Scenarios as channels of forecast advice

Today's business environment provides tougher competition than ever before, stressing the important role played by information and forecasts in decision-making. The scenario method has been popular for focused organizational learning, decision making and strategic thinking in business contexts, and yet, its use in communicating forecast information and advice has received little research attention. This is surprising since scenarios may provide valuable tools for communication between forecast providers and users in organizations, offering efficient platforms for information exchange via structured storylines of plausible futures. In this paper, we aim to explore the effectiveness of using scenarios as channels of forecast advice. An experimental study is designed to investigate the effects of providing scenarios as forecast advice on individual and group-based judgmental predictions. Participants are given time series information and model forecasts, along with (i) best-case, (ii) worst-case, (iii) both, or (iv) no scenarios. Different forecasting formats are used (i.e., point forecast, best-case forecast, worst-case forecast, and surprise probability), and both individual predictions and consensus forecasts are requested. Forecasts made with and without scenarios are compared for each of these formats to explore the potential effects of providing scenarios as forecast advice. In addition, group effects are investigated via comparisons of composite versus consensus predictions. The paper concludes with a discussion of results and implications for future research on scenario use in forecasting

Judgmental adjustments and scenario use: Individual versus group forecasts

Judgmental adjustments to model forecasts are common in organizations. Given that such adjustments may not always enhance forecast accuracy, it is essential to provide support tools to improve communication and information sharing between forecasters and decision-makers. Scenarios provide a possible toolbox to aid this process. Current work outlines a series of experiments investigating the effects of providing a set of scenarios as forecast advice on individual and group-based judgmental predictions. Findings suggest key directions for designing and implementing effective forecast management systems to benefit both the providers and users of forecasts

Do risky scenarios affect forecasts of savings and expenses?

Many people do not possess the necessary savings to deal with unexpected financial events. People’s biases play a significant role in their ability to forecast future financial shocks: they are typically overoptimistic, present-oriented, and generally underestimate future expenses. The purpose of this study is to investigate how varying risk information influences people’s financial awareness, in order to reduce the chance of a financial downfall. Specifically, we contribute to the literature by exploring the concept of ‘nudging’ and its value for behavioural changes in personal financial management. While of great practical importance, the role of nudging in behavioural financial forecasting research is scarce. Additionally, the study steers away from the standard default choice architecture nudge, and adds originality by focusing on eliciting implementation intentions and pre-commitment strategies as types of nudges. Our experimental scenarios examined how people change their financial projections in response to nudges in the form of new information on relevant risks. Participants were asked to forecast future expenses and future savings. They then received information on potential events identified as high-risk, low-risk or no-risk. We investigated whether they adjusted their predictions in response to various risk scenarios or not and how such potential adjustments were affected by the information given. Our findings suggest that the provision of risk information alters financial forecasting behaviour. Notably, we found an adjustment effect even in the no-risk category, suggesting that governments and institutions concerned with financial behaviour can increase financial awareness merely by increasing salience about possible financial risks. Another practical implication relates to splitting savings into different categories, and by using different wordings: A financial advisory institution can help people in their financial behaviour by focusing on ‘targets’, and by encouraging (nudging) people to make breakdown forecasts rather than general ones

Why/when can scenarios be harmful for judgmental demand forecasts and the following production order decisions?

Judgmental demand forecasting constitutes an integral part of inventory management and production planning activities within organizations. Among forecasting academicians and practitioners, there is the generally accepted belief that the presence of scenarios is largely beneficial for future planning and may aid the decision makers in producing these demand predictions. However, there is only circumstantial evidence and some studies report controversial findings. One recent experimental work (Gonul, Goodwin & Onkal, ISF2019) investigated the interaction between the existence of optimistic and pessimistic scenarios and the presence of time-series information alone in the task of generating demand forecasts and the following production order decisions. The findings revealed that providing scenarios worsened forecast accuracy and swayed the production order decisions further away from the optimality. What were the reasons underlying these results? Why did scenarios degrade forecasters’ accuracy? This current work is an attempt to disentangle this puzzle by trying to shed some light on these controversial findings through the application of a Generalized Estimating Equations (GEE) model. The findings from this analysis will be discussed to guide future research on scenarios and judgmental forecasting

Variability in Forest Visit Numbers in Different Regions and Population Segments before and during the COVID-19 Pandemic

In view of the prevailing preferences for health and recreation revealed by previous studies as the main expected benefits of forest visits, the research presented herein focuses on whether such expectations would translate into a significant increase in the number of forest visits (NFV) following pandemic outbreaks. In this context, a Slovak nationwide survey on forests was conducted, with the main objective of casting light on possible changes in NFV as a coping mechanism or behavioral response to the discomfort and severe restrictions stemming from coronavirus disease 2019 (COVID-19) and the related measures. The survey was administered on a statistically representative sample after the pandemic’s first wave ebbed and restrictions were eased in the summer months of 2020. Collected data were assessed using ANOVA, the results of which supported the importance of forests as places providing opportunities for restoration of mental and physical resources. Forest accessibility as represented by forest coverage and settlement size emerged as a paramount factor affecting NFV rates both before and during the COVID-19 pandemic. The pandemic and its accompanying measures affected the relationships between NFV and average per capita income, type of employment, and most importantly age, highlighting possible vulnerabilities and disadvantages in certain population segments

Developing Techniques to Support Technological Solutions to Disinformation by Analysing Four Conspiracy Networks During COVID-19

Given the role of technology and social media during the COVID-19 pandemic, the aim of this paper is to conduct a social network analysis of four COVID-19 conspiracy theories that were spread during the pandemic between March to June 2020. Specifically, the paper examines the 5G, Film Your Hospital, Expose Bill Gates, and the Plandemic conspiracy theories. Identifying disinformation campaigns on social media and studying their tactics and composition is an essential step toward counteracting such campaigns. The current study draws upon data from the Twitter Search API and uses social network analysis to examine patterns of disinformation that may be shared across social networks with sabotaging ramifications. The findings are used to generate the Framework of Disinformation Seeding and Information Diffusion for understanding disinformation and the ideological nature of conspiracy networks that can support and inform future pandemic preparedness and counteracting disinformation. Furthermore, a Digital Mindfulness Toolbox (DigiAware) is developed to support individuals and organisations with their information management and decision-making both in times of crisis and as strategic tools for potential crisis preparation