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The literature on economic forecasting, is showing an increase in criticism, of the inaccuracy of forecasts, with major implications for economic, and fiscal policymaking. Forecasts are subject to the systemic uncertainty of human systems, considerable event-driven uncertainty, and show biases towards optimistic growth paths. The purpose of this study is to consider approaches to improve economic foresight.

This study describes the practice of economic foresight as evolving in two separate, non-overlapping branches, short-term economic forecasting, and long-term scenario analysis of development, the latter found in studies of climate change and sustainability. The unique case of Ireland is considered, a country that has experienced both steep growth and deep troughs, with uncertainty that has confounded forecasting. The challenges facing forecasts are discussed, with brief review of the drivers of growth, and of long-term economic scenarios in the global literature.

Economic forecasting seeks to manage uncertainty by improving the accuracy of quantitative point forecasts, and related models. Yet, systematic forecast failures remain, and the economy defies prediction, even in the near-term. In contrast, long-term scenario analysis eschews forecasts in favour of a set of plausible or possible alternative scenarios. Using alternative scenarios is a response to the irreducible uncertainty of complex systems, with sophisticated approaches employed to integrate qualitative and quantitative insights.

To support economic and fiscal policymaking, it is necessary support advancement in approaches to economic foresight, to improve handling of uncertainty and related risk.

While European Union Regulation (EC) 1466/97 mandates pursuit of improved accuracy, in short-term economic forecasts, there is now a case for implementing advanced foresight approaches, for improved analysis, and more robust decision-making.

Building economic resilience and adaptability, as part of a sustainable future, requires both long-term strategic planning, and short-term policy. A 21st century policymaking process can be better supported by analysis of alternative scenarios.

To the best of the authors’ knowledge, the article is original in considering the application of scenario foresight approaches, in economic forecasting. The study has value in improving the baseline forecast methods, that are fundamental to contemporary economics, and in bringing the field of economics into the heart of foresight.

The purpose of this article is to present a systematic review of scientific production on career stages in the last decade (2011–2020). More specifically, it seeks to understand the methodological approaches, how career stages have been operationalized in research in the Management field, and the main results of these researches.

The authors searched articles about career stages on the Web of Science database published between 2011 and 2020. The final portfolio for the systematic review included 20 article based on pre-established criteria for the selection.

The results present an overview of these articles, as well as the methodological approaches used. The authors confirmed that there is no consensus on the operationalization of the career stage. Five topics associated with career stages were discussed: workers' attitudes and behaviors; training and mentoring; intentions; perception of success and work-life balance; and work values.

The authors found no other studies concerning the review of scientific production on career stages and divergences in the operationalization of the theme. However, considering the large number of research studies that deal with careers and their stages, it is relevant to discuss how the career stages can be operationalized and whether their operationalization is valid.

Young people’s attachment to their smartphones is well-documented, with smartphones often described as prostheses. While prior studies typically assume a clear human/machine divide, this paper aims to build on posthuman perspectives, exploring intercorporeality, the blurring of human/technology boundaries, between emerging adults and their smartphones. The paper aims to discuss these issues.

Drawing on assemblage theory, this interpretive study uses smartphone diaries and friendship pair/small group discussions with 27 British emerging adults.

Participants in this study are characterized as homo prostheticus, living with and through their phones, treating them as extensions of their mind and part of their selves as they navigated between their online and offline, private and social lives. Homo prostheticus was part of a broader assemblage or amalgamation of human and non-human components. As these components interacted with each other, the assemblage could be strengthened or weakened by various technological, personal and social factors.

These qualitative findings are based on a particular sample at a particular point in time, within a particular culture. Further research could explore intercorporeality in human–smartphone relationships among other groups, in other cultures.

Although other studies have used prosthetic metaphors, this paper contributes to understanding of smartphones as a prostheses in the lives of emerging adults, highlighting intercorporeality as a key feature of homo prostheticus. It also uses assemblage theory to contextualize homo prostheticus and explores factors strengthening or weakening the broader human–smartphone assemblage.

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

This paper aims to develop a credit-risk model in which firms face rollover risk, and the markets for defaulted assets are segmented due to entry costs. The paper shows that reducing the entry costs in this economy may decrease the total surplus of the economy. This outcome can arise because when market barriers are lifted, the gap between the liquidation prices across the markets will shrink, but then the market that would experience a price drop may face more bankruptcies because the rollover risk will increase in that market. The paper describes under which condition such an intervention policy improves or hurts the total surplus.

This paper examines the process optimization method of the online sales model of information product demand concerning the spillover effect. It illustrates the spillover effect (SE) of online product demand compared with traditional market demand. Also, optimized the SE for the ethical and ordinary consumer.

This article primarily focused on two types of models for online marketing: one is wholesales, and another is the agency. Firstly, the wholesale and agency models without SE and the wholesale and agency models with SE are constructed, respectively, to realize the SE in different sales models. Secondly, online channel participants' optimal price, demand and profit under variant conditions are compared and analyzed. Finally, efficient supply chain theory is optimized for the decision-making of online marketing consumers using an equation-based comparative analysis method.

The study found that when SEs are not considered, stronger piracy regulation makes online channel participants more beneficial. When the positive SE is strong, it is detrimental to manufacturers. When SEs are not considered, online channel participants only reach Pareto in agency mode. Pareto optimality can be achieved in wholesale and agency modes when SEs are considered.

The research has practical implications for an effective supply chain model for online marketing. This is the first algorithm-based comparative study concerning theoretical spillover effect analysis in supply chain management.

The authors explore the hypothesis that some movements in commodity prices are anticipated (news shocks) and can trigger aggregate fluctuations in small open emerging economies. This paper aims to discuss the aforementioned objective.

The authors build a multi-sector dynamic stochastic general equilibrium model with endogenous commodity production. There are five exogenous processes: a country-specific interest rate shock that responds to commodity price fluctuations, a productivity (TFP) shock for each sector and a commodity price shock. Both TFP and commodity price shocks are composed of unanticipated and anticipated components.

The authors show that news shocks to commodity prices lead to higher output, investment and consumption, and a countercyclical movement in the trade-balance-to-output ratio. The authors also show that commodity price news shocks explain about 24% of output aggregate fluctuations in the small open economy.

Given the importance of both anticipated and unanticipated commodity price shocks, policymakers should pay attention to developments in commodity markets when designing policies to attenuate the business cycles. Future research should investigate the design of optimal fiscal and monetary policies in SOE subject to news shocks in commodity prices.

This paper contributes to the knowledge of the sources of fluctuations in emerging economies highlighting the importance of a new source: news shocks in commodity prices.