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This investigation aims to determine the effect of trade uncertainty on domestic investment (DI) and foreign direct investment (FDI) for the Turkish economy from the first quarter of 2005 to the first quarter of 2020.

The authors adopt the vector autoregression (VAR) model augmented with Fourier terms. Using this methodology, the authors obtain the empirical results of the impulse-response functions and the variance decomposition analysis.

The empirical results demonstrate that a shock to trade uncertainty has a slight negative impact on DI for up to approximately 1.5 years, whereas its impact on FDI is negative but long-lasting. Moreover, the contribution of trade uncertainty to FDI is relatively higher than to DI in the error variance decomposition for the investigated period. These empirical results can be beneficial for shaping the Turkish authorities' trade policies in the following periods.

These findings have implications within the macroeconomic setting. Government authorities can provide tax exemptions for specified sectors and debureaucratize investment processes for both domestic and foreign entrepreneurs. Additionally, institutional quality and property rights should be protected strictly and developed gradually.

This study is the first to examine the impact of world trade uncertainty on Türkiye’s DI and FDI. Because trade uncertainty might act as fixed costs, this creates the option value of waiting and seeing the market, and firms hesitate to incur investment.

Decentralized finance (DeFi), enabled by blockchain, could bring about a new financial system, where peers will interact directly, with little or no place for traditional intermediation. However, some crucial tasks cannot be left solely to an algorithm and, consequently, most DeFi applications still require human decisions. The aim of this research is to assess the role of intermediation in the light of DeFi, analysing how humans and algorithms will interact.

The authors based their work on a twofold qualitative methodology, first analysing publicly available secondary data, particularly from white papers and DeFi Pulse (a website providing data on DeFi solutions) and then running two focus group discussions.

DeFi does not eliminate financial intermediation, but enables it to be performed in new ways, where decentralization means that no single entity can hold too much power or monopoly. DeFi has, however, inherited risks from the underlying technologies that unintentionally facilitate illegal behaviour and can hamper the authorities’ supervision. The complex duality algorithm- vs human-based actions will not be solved indisputably in favour of the former, as DeFi solutions can range from requiring algorithms to play a dominant role, to enabling greater human interaction by actively involving more people.

This research contributes to the emerging debate between algorithm- and human-based intermediation, especially in relation to the standing literature on financial intermediation, where considerations made in the light of the newest theories on blockchain and DeFi are still scarce.

The aim of this study is to investigate the impact of local political uncertainty on the asymmetric cost behavior (i.e. cost stickiness) for listed firms in China.

In this study, the authors manually collect the turnover data of prefecture-city officials as a measure of exogenous fluctuations in political uncertainty and obtain firm-level financial information from the China Stock Market Accounting Research (CSMAR) database. To perform the analysis, the authors augment the traditional cost stickiness model by including the interaction terms of the prefecture-city official turnover, and firm-level and prefecture-city level control variables.

The authors find that political turnover leads to a higher degree of cost stickiness, implying that firms retain slack resources when political uncertainty is high. Moreover, the effect of political turnover on cost stickiness is more pronounced for firms residing in regions with weaker institutional environments, and firms that are privately owned and with smaller size. The authors further provide evidence that policy uncertainty and the threat of losing political connection are two underlying channels. Overall, this study documents that the local political process is an important channel that influences corporate operational decisions.

This study provides the first piece of evidence on the relation between political uncertainty and cost stickiness at the local government level. Moreover, the authors propose and demonstrate two underlying channels through which political uncertainty affects firms' asymmetric cost behavior.

This study explores the response of consumer confidence in policy uncertainty in the Japanese context. The study also considers the dynamism of stock market behavior and financial stress and its impact on consumer confidence, which has remained unaddressed in the literature. The role of these control variables has important implications for policy discussions, particularly when other countries can learn from Japanese experiences.

The nonlinear autoregressive distributed lag model postulated by Shin et al. (2014) was used for studying the asymmetric response of consumer confidence to policy uncertainty. This method has improved estimates compared to traditional linear cointegration methods.

The findings confirm the asymmetric impact of policy uncertainty on the consumer confidence index in Japan. The impact of the rise in policy uncertainty is greater than that of a fall in asymmetry on consumer confidence in Japan. Furthermore, the Wald test confirmed asymmetric behavior.

