full article

Crowdfunding has mostly been used to finance very unique projects. Recently, however, companies have begun using it to finance more traditional products where they compete against other sellers of similar products. Major crowdfunding platforms, Kickstarter and Indiegogo, as well as Amazon have launched several projects consistent with this trend. This paper offers a model where two competing firms can use crowdfunding prior to direct sales. The model provides several implications that have not yet been tested e.g., (1) Firms can use crowdfunding strategically to signal a high level of demand for their products; (2) (Reward-based) crowdfunding is procyclical; (3) A higher platform fee may lead to higher firm profits in equilibrium; (4) Competition increases the chances of using crowdfunding compared to the monopoly case; (5) A non-monotonic relationship exists between the risk of crowdfunding campaign failure and firm profit. Full article

Recent housing policies include measures for home purchase control and shanty town redevelopment. This study proposes sustainable pricing, in that the long-run equilibrium price is determined by the fundamentals of house prices. We argue that changes in CPI might have led to rapidly growing house prices and rather high price levels. We investigate the long-run or short-run impacts of new commodity housing completions, transacted square meters of commodity housing, and CPI for house prices in Shanghai. We adopt monthly data for the period of 2005–2010. We test for unit roots using both the ADF and PP techniques and structural breaks using both the Zivot-Andrews (Model B) and Perron (Model C) methods. Considering Cheung-Lai and Reinsel–Ahn finite-sample corrections, the results suggest a long-run equilibrium. Housing completions negatively impact house prices in the short run. A positive volume-price relationship is suggested. Housing sales affect house prices in the short run but not vice versa. Hence, the empirical evidence supports the search model. In addition, CPI is strongly exogenous with respect to the long-run relationship and thus is a long-term determinant of house prices. CPI also positively and drastically influences house prices in the short run. Therefore, a reduction in inflation rate could stabilize house prices, increasing the chances of sustainable prices in the future. Full article