Search results

This paper aims to minimize the mean-risk cost of sustainable and resilient supplier selection, order allocation and production scheduling (SS,OA&PS) problem under uncertainty of disruptions. The authors use conditional value at risk (CVaR) as a risk measure in optimizing the combined objective function of the total expected value and CVaR cost. A sustainable supply chain can create significant competitive advantages for companies through social justice, human rights and environmental progress. To control disruptions, the authors applied (proactive and reactive) resilient strategies. In this study, the authors combine resilience and social responsibility issues that lead to synergy in supply chain activities.

The present paper proposes a risk-averse two-stage mixed-integer stochastic programming model for sustainable and resilient SS,OA&PS problem under supply disruptions. In this decision-making process, determining the primary supplier portfolio according to the minimum sustainable-resilient score establishes the first-stage decisions. The recourse or second-stage decisions are: determining the amount of order allocation and scheduling of parts by each supplier, determining the reactive risk management strategies, determining the amount of order allocation and scheduling by each of reaction strategies and determining the number of products and scheduling of products on the planning time horizon. Uncertain parameters of this study are the start time of disruption, remaining capacity rate of suppliers and lead times associated with each reactive strategy.

In this paper, several numerical examples along with different sensitivity analyses (on risk parameters, minimum sustainable-resilience score of suppliers and shortage costs) were presented to evaluate the applicability of the proposed model. The results showed that the two-stage risk-averse stochastic mixed-integer programming model for designing the SS,OA&PS problem by considering economic and social aspects and resilience strategies is an effective and flexible tool and leads to optimal decisions with the least cost. In addition, the managerial insights obtained from this study are extracted and stated in Section 4.6.

This work proposes a risk-averse stochastic programming approach for a new multi-product sustainable and resilient SS,OA&PS problem. The planning horizon includes three periods before the disruption, during the disruption period and the recovery period. Other contributions of this work are: selecting the main supply portfolio based on the minimum score of sustainable-resilient criteria of suppliers, allocating and scheduling suppliers orders before and after disruptions, considering the balance constraint in receiving parts and using proactive and reactive risk management strategies simultaneously. Also, the scheduling of reactive strategies in different investment modes is applied to this problem.

This study seeks to build a financial uncertainty index for Saudi Arabia. This index serves as a leading indicator of Saudi economic activity and helps to describe economic fluctuations and forecast economic trends.

This study adopts an extension of the Jurado et al. (2015) procedure by combining financial uncertainty factors with their net spillover effects on GDP and inflation to construct an aggregate financial uncertainty index. The authors consider 13 monthly financial variables for Saudi Arabia from January 2010 to June 2021.

The empirical results show that the constructed financial uncertainty estimates are good leading indicators of economic activity. The robustness analysis suggests that the authors’ proposed financial uncertainty estimators outperform the alternative estimates used by other existing approaches to estimate the financial conditions index.

To the best of the authors’ knowledge, this is the first attempt at constructing a financial uncertainty index for Saudi Arabia. This study extends the empirical literature, from which the authors propose a novel conceptual framework for building a financial uncertainty index by combining the approach of Jurado et al. (2015) and the time-varying connectedness network approach proposed by Antonakakis et al. (2020)

The paper aims to investigate whether or not a firm’s capital structure can interact with past stock returns to affect future stock returns. Specifically, the authors examine whether or not capital structure can help improve momentum profit.

The authors use the US common stocks data from 1965 to 2022 to empirically examine the impact of capital structure on momentum profit.

When capital structure is measured either as the ratio of debt to asset or the ratio of liability to asset, we all find out that momentum strategies tend to be more profitable for stocks with large capital structure.

Besides documenting the empirical evidence of the impact of capital structure on momentum profit, the authors also present a simple explanation for their empirical results and show that their finding is consistent with the behavioral finance theory that characterizes investors’ increased psychological bias and the more limited arbitrage opportunity when the estimation of firm value becomes more difficult or less accurate.

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 purpose of this paper is to investigate the impact of changes in credit stock on real and financial indicators in Turkey with a focus on conditional and time-varying dynamics.

In addition to lag-augmented vector autoregression (LA-VAR) based time-varying Granger causality tests, threshold models and a research setting that identifies high/low states of credit growth based on 24-month moving averages are used to explore regime-dependent behavior. For investigating the asymmetric dynamics, the authors use a methodology that identifies good/bad news in credit growth based on 24-month moving averages and standard deviations.

