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This study aims to examine foreign direct investment (FDI) factors and develops a rational framework for FDI inflow in Western European countries such as France, Germany, the Netherlands, Switzerland, Belgium and Austria.

Data for this study were collected from the World development indicators (WDI) database from 1995 to 2018. Factors such as economic growth, pollution, trade, domestic capital investment, gross value-added and the financial stability of the country that influence FDI decisions were selected through empirical literature. A framework was developed using interpretable machine learning (IML), decision trees and three-stage least squares simultaneous equation methods for FDI inflow in Western Europe.

The findings of this study show that there is a difference between the most important and trusted factors for FDI inflow. Additionally, this study shows that machine learning (ML) models can perform better than conventional linear regression models.

This research has several limitations. Ideally, classification accuracies should be higher, and the current scope of this research is limited to examining the performance of FDI determinants within Western Europe.

Through this framework, the national government can understand how investors make their capital allocation decisions in their country. The framework developed in this study can help policymakers better understand the rationality of FDI inflows.

An IML framework has not been developed in prior studies to analyze FDI inflows. Additionally, the author demonstrates the applicability of the IML framework for estimating FDI inflows in Western Europe.

This study aims to analyse the intellectual property rights (INPR), foreign direct investment (FDI) inflows and technological exports of 32 developing and developed countries for the period of 2006–2020.

Diagnostic tests were used to confirm the panel least squares, fixed effect, random effect, feasible general least squares, dynamic ordinary least squares and fully modified ordinary least squares estimator results as well as to increase the robustness.

According to the findings for the developing countries, trademark, patent and industrial design applications, each had a significant positive long-run effect on FDI inflows. In addition, there was a significant positive long-run relationship between patent applications and medium- and high-technology exports. Meanwhile, trademark and industrial design applications had a significant negative long-term effect on medium- and high-technology exports. In developed countries, patent and industrial design applications each have a significant negative long-term on medium- and high-technology exports. Furthermore, patent and trademark applications each had a significant negative long-run effect on FDI inflows.

This study contributes significantly to the focus that host countries evaluate the technology gaps between domestic and foreign investors at different industry levels to select the best INPR rules and innovation process by increasing international cooperation. Furthermore, the host countries should follow the structure–conduct–performance paradigm based on analysis of the market structure, strategic firms and industrial dynamics systems.

Drawing on the literature on brand–consumer relations in an attempt to apply the concept of brand love to a city tourism destination, this paper aims to explore the antecedents and consequences of city brand love.

Based on quantitative research and cluster sampling, study data was collected from 330 international tourists who visited six Iran cities. The research model is tested using partial least square structural equation modeling.

According to the results, city brand attractiveness, city brand identification and memorable city brand experience are the antecedents of city brand love. Moreover, the city brand attractiveness, both directly and indirectly through memorable experiences and identification with the city brand, is one of the antecedents of city brand love. Finally, the results suggest that word of mouth and revisit intention are major behavioral outcomes of city brand love.

By providing a validated conceptual model that traces the antecedents and consequences of city brand love, this study attempts to answer prior calls for examination from the viewpoint of city tourism scholars.

本研究基于定量研究和整群抽样, 研究数据来自访问伊朗六个城市的330名国际游客。研究采用偏最小二乘结构方程模型对研究模型进行了检验。

借鉴品牌-消费者关系的相关文献, 本研究试图将品牌爱的概念应用于一个城市旅游目的地, 探讨城市品牌喜爱的前因和后果。

结果表明, 城市品牌吸引力、城市品牌辨识度和令人难忘的城市品牌体验是城市品牌喜爱的前因。城市品牌吸引力通过城市品牌直接或间接通过难忘体验和认同产生, 是城市喜爱的前因。最后, 研究结果表明, 口碑和重访意愿是城市品牌喜爱的主要行为结果。

通过提供一个经过验证的概念模型, 追溯城市品牌喜爱的前因后果, 本研究试图从城市旅游学者的角度回答先前检验的呼吁。

A partir de una investigación cuantitativa y muestreo por conglomerados, los datos del estudio se recogieron de 330 turistas internacionales que visitaron seis ciudades iraníes. El modelo conceptual se analizó mediante un modelo de ecuaciones estructurales de mínimos cuadrados parciales (PLS).

Basándose en la literatura sobre las relaciones entre marca y consumidor para aplicar el concepto de amor de marca a una ciudad como destino turístico, la presente investigación analiza los antecedentes y las consecuencias del amor de marca de ciudad.

