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The purpose of this paper is to analyze the credit channel effects on investment behavior for the US and the Euro area.

This paper uses the dynamic stochastic general equilibrium model and calibrates a version of the Carlstrom and Fuerst’s (1997) agency cost model of business cycles with time-varying uncertainty in the technology shocks that affect capital production. To highlight the differences between the US and European financial sectors, the paper focuses on two key components of the lending channel: the risk premium associated with bank loans and the bankruptcy rates.

This paper shows that the effects of minor differences in the credit market translate into large, persistent and asymmetric fluctuations in real and financial variables and depend on the type of shocks. The results imply that the Euro areas supply elasticities for capital are less elastic than that of the USA following a technology shock. Finally, the authors find that the adverse impact of uncertainty shocks is heterogeneous across countries and amplified by the steady-state bankruptcy rate and risk premium.

This paper quantifies the effects of uncertainty shocks when there is a credit channel due to asymmetric information between lenders and borrowers for the Euro area countries, and then compares the results to that of the USA. This paper shows that financial accelerator mechanism could potentially play a significant role in business cycles in the Euro area. This result directly lends one to conclude the following: the credit channel that affects the financial sector does indeed matter for macroeconomic behavior, and that policy makers should be attentive in smoothing out uncertainties if the economic policies are to lower the business and financial cycle volatilities.

Although networked hospitality businesses as Airbnb are a recent phenomenon, a rapid growth has made them a serious competitor for the hospitality industry with important consequences for tourism and for tourist destinations. The purpose of this paper is to analyse the nature of the phenomenon, its potential further development in the next five years and the impact this developments will have on tourism, on hotels and on city destinations.

A literature study, combined with scenario workshops and a Delphi panel, were used to map current trends and uncertainties. With this input, future scenarios were elaborated using the Global Business Network (“scenario cross”) method.

Network platforms as Airbnb are often classified under something called the “Sharing Economy”, a denomination that obscures their true nature. Airbnb is a challenging innovation to which traditional hospitality will have to respond. Its impact has at the same time led to a call for regulatory policies. The definition of these policies and the evolution of tourism are variables that determine future scenarios. Attempts to ban the phenomenon mean a disincentive to innovation and protect oligopolistic markets; more receptive policies may have the desired results if tourism grows moderately but in booming destinations they may lead to a harmful commercialization.

Until now, Airbnb has been described in conceptual studies about the so-called “Sharing economy”, or more recently in empirical studies about isolated effects of holiday rentals. This paper contextualizes the evolution of networked hospitality and seeks to synthesize the sum of its impacts, thus enabling businesses and local governments to define positions and strategies.

This study aims to focus on building a conceptual closed-loop vaccine supply chain (CLVSC) to decrease vaccine wastage and counterfeit/fake vaccines.

Through a focused literature review, the framework for the CLVSC is described, and the system dynamics (SD) research methodology is used to build a causal loop diagram (CLD) of the proposed model.

In the battle against COVID-19, waste management systems have become overwhelmed, which has created negative environmental and extremely hazardous societal impacts. A key contributing factor is unused vaccine doses, shown as a source for counterfeit/fake vaccines. The findings identify a CLVSC design and transshipment operations to decrease vaccine wastage and the potential for vaccine theft.

This study contributes to establishing a pandemic-specific VSC structure. The proposed model informs the current COVID-19 pandemic as well as potential future pandemics.

A large part of the negative impact of counterfeit/fake vaccines is on human well-being, and this can be avoided with proper CLVSC.

This study develops a novel overarching SD CLD by integrating the epidemic model of disease transmission, VSC and closed-loop structure. This study enhances the policymakers’ understanding of the importance of vaccine waste collection, proper handling and threats to the public, which are born through illicit activities that rely on stolen vaccine doses.

Although scholars argue that artificial intelligence (AI) represents a tool to potentially smoothen the bullwhip effect in the supply chain, only little research has examined this phenomenon. In this article, the authors conceptualize a framework that allows for a more structured management approach to examine the bullwhip effect using AI. In addition, the authors conduct a systematic literature review of this current status of how management can use AI to reduce the bullwhip effect and locate opportunities for future research.

Guided by the systematic literature review approach from Durach et al. (2017), the authors review and analyze key attributes and characteristics of both AI and the bullwhip effect from a management perspective.

The authors' findings reveal that literature examining how management can use AI to smoothen the bullwhip effect is a rather under-researched area that provides an abundance of research avenues. Based on identified AI capabilities, the authors propose three key management pillars that form the basis of the authors' Bullwhip-Smoothing-Framework (BSF): (1) digital skills, (2) leadership and (3) collaboration. The authors also critically assess current research efforts and offer suggestions for future research.

By providing a structured management approach to examine the link between AI and the bullwhip phenomena, this study offers scholars and managers a foundation for the advancement of theorizing how to smoothen the bullwhip effect along the supply chain.