Aim/Purpose: This paper aims to empirically quantify the financial distress caused by the COVID-19 pandemic on companies listed on Amman Stock Exchange (ASE). The paper also aims to identify the most important predictors of financial distress pre- and mid-pandemic. Background: The COVID-19 pandemic has had a huge toll, not only on human lives but also on many businesses. This provided the impetus to assess the impact of the pandemic on the financial status of Jordanian companies. Methodology: The initial sample comprised 165 companies, which was cleansed and reduced to 84 companies as per data availability. Financial data pertaining to the 84 companies were collected over a two-year period, 2019 and 2020, to empirically quantify the impact of the pandemic on companies in the dataset. Two approaches were employed. The first approach involved using Multiple Discriminant Analysis (MDA) based on Altman’s (1968) model to obtain the Z-score of each company over the investigation period. The second approach involved developing models using Artificial Neural Networks (ANNs) with 15 standard financial ratios to find out the most important variables in predicting financial distress and create an accurate Financial Distress Prediction (FDP) model. Contribution: This research contributes by providing a better understanding of how financial distress predictors perform during dynamic and risky times. The