Conforme a los resultados, el atractivo de la marca ciudad, la identificación con la marca ciudad y la experiencia memorable con la marca ciudad son los antecedentes del amor a la marca ciudad. Adicionalmente, el atractivo de la marca ciudad, tanto directa como indirectamente a través de las experiencias memorables y la identificación con la marca ciudad, es uno de los antecedentes del amor por la marca ciudad. Finalmente, los resultados sugieren que la comunicación boca-oído y la intención de volver a visitar la ciudad son los principales resultados comportamentales del amor de marca de ciudad.

Al proporcionar un modelo conceptual validado que analiza los antecedentes y las consecuencias del amor de marca de ciudad, este estudio trata de responder a las llamadas para su estudio desde la óptica del turismo urbano.

The citizen-shareholder approach in the capital market is considered a knowledge-enhancing and emerging concept in financial and accounting offerings. Its reliable background in management and human sciences makes it an essential basis for protecting the interests of shareholders and investors. Shareholders are considered a necessary part of the social platforms that are companies and regulatory institutions in the capital market; beyond being obligated to protect their material and intellectual rights, they are responsible for developing norms and facilitating investment values and gaining trust through mutual interactions based on respect for their interests. The purpose of this paper is to perform interactive qualitative analysis of the requirements for protecting the rights of citizens of capital market shareholders.

The methodology of the research is mixed, so that in the qualitative part, through content screening, the dimensions related to the protection of the citizen rights of the capital market shareholders were identified through a systematic review of 10 research in the period of 2017–2022. Then, the reliability of the specified dimensions was examined through Delphi analysis; in the quantitative part of the research, the criteria identified through the pairwise comparison matrix were first determined by the level of their relationships to determine based on the pattern of systemic representation of drivers and the consequences of requirements to protect the rights of citizens of capital market shareholders.

The research results in the qualitative part indicated the existence of 12 primary themes; during the two stages of Delphi analysis, three themes were removed, and a total of nine themes entered the quantitative phase. The results in a quantitative part indicate the creation of specialized and active committees of the board of directors as the primary driver and the reliability and timely disclosure of information in the long term as a systemic consequence.

To the best of the authors’ knowledge, this is the first research that presents the new concept of citizen shareholders to strengthen the requirements of protecting the rights of shareholders in the capital market while developing new theoretical literature.

This paper aims to explore the interplay between industrial diversity and sustainable economic development in US counties.

Among other popularly used measures, this study uses an underused measure, Hachman index, to gauge the degree of industrial diversity in the models. To capture the impact of industrial diversity on the local community, this study estimates the relationship of two diversity measures to four traditional socioeconomic indicators: per capita personal income growth, gross domestic product per worker, income inequality ratio and poverty rate.

Statistical results suggest that industrial diversity, which is measured by Hachman index, is significantly related to the four socio-economic indicators. Industrial diversity can positively contribute to regional per capita personal income growth and mitigate income inequality and poverty stress; however, it is negatively related to the gross domestic product (GDP) per worker, which means industrial specialization may contribute to GDP per worker growth.

The findings of this study show that there is a nonlinear relationship between industrial diversity and all socioeconomic indicators. Most of the control variables, human capital variables and business and industry profile variables also display significant and positive impacts on economic development.

This study aims to investigate the influence of economic policy uncertainty (EPU) and geopolitical risk (GPR) on the relationship between internal cash flow and external financing in an emerging market, Saudi Arabia. It also examines the role of asset tangibility and financial crisis in establishing this relationship.

The sample was taken from non-financial sector companies listed on the Saudi Stock Exchange between 2002 and 2019. The data were analyzed using panel data regression analysis, including ordinary least squares and fixed effects model. The author addresses potential endogeneity through the generalized method of moments.

This study found that both EPU and GPR reduce the sensitivity of external financing to internal cash flow. This implies that firms depend more on internally generated funds during periods of increased EPU and GPR. Besides, this study found that the influence of EPU and GPR on the sensitivity of external financing to internal cash flow is more (less) negative for more tangible firms (during the financial crisis period). This result implies that Saudi firms boasting a higher level of tangibility are more flexible when it comes to seeking external financing. However, the presence of uncertainty during the crisis period makes the external financing costly, and therefore, firms will be less likely to raise funds from external sources.

This study has important implications for managers, policymakers and regulators. First, the paper findings provide insights for corporate decision-makers in helping them to focus on internal funds to finance their investment during uncertain times. Second, the findings help managers to understand the role of asset tangibility in raising external funding when firms face financial constraints due to uncertainty. Third, this study also helps corporates to focus on internal funds to finance their investment during the crisis period because EPU and GPR increase the cost of external finance. Finally, the results provide guidelines for policymakers and regulators to make appropriate policy measures to increase the easy availability of external finance during periods of increased EPU and GPR.

This paper is the first to shed light on the impact of internal funds on external financing while paying close attention to the role of EPU and GPR.

This paper delves into the ex ante rates of return demanded by the private sector in Indonesian public–private partnership (PPP) infrastructure projects and the manifold factors emanating from project attributes that can influence these rates.

This paper analyzes feasibility studies of 37 PPP projects across different sectors. The studies were carefully selected based on relevance, completeness and validity of data. The analysis uses statistical techniques, including Levene’s tests, t-tests, ANOVA tests, Cohen’s effect size and Pearson correlations, to explore differences in cost of capital and excess returns across various attributes.

Based on the statistical analysis, no significant difference exists between the excess return of 200 basis points (bps) and the equity excess return of 0 bps. This suggests that the eligibility criteria for PPP projects require an internal rate of return (IRR) equal to the weighted average cost of capital plus 200 bps or an equity IRR equal to the cost of equity. The variations in the tested variables among diverse project attributes do not exhibit statistically significant disparities, even though specific attributes display moderate to high effect sizes.

This paper represents one of the first attempts to examine the rates of return demanded by the private sector in the context of Indonesian PPP projects. It comprehensively explores the factors that influence these rates, drawing on insights derived from feasibility studies.

This paper aims to investigate the impact of climate change news on the dynamics of US stock indices.

The empirical basis of the study was 3,209 news articles. Sentiment analysis was performed by a pre-trained bidirectional FinBERT neural network. Thematic modeling is based on the neural network, BERTopic.

The results show that news sentiment can influence the dynamics of stock indices. In addition, five main news topics (finance and politics natural disasters and consequences industrial sector and Innovations activism and culture coronavirus pandemic) were identified, which showed a significant impact on the financial market.

First, we extend the theoretical concepts. This study applies signaling theory and overreaction theory to the US stock market in the context of climate change. Second, in addition to the news sentiment, the impact of major news topics on US stock market returns is examined. Third, we examine the impact of sentimental and thematic news variables on US stock market indicators of economic sectors. Previous works reveal the impact of climate change news on specific sectors of the economy. This paper includes stock indices of the economic sectors most related to the topic of climate change. Fourth, the research methodology consists of modern algorithms. An advanced textual analysis method for sentiment classification is applied: a pre-trained bidirectional FinBERT neural network. Modern thematic modeling is carried out using a model based on the neural network, BERTopic. The most extensive topics are “finance and politics of climate change” and “natural disasters and consequences.”

This paper has analysed the impact of cultural dimensions, investor sentiment and uncertainty on bank stock returns. Also, the study examined the influences of the interaction between cultural dimensions and individual (private) sentiment (investor sentiment).

To meet the study's objectives, a two-step generalised method of moments estimator was applied to the study sample, which included 105 banks in the nine Middle East and North African region countries between 2010 and 2020.

The cultural dimensions of individualism and masculinity were found to have a positive and significant effect on banks' buy and hold stock return (BUH). At the same time, power distance and uncertainty avoidance were discovered to have negative effects. Besides, the findings revealed that the interactions of power distance, individual sentiment and uncertainty avoidance had positive and significant relationships with banks' BUH. However, individualism, individual sentiment and masculinity had inverse relationships with banks' BUH. Furthermore, the findings revealed that investor sentiment positively influenced banks' BUH. Finally, uncertainty influenced banks' BUH stock returns positively.

Important implications for participants in the financial sector and governments may be learnt from this study's conclusions. Due to cultural biases, this study's findings suggested that investors overreact in the stock market.

Additionally, this research comprises one of the few studies that have overviewed the link between classical and behavioural finance in MENA countries with distinctive cultural characteristics.

This study aims to propose an approach to assess the security of supply (SS) in a coal-fired electricity generation supply chain subject to public price regulation in Brazil. This study characterizes the Brazilian scenario of coal-fired electricity generation, which represents less than 3.5% of the energy sources.

Data from six mining companies that supply a coal plant were analyzed in a case study. The risks were characterized and objectively estimated through a synthetic multidimensional index. Structural changes in the earnings before interest, taxes, depreciation, amortization and exploration indicator time series of coal companies (CC) were statistically detected.

Empirical evidence demonstrates that the supply chain has a low disruption risk (SS index equal to 0.74). However, when suppliers are individually analyzed, 48.64% of all coal shows moderated disruption risk, and 2.51% is under high risk. In addition, this study finds a drop in the financial results of CC related to public regulation of coal prices. This impacts the security of coal supply.

This study discusses the influence of legal and regulatory policy risks in a coal power generation supply chain and the implications of the SS index as a management tool.

A novel SS index is presented and empirically operationalized, and its dimensions – environmental, occupational, operational, economic-financial and supply capacity – are analyzed.