Results strongly suggest that the impact of changes in credit stock induces conditional responses. Moreover, we find evidence for asymmetric responses. In the case of Turkey, efforts to spur growth through credit produce a strong negative byproduct, a depreciation in the exchange rate. The authors also find that changes in credit stock have become more relevant for uncertainties in inflation and exchange rate expectations, particularly in the era after mid-2018 in which credit growth volatility has increased noticeably.

This study provides a comprehensive analysis of time-varying and conditional responses to a change in credit stock in a major emerging economy. Using a moving threshold based only on the available information in the analysis of state-dependency represents a new approach.

The study examines how the liquid assets holdings among non-financial Indian firms vary due to tightening monetary policy and increasing macroeconomic uncertainty.

The authors analyze 5,640 firms for the period 2011–2021. The authors first estimate India’s monetary policy shocks by decomposing the exogenous shocks from the systematic component of monetary policy changes. The authors then examine the effects of the estimated monetary policy shocks and a range of macroeconomic and policy uncertainty indicators on companies’ cash and bank balances to asset ratios using two-step system generalized method of moments (GMM) estimators.

The authors find that monetary policy shocks cause the cross-sectional variances for the firms’ liquidity holdings to increase. In anticipation of macroeconomic volatility, companies respond to these shocks after taking into account all the firm-level information to minimize the opportunity costs of holding extra cash or too few cash balances that can hamper firms’ operations. Furthermore, compared to other shocks, the contribution of inflation-induced shocks is predicted to be the largest in the cross-sectional deviation of the firm’s cash holdings. The authors also find that low-growth, older and financially constrained firms observe lesser heterogeneity in their cash holdings as they tend to hold cash as a precautionary buffer.

The authors’ approach to the analysis is unique in many ways. To address potential transmission bias, the authors use nowcasts and forecasts of real gross domestic product (GDP) growth and inflation to generate a series of exogenous monetary policy shocks for identifying unanticipated changes in short-term interest rates. Subsequently, the authors estimate how these shocks affect the cross-sectional deviation of liquid assets. For estimating the effects of macroeconomic uncertainty on corporate cash demand, the authors utilize a range of proxies for uncertainty. Unlike previous attempts, the authors offer evidence for a developing and fast-emerging economy.

This paper aims to examine the dynamic conditional correlation (DCC) and hedging ratios between Dow Jones markets and oil, gold and bitcoin. Using daily data, including the COVID-19 pandemic and the Russia–Ukraine war. We employ the DCC-generalized autoregressive conditional heteroskedasticity (GARCH) and asymmetric DCC (ADCC)-GARCH models.

DCC-GARCH and ADCC-GARCH models.

The most of DCCs among market pairs are positive during COVID-19 period, implying the existence of volatility spillovers (Contagion-effects). This implies the lack of additional economic gains of diversification. So, COVID-19 represents a systematic risk that resists diversification. However, during the Russia–Ukraine war the DCCs are negative for most pairs that include Oil and Gold, implying investors may benefit from portfolio-diversification. Our hedging analysis carries significant implications for investors seeking higher returns while hedging their Dow Jones portfolios: keeping their portfolios unhedged is better than hedging them. This is because Islamic stocks have the ability to mitigate risks.

Our paper may make a valuable contribution to the existing literature by examining the hedging of financial assets, including both conventional and Islamic assets, during periods of stability and crisis, such as the COVID-19 pandemic and the Russia–Ukraine war.

This paper aims to investigate the effects of volatility transmission among Bitcoin and other leading cryptocurrencies, namely, Binance USD, BNB, Cardano, Dogecoin, Ethereum, Polkadot, Polygon, Solana, Tether, USD Coin and XRP.

The multivariate BEKK-GARCH model is used with the daily data set from 1 January 2017 to 31 March 2023. The data set is analysed in its entirety and is also the COVID-19 epidemic period.

The study reveals that while the volatility of cryptocurrency prices is influenced by their own historical shocks and volatility, there is proof of the effects shock transmission among Bitcoin and other notable cryptocurrencies. Furthermore, the authors identify the spillover effects of volatility among all 11 pairs and provide evidence that conditional correlations with varying time constants are present, and predominantly positive for both the entire and COVID-19 outbreak periods.

The findings will be helpful to market experts who want to avoid losses in traditional assets. To develop the best risk management and hedging strategies, businesses might use the information to build asset portfolios or personalise payment methods. The use of such data by investors and portfolio managers could aid in the development of investment opportunities, risk insurance plans or hedging strategies for the management of financial portfolios.

To the best of the authors’ knowledge, the use of the BEKK-GARCH model for examining the effects of volatility spillover among Bitcoin and the other eleven top cryptocurrencies has not been previously documented.

In daily marketing practices, when launching and promoting new products, marketers often induce consumers’ awe of nature via exposing consumers to beautiful natural scenes. Does this marketing practice really facilitate consumers’ subsequent new product choice? Existing awe research and new product research have not examined this issue yet. The purpose of this study is to study whether the marketing practice of awe induction faciliates consumers' new product choice.

This paper examines the double-edged sword effect of different types of awe on consumers’ adoption of new products. The authors conducted five experiments using various product categories (soft drinks, juices, cookies and watches), various many sources of sample types (college student samples and adult samples) and various manipulation of awe. The authors also focused on both new products with incongruent visual appearance (Experiment 1a, Experiment 1c, Experiment 2 and Experiment 3) and new products with incongruent conceptual attributes (Experiment 1b) to enhance the rigor of the experiments and the generalizability of the conclusions.

The authors find that when consumers perceive awe of threatening natural phenomena, they decrease their choice of moderately incongruent new products (positive effect), while when consumers perceive awe of beautiful natural phenomena, they increase their choice of moderately incongruent new products (negative effect). Also, this paper finds that the emergence of the positive of the double-edged sword effect is driven by the sequential mediation of the need for accommodation and openness to new experiences, while the emergence of the negative of the double-edged sword effect is driven by the uncertainty reduction motive.

This research has important theoretical implications. First, this paper advances existing awe research by reconciling the inconsistent findings in existing awe research by categorizing awe of nature. Second, this paper advances existing research on new products and moderate incongruity effects by exploring when the moderate incongruity effect exists and when it reverses in the new products field through the classification of awe of nature.

This study has rich implications for marketing management. First, marketers can facilitate consumers’ adoption of moderate incongruent new product via priming consumers’ awe of beautiful nature. Second, this paper suggests that marketers and brand managers should carefully choose the timing of new product launches to avoid inducing consumer awe of threatening nature (e.g. immediately after a severe natural disaster). Finally, the results of Experiment 3 in this paper suggest that when marketers want to launch new products with moderate incongruity, they need to target consumers with high cognitive flexibility.

This paper discusses how different types of awe affect consumers’ attitudes and choice of moderately new products. This research question has its social value in helping marketers, companies, consumers and society know the power of awe of nature on the behaviors and decision-making.

To the best of the author’s knowledge, this paper is among the first ones to examine the double-edged sword effect of different types of awe of nature on consumers’ new product adoption.

This study aims to identify the ability of gold and cryptocurrency (Cryptocurrency Uncertainty Index (UCRY) Price) as safe haven assets (SHA) for stocks and bonds in both conventional (i.e. stock indices and government bonds) and Islamic markets (i.e. Islamic stock indices and Islamic bonds (IB)).

The authors employed the nonadditive panel quantile regression model by Powell (2016). It measured the safe haven characteristics of gold and UCRY Price for stock indices, government bonds, Islamic stocks, and IB under gold circumstances and level of cryptocurrency uncertainty, respectively. The period spanned from 11 March 2020 to 31 December 2021.

This study discovered three findings, including: (1) gold is a strong safe haven for stocks and bonds in conventional and Islamic markets under bearish conditions; (2) UCRY Price is a strong safe haven for conventional stocks and bonds but only a weak safe haven for Islamic stocks under high crypto uncertainty; and (3) gold offers a safe haven in both emerging and developed countries, while UCRY Price provides a better safe haven in developed than in emerging countries.

Gold always wins big for safe haven properties during unstable economy. It can also win over investors who consider shariah compliant products. Therefore, it should be included in an investor's portfolio. Meanwhile, cryptocurrencies are more common for developed countries. Thus, the governments and regulators of emerging countries need to provide more guidance around cryptocurrency so that the societies have better literacy. On top of that, the investors can consider crypto to mitigate risks but with limited safe haven functions.

The originality aspects of this study include: (1) four chosen assets from conventional and Islamic markets altogether (i.e. stock indices, government bonds, Islamic stock indices and IB); (2) indicator countries selected based on the most used and owned cryptocurrencies for the SHA study; and (3) the utilization of UCRY Price as a crypto indicator and a further examination of the SHA study toward four financial assets.