The contribution of this study is threefold. First, this study contributes to the extant literature by analyzing the asymmetric response of consumer confidence to policy uncertainty, controlling for both the financial stress and stock price indices. Second, to test the robustness of the exercise, the study utilized different frequencies of observations. Third, this study is the first to utilize the concept of Arbatli et al. (2017) to formulate a combined index of uncertainty based on economic policy uncertainty index, along with uncertainty indices such as fiscal, monetary, trade and exchange rate policies to study the overall impact of policy uncertainty.

This study aims to establish the shape of investment dynamics in equity crowdfunding to better understand backer behavior.

This study provides insights into when backers invest in successful funding campaigns. It uses t-tests to compare differences in means between observation windows during successful funding campaigns. It is based on 4,938 transactions from 61 campaigns, focusing on the first and last tail ends.

In contrast to previous findings, the current investment dynamics seem more U-shaped than L-shaped. This supports previous findings about a strong start but also suggests a late collective attention effect. The strength is higher at the first tail end. However, differences in the later tail ends are statistically significant and emphasize the presence of late investment activities, especially in crowded or less complex campaigns.

These findings emphasize the importance of signaling during the entire funding window. This encourages platforms to invest in user-friendly functionalities that guide entrepreneurs and help backers when investing in successful campaigns.

This study improves the understanding of backer behavior and suggests changing investment dynamics in equity crowdfunding. In addition, this pattern contrasts with previous findings on dynamic collective attention effects in rich digitally informative markets, implying two attention effects when uncertainty is high.

Using overlapped portfolio data on public equity funds in Korea, the authors construct several types of fund-stock weighted bipartite networks and measure fund network centrality. The authors also examine the relationship between network centrality and fund investment performance. The authors' results are three-fold. First, the authors find that the fund centrality of the network in which funds and stocks are connected based on the most active investing behavior positively affects the fund performance. Second, the funds with a high centrality level based on the same network generate higher returns by holding stocks with high value uncertainty. Third, the authors find that fund centrality is not associated with herd behavior. Based on these results, the authors argue that fund centrality is a proxy of information advantage and skill of fund managers. The authors' paper shows that network analysis could be a new way to identify funds with better performance and measure the skill and information advantage to construct an optimal portfolio.

The relevance of present consumption bias on personal finance has been confirmed in several studies and has important theoretical and practical implications. It has important, measurable implications when analyzing commitment or self-control, adherence to healthy habits (e.g. exercising or dieting), procrastination tendencies or savings. The purpose of this paper is to contribute to our understanding of these issues by postulating a model of income uncertainty within a hyperbolic discounting framework that measures the cost of financial intertemporal inconsistencies related to this bias. The emphasis is on the analysis of this cost. We also propose experimental designs and consistent estimation methods, as well as agent-based modelling extensions.

The authors develop a finite-horizon model with hyperbolic preferences. Individuals have a present bias distinct from their discount rate so their choices face intertemporal inconsistencies. The authors further extend the analysis with uncertainty about future incomes. Specifically, individuals live for three periods, and the authors find the optimal consumption levels in the perfect-information benchmark by backward induction. They then proceed to add biases and uncertainty to characterize their implications and measure the costs of the intertemporal inconsistencies they cause.

The authors measure how an agent's utility is greater when they “tie their hands” than when they are free to re-evaluate and change their consumption schedule. This “cost of being vulnerable to falling into temptation” only depends (increasingly) on the measure of the present bias and (decreasingly) on the discount factor. They analyze the varying effects on utility and consumption of changes in impatience and optimism. They conclude by discussing theoretical and practical implications; they also propose agent-based simulations, as well as empirical and experimental designs, to further test the relevance and applications of the results.

This model has important, measurable implications when analyzing commitment or self-control, adherence to healthy habits (e.g. exercising or dieting), procrastination tendencies or savings.

The results enhance the estimation of the costs of present biases such that employers can better identify the incentives required to acquire and retain human capital. The authors provide evidence that workers are vulnerable to contract renegotiations and about the need for a regulator that restores ex-ante efficiency. Similarly, in the private sector, firms could recognize the postulated consumer profiles and focus their resources on anxious, too-optimistic or potentially addictive consumers; this, again, provides some justification about the need for a regulator.

In traditional exponential discounting, the marginal rate of substitution of consumption between two points depends only on their distance; thus, it allows none of the intertemporal inconsistencies we often observe in real life. Therefore, hyperbolic discounting better fits the data. The authors model choice under uncertainty and focus on the costs caused when present biases (ex-post) push behaviour away from ex-ante optimality. They conclude by proposing experimental designs to further enhance the estimation and implications of these costs. The postulated refinements have the potential to improve previous analyses on commitment devices and commitment-related regulation.

This paper aims to deepen the understanding of the relationship between global economic uncertainty and price volatility, specifically focusing on commodity, industrial materials and energy price indices as proxies for global inflation, analyzing data from 1997 to 2020.

The dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model is used to study the dynamic relationship between variables over a while.

The results demonstrated a positive relationship between commodity prices and the global economic policy uncertainty (GEPU). Except for 1999–2000 and 2006–2008, the results of the energy price index model were very similar to those of the commodity price index. A predominant positive relationship is observed focusing on the connection between GEPU and the industrial material price index. The results of the pairwise Granger causality reveal a unidirectional relationship between the GEPU – the Global Commodity Price Index – and the GEPU – the Global Industrial Material Price Index. However, there is bidirectional causality between the GEPU – the Global Energy Price Index. In sum, changes in price indices can be driven by GEPU as a political factor indicating unfavorable economic conditions.

This paper provides a deeper understanding of the role of global uncertainty in the global inflation process. It fills the gap in the literature by empirically investigating the dynamic movements of global uncertainty and the three most important groups of prices.

The study investigates the effect of behavioural uncertainty on the environmental sustainability of restaurant businesses in Tanzania. Also, the study examines the moderating role of purchasing technical knowledge on the main relationship between the study variables.

The quantitative approach was used and cross-sectional data were collected at a specific time from restaurant businesses in Dodoma, Tanzania. The PROCESS macro was used to analyse the relationships between behavioural uncertainty, purchasing technical knowledge and environmental sustainability.

Behavioural uncertainty has a significant and negative effect on the environmental sustainability of restaurant businesses. Purchasing technical knowledge, on the other hand, has a positive and significant effect on the environmental sustainability of restaurant businesses. Finally, purchasing technical knowledge has a positive and significant moderating effect on the relationship between behavioural uncertainty and environmental sustainability such that the negative effect of behavioural uncertainty is reduced with increasing purchasing technical knowledge.

This study considers purchasing skills in terms of purchasing technical knowledge as a moderating variable; hence, other studies may take into account other moderating variables to extend this study. Also, the study considered only environmental sustainability and hence is limited in terms of other dimensions of sustainability and provide an avenue for further research in social and economic sustainability.

Since purchasing technical knowledge reduces the negative effect of behavioural uncertainty on the relationship with environmental sustainability, restaurant managers should be encouraged to improve their purchasing technical knowledge by attending short- and long-term training on purchasing functions in the restaurant industry.

The social implications of the investigated link between behavioural uncertainty, purchasing technical knowledge and environmental sustainability in the restaurant industry include raising awareness, promoting sustainable practises and fostering an environmentally responsible culture. By addressing behavioural uncertainty, leveraging purchasing technical knowledge and embracing sustainability the industry can contribute to a more environmentally conscious society.

By providing empirical evidence from Tanzania, the study extends literature on examining the environmental sustainability of restaurant businesses. The study also establishes the interaction effect of purchasing technical knowledge as an important skill in reducing the negative effect of behavioural uncertainty on enhancing environmental sustainability in restaurant businesses.

The novel coronavirus (nCoV) pandemic, and the challenges of social distancing, proffer a unique opportunity to re-explore the role of social network support in entrepreneurship. Applying social support theory and gender schema theory, this study aims to examine the gender-based differences in prospective entrepreneurs' reliance on their social networks in their entrepreneurial journey amid social turmoil.

The authors collected two-stage primary survey data of prospective entrepreneurs within the pandemic's timeframe from Science and Technology Parks in Iran, one of the first countries to deal with the first, second and third waves of the 2019-nCoV virus.

The findings demonstrate that female entrepreneurs rely more strongly on their social network support for guidance and encouragement, which positively affects their opportunity intention. While this effect is also seen in men, the effect size is smaller. Also, prospective female entrepreneurs were generally more dissuaded from opportunity intention by the severe perceived environmental uncertainty of the crisis than were men.

Prior research on the interaction between social network support and opportunity intentions has been examined in the context of socio-economic normalcy. The authors test whether, how and why these interactions hold in times of crisis, with especial attention to the mechanisms of experienced stress, perceived environmental uncertainty and idea innovativeness.