Search results

This study investigates the nexus between the returns on oil prices (OP) and unemployment (UR) while taking into account the influences of two of the most representative measures of uncertainty, the Baker et al. (2016) and Caldara and Iacovello (2021) indexes of economic policy uncertainty (EP) and geopolitical risks (GP), in the relationship.

The authors use data on the US, Canada, France, Italy, Germany and Japan from January 2000 to February 2022 and the UK from January 2000 to December 2021. The authors then apply the continuous wavelet transform (CWT), wavelet coherence (WC), partial wavelet coherence (PWC) and multiple wavelet coherence (MWC) to examine the returns within a time and frequency framework.

The CWT tracks the movement and evolution of individual return series with evidence of high variances and heterogenous tendencies across frequencies that also align with critical events such as the GFC and COVID-19 pandemic. The WC reveals the presence of a bidirectional relationship between OP and UR across economies, showing that the two variables affect each other. The authors’ findings establish the predictive influence of oil price on unemployment in line with theory and also show that the variation in UR can impact the economy and alter the dynamics of OP. The authors employ the PWC and MWC to capture the impact of uncertainty indexes in the co-movement of oil price and unemployment in line with the theory of “investment under uncertainty”. Taking into account the common effects of EP and GP, PWC finds that uncertainty measures significantly drive the co-movement of oil prices and unemployment. This result is robust when the authors control for the influence of economic activity (proxied by the GDP) in the co-movement. Furthermore, the MWC reveals the combined intensity, strength and significance of both oil prices and the uncertainty measures in predicting unemployment across countries.

This study investigates the relationship between oil prices, uncertainty measures and unemployment under a time and frequency approach.

1. Wavelet approaches are used to examine the relationship between oil prices and unemployment in the G7.

2. We account for uncertainty measures in the dynamics of oil prices and unemployment.

3. We observe a bidirectional relationship between oil prices and unemployment.

4. Uncertainty measures significantly drive oil prices and unemployment co-movement.

5. Both oil prices and uncertainty measures significantly drive unemployment.

Wavelet approaches are used to examine the relationship between oil prices and unemployment in the G7.

We account for uncertainty measures in the dynamics of oil prices and unemployment.

We observe a bidirectional relationship between oil prices and unemployment.

Uncertainty measures significantly drive oil prices and unemployment co-movement.

Both oil prices and uncertainty measures significantly drive unemployment.

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.

This paper aims to explore how sell-side analysts and salespeople make sense of uncertainty on their market knowledge, valuation and marketing outputs.

Data is collected by direct observations of and interviews with analysts and salespeople in the Turkish stock exchange, an emerging market with considerable global fund management activity.

Analysts face considerable uncertainty on their market value forecasts but dismiss it as local dynamics not incorporable to valuation practices in global sell-side business. Salespeople, despite paying more attention to such dynamics owing to their sales tasks, limit themselves to analyst output in marketing. Both actors recognise the importance of analyst work to be able to have “a right to speak” in global sell-side business.

Changing market conditions and regulations since the time of study have been shaping analysts and salespeople work in global sell-side business, for example, the way sell-side is compensated by buy-side, buy-side’s move to receiving sell-side services from fewer brokers and hence shrinking sell-side teams. The paper does not address these. Nonetheless, it shows how valuation and marketing can be two distinct lines of work in sell-side business irrespective of market conditions and raises the question for future research as to how sell-side professionals manage this distinction, and how they make sense of and cope with broad market dynamics beyond sell-side and buy-side relations (e.g. automated trading machines, online retail trading).

The paper provides rare observation-based insights into analyst and salespeople work, including their sensemaking of uncertainty. It shows the importance of market identities and associated knowledge in valuation and marketing work in sell-side business.

The purpose of this paper is to interpret organizational change from a co-evolutionary perspective. It examines the co-evolution between institutional environments and organizational change with the mediating role of uncertainty as perceived by managers.

The author employed an inductive case study to explore how institutional environments interact with organizational change in a novel context: a Chinese state-owned enterprise.

The author developed a co-evolutionary model of organizational change that emphasizes the interaction between institutional-level factors and organizational-level change as bridged by top management perceptions of uncertainty. The model also illustrates the dynamics of organizational uncertainty and its effects on organizational change.

The study implies that uncertainty may not be an inevitable negative influence on organizational development, and tell managers how to manages the dynamics of uncertainty through two principles.

This study contributes to the organizational change literature by interpreting organizational change as the results of interaction between multi-level factors from institutional, organizational, and team levels. The author also expand the understanding of uncertainty from a dynamic perspective.

The purpose of this paper is to improve control performance and safety of a real two-wheeled inverted pendulum (TWIP) robot by dealing with model uncertainty and motion restriction simultaneously, which can be extended to other TWIP robotic systems.

The inequality of lumped model uncertainty boundary is derived from original TWIP dynamics. Several motion restriction conditions are derived considering zero dynamics, centripedal force, ground friction condition, posture stability, control torque limitation and so on. Sliding-mode control (SMC) and model predictive control (MPC) are separately adopted to design controllers for longitudinal and rotational motion, while taking model uncertainty into account. The reference value of the moving velocity and acceleration, delivered to the designed controller, should be restricted in a specified range, limited by motion restrictions, to keep safe.

The cancelation of model uncertainty commonly existing in real system can improve control performance. The motion commands play an important role in maintaining safety and reliability of TWIP, which can be ensured by the proposed motion restriction to avoid potential movement failure, such as slipping, lateral tipping over because of turning and large fluctuation of body.

An inequation of lumped model uncertainty boundary incorporating comprehensive errors and uncertainties of system is derived and elaborately calculated to determine the switching coefficients of SMC. The motion restrictions for TWIP robot moving in 3D are derived and used to impose constraints on reference trajectory to avoid possible instability or failure of movement.

The purpose of this paper is to extend the literature on the spillovers across economic policy uncertainty (EPU) and cryptocurrency uncertainty indices.

This paper uses cross-country economic policy uncertainty indices and the novel data measuring the cryptocurrency price uncertainties over the period 2013–2021 to construct a sample of 946 observations and applies the time-varying parameter vector autoregression (TVP-VAR) model to do an empirical study.

The findings suggest that there are cross-country spillovers of economic policy uncertainty. In addition, the total uncertainty spillover between economic policies and cryptocurrency peaked in 2015 before gradually decreasing in the following periods. Concomitantly, the cryptocurrency uncertainty has acted as the “receiver.” More importantly, the authors found the predictive power of economic policy uncertainty to predict the cryptocurrency uncertainty index. This paper’s results hold robust when using alternative measurement of cryptocurrency policy uncertainty.

This study is the first research that deeply investigates the association between two uncertainty indicators, namely economic policy uncertainty and the cryptocurrency uncertainty index. We provide fresh evidence about the dynamic connectedness between country-level economic policy uncertainty and the cryptocurrency index. Our work contributes a new channel driving the variants of uncertainties in the cryptocurrency market.

Applying discrete linear optimal control to robot manipulators faces two challenging problems, namely nonlinearity and uncertainty. This paper aims to overcome nonlinearity and uncertainty to design the discrete optimal control for electrically driven robot manipulators.

Two novel discrete optimal control approaches are presented. In the first approach, a control-oriented model is applied for the discrete linear quadratic control while modeling error is estimated and compensated by a robust time-delay controller. Instead of the torque control strategy, the voltage control strategy is used for obtaining an optimal control that is free from the manipulator dynamics. In the second approach, a discrete optimal controller is designed by using a particle swarm optimization algorithm.

The first controller can overcome uncertainties, guarantee stability and provide a good tracking performance by using an online optimal algorithm whereas the second controller is an off-line optimal algorithm. The first control approach is verified by stability analysis. A comparison through simulations on a three-link electrically driven robot manipulator shows superiority of the first approach over the second approach. Another comparison shows that the first approach is superior to a bounded torque control approach in the presence of uncertainties.

The originality of this paper is to present two novel optimal control approaches for tracking control of electrically driven robot manipulators with considering the actuator dynamics. The novelty is that the proposed control approaches are free from the robot's model by using the voltage control strategy. The first approach is a novel discrete linear quadratic control design supported by a time-delay uncertainty compensator. The second approach is an off-line optimal design by using the particle swarm optimization.

This study aims to explore potential paradigm shift in how “global economies” react to adverse macroeconomic conditions from key dominant economies such as the US and the Chinese economies. This is done by examining how economic activities within key economies around the world react to, or are impacted by, modeled adverse macroeconomic condition emanating from the Chinese and the US economies.

To verify potential paradigm shift in how external macroeconomic uncertainty impacts “global” industrial productivity and overall gross domestic product (GDP) growth within selected economies, this study opts for seemingly unrelated regression (SUR) model. Adoption of this method has been influenced by the potential for correlated error terms between modeled adverse macroeconomic condition, industrial productivity and GDP growth variables being tested in a two-equation system.

Empirical results based on SUR analysis find no evidence of this potential paradigm shift within the time frame examined in the study. Estimated results suggest that notwithstanding the recent growth surge of the Chinese economy, macroeconomic happenings within the US economy still exert significantly more influence on key economies around the world. For instance, this study finds that macroeconomic uncertainty associated with the US economy significantly constrains both industrial productivity and overall GDP growth within most of the economies tested, whereas the same condition emanating from the Chinese economy seems to rather have a weak positive impact on the same macroeconomic variables.

Research results are strictly limited to the focus time frame for this study; it is likely that expanded data involving more years beyond what was analyzed in this study could yield different results.

This study is an original research based on data from a reputable US federal institution.

The purpose of this paper is to discuss how decisions regarding organisational flexibility can be improved through targeted resource allocation, by focusing on the supply chain's level of uncertainty exposure. Specifically, the issue of where and in what ways flexibility has been incorporated across the organisation's supply chain is addressed.

A two-phase methodology design based on literature review and case study was used. Using 83 journal articles in the areas of uncertainty and flexibility an analytical process for assessing uncertainty-flexibility mismatches was developed. Furthermore, results from ten interviews with senior/middle managers within the Australian manufacturing sector were used to provide preliminary insights on the usefulness and importance of the analytical process and its relationship with organisational practice.

The paper emphasises the importance of having a systematic and encompassing view of uncertainty-flexibility mismatches across the supply chain, as well as the significance of socio-technical engagement. The paper both conceptually and empirically illustrates how, using a structured analytical process, flexibility requirements across the supply, process, control and demand segments of a supply chain might be assessed. A four-step analytical process was accordingly developed and, its application, usefulness and importance discussed using empirical data.

The analytical process presented in this paper can assist managers to obtain a comprehensive overview of supply chain flexibility when dealing with situations involving uncertainty. This can facilitate and improve their decision-making with respect to prioritising attention on identified flexibility gaps in order to ensure stability of their performance.

The paper presents a supply chain-wide discussion on the difficulties that uncertainty brings to organisations, and how organisational flexibility might serve to moderate those challenges for supply chain management. It discusses how to identify the flexibility gap and proposes an original analytical process for systematic assessment of uncertainty-flexibility mismatches.