Search results

Purpose: This study analyses how investments and specific financial factors affect the financial performance of businesses in Kosovo. Exploring the relationship between investments and financial performance and their impact on performance volatility, performance is assessed using return on assets (ROA) and return on equity (ROE) investments.

Methodology: Quantitative methods using secondary data from audited financial statements of Kosova manufacturing and commercial enterprises cover a 3-year period (2019–2021), involving 40 enterprises with 120 observations. Statistical tests such as descriptive statistics, correlation analysis, linear regression, Hausman–Taylor regression, fixed effects, random effects, and generalised estimating equations (GEE) model are applied. The study also utilises ARCH–GARCH analysis to assess the relationship between investments and performance volatility.

Findings: Investments positively impact the financial performance of Kosova businesses and significantly reduce performance volatility. Long-term liabilities, retained earnings, and short-term liabilities also play a role in reducing asset return volatility, while cash flow from financial activities increases it. Investments, cash flows from financial activities, long-term liabilities, short-term liabilities, retained earnings, and solvency affect equity return volatility.

Practical Implications: The study sheds light on how investments and financial factors influence the financial performance and volatility of Kosova businesses. Policymakers can use these insights to create policies that foster the development of commercial and manufacturing enterprises, given their importance in Kosovo’s economy.

Significance: This research provides valuable insights for business managers to enhance investment strategies and improve financial performance. Policymakers can rely on this academic study to enhance the economic environment and promote the growth of businesses in Kosovo.

The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

A better understanding of the determinants of demand through accurate estimates of the elasticity of import demand can help policymakers and exporters improve their market access and competitiveness. This study analyzed the EU's demand for imported potato from major suppliers between 1994 and 2018, with the aim to evaluate the competitiveness of Egyptian potato.

This study adopted an import-differentiated framework to investigate demand relationships among the major potato suppliers to the EU's. To evaluate the competitiveness of Egyptian potato on the EU market, expenditure and price demand elasticities for various suppliers were calculated and compared.

The empirical results indicated that as income allocation of fresh potatoes increases, the investigated EU markets import more potatoes from other suppliers compared to imports from Egypt. The results show that EU importers may switch to potato imports from other suppliers as the import price of Egyptian potatoes increases, which enter the EU markets before domestically produced potatoes are harvested.

Due to data unavailability, the present study relied on yearly data on quantities and prices of EU potato imports. A higher frequency of observations should allow for considering seasonal effects, and thereby providing a more transparent picture of market dynamics and demand behavior of EU countries with respect to potato import from various sources of origin.

The study used a system-wide and source differentiated approach to analyze import demand. In particular, the empirical approach allowed for comparing different demand models (AIDS, Rotterdam, NBR and CBS) to filter out the superior and most suitable model for that data because the suitability and performance of a demand model depends rather on data than on universal criteria.

Purpose: This study investigates internal/own shock in the domestic market and three external volatility spillovers from India, the UK, and the USA to the Sri Lanka stock market.

Need for the Study: The external market’s internal/own shocks and volatility spillovers influence portfolio choices in domestic stock market returns. Hence, it is required to investigate the internal shock in the domestic market and the external volatility spillovers from other countries.

Methodology: This study employs a quantitative method using ARMA(1,1)-GARCH(1,1) model. All Share Price Index (ASPI) is the proxy for the Colombo Stock Exchange (CSE) stock return. It uses daily time-series data from 1^st April 2010 to 21^st June 2023.

Findings: The findings revealed that internal/own and external shocks substantially impact the stock price volatility in CSE. Significant volatility clusters and persistence with extended memory in ASPI confirm internal/own shock in the market. Furthermore, CSE receives significant volatility shock from the USA, confirming external shock. This study’s findings highlight the importance of considering internal and external shocks in portfolio decision-making.

Practical Implications: Understanding the influence of internal shocks helps investors manage their portfolios and adapt to market volatility. Recognising significant volatility spillovers from external markets, especially the USA, informs diversification strategies. From a policy standpoint, the study emphasises the need for robust regulations and risk management measures to address shocks in domestic and global markets. This study adds value to the literature by assessing the sources of volatility shocks in the CSE, employing the ARMA-GARCH, a sophisticated econometrics model, to capture stock returns volatility, enhancing understanding of the CSE’s volatility dynamics.

This study aims to investigate the effect of monetary policy on housing prices for US economy. It specifically examines whether nominal or real interest rates are the key drivers behind fluctuations in housing prices in US.

Monthly data from January 1991 to July 2023 and various appropriate analytical tools such as unit root tests, Johansen’s cointegration test, vector error correction model (VECM), impulse response function and Granger causality test were applied for the data analysis.

The Johansen cointegration findings reveal the presence of a long-term relationship among the variables. VECM results indicate a negative correlation between nominal and real interest rates and housing prices in both the short and long terms, suggesting that a strict monetary policy can help in controlling the housing price increase in the USA. However, housing prices are more responsive to changes in nominal interest rates than to real interest rates. Additionally, the study reveals that the COVID-19 pandemic contributed to the upsurge in housing prices in the USA.

This study contributes by examining the role that nominal or real interest rates play in shaping housing prices in the USA. Moreover, given the recent significant upsurge in housing prices, this study presents a unique opportunity to investigate whether these price increases are influenced by the Federal Reserve's monetary policy decisions regarding nominal or real interest rates. Additionally, using monthly data, this study provides a deeper understanding of the fluctuations in housing prices and their connection to monetary policy tools.

Open innovation (OI), by now one of the major concepts for the analysis of innovation, is seen as a methodology for collaboratively designing and implementing solutions by engaging stakeholders in an iterative and inclusive service design process. This paper aims to empirically investigate OI capacities, defined as a cooperative, knowledge-sharing innovation ecosystem, and to explore how it can lead to improved performance of firms in Central and Eastern European (CEE) and Southeastern European (SEE) countries.

The study builds on the World Bank/European Bank for Reconstruction and Development (EBRD’s) Business Environment Enterprise Performance Survey (BEEPS) dataset for 2009, 2013 and 2019. Primarily, the research model was estimated using log-transformed ordinary least squares (OLS). Taking into consideration that this method might produce substantial bias, yielding misleading inferences, this study is fitting Poisson pseudo maximum likelihood estimators with robust standard errors and instrumental variable/generalized method of moments estimation (IV/GMM) approach for comparative results. Secondarily, the research model was tested using structural equation modelling (SEM) to investigate the relationship between five OI capacities and firm performance.

The findings indicate that there is a significant positive relationship between most OI capacities and firm performance, except for innovation, which did not show a statistically significant relationship with firm performance. Specifically, research and development (R&D), knowledge and coopetition are statistically significant and positively associated with firm performance, whereas transformation is statistically significant but negatively associated with firm performance. The IV/GMM estimations’ findings support the view that the firm performance is significantly affected by OI capacities, together with some control variables such as size, age, foreign ownership and year dummy to have a significant impact on firm performance.

This paper fills an identified gap in the literature by investigating the impact of OI on firm performance executed in the specific CEE and SEE country context.

This study aims to investigate the spatial distribution of housing prices and identify the affecting factors (independent variable) on the cost of residential units (dependent variable).

The method of the present study is descriptive-analytical and has an applied purpose. The used statistical population in this study is the residential units’ price in Tehran in 2021. For this purpose, the average per square meter of residential units in the city neighborhoods was entered in the geographical information system. Two techniques of ordinary least squares regression and geographically weighted regression have been used to analyze housing prices and modeling. Then, the results of the ordinary least squares regression and geographically weighted regression models were compared by using the housing price interpolation map predicted in each model and the accurate housing price interpolation map.

Based on the results, the ordinary least squares regression model has poorly modeled housing prices in the study area. The results of the geographically weighted regression model show that the variables (access rate to sports fields, distance from gas station and water station) have a direct and significant effect. Still, the variable (distance from fault) has a non-significant impact on increasing housing prices at a city level. In addition, to identify the affecting variables of housing prices, the results confirm the desirability of the geographically weighted regression technique in terms of accuracy compared to the ordinary least squares regression technique in explaining housing prices. The results of this study indicate that the housing prices in Tehran are affected by the access level to urban services and facilities.

Identifying factors affecting housing prices helps create sustainable housing in Tehran. Building sustainable housing represents spending less energy during the construction process together with the utilization phase, which ultimately provides housing at an acceptable price for all income deciles. In housing construction, the more you consider the sustainable housing principles, the more sustainable housing you provide and you take a step toward sustainable development. Therefore, sustainable housing is an important planning factor for local authorities and developers. As a result, it is necessary to institutionalize an integrated vision based on the concepts of sustainable development in the field of housing in the Tehran metropolis.

Brief loving-kindness meditation (LKM) is introduced here as a valid social marketing intervention. LKM positively influences prosocial cognitions and affects. However, it remains unclear whether brief meditation interventions can influence prosocial behavior. This study aims to provide evidence of the effects of short LKM on prosocial behavior.

This study reports the results of three experiments examining the effects of brief LKM on donations to unknown others. The results are then integrated with the results of seven other studies testing the effects of brief LKM on prosocial behavior using a meta-analysis (n = 683).

LKM increased love more than the control group (focused breathing) in the three experiments; however, its effects on donations were mixed. The meta-analysis shows that LKM has a small-to-medium significant effect compared to active control groups (d = 0.303); moreover, age and type of prosocial measure used moderate the effects.

Results suggest that LKM can nurture prosocial emotions such as love and lead young individuals to donate. However, these emotions may not be sufficient to lead adult meditators to share their resources with unknown others. This study presents the first meta-analysis of brief LKM and provides insights into the use of meditation in social marketing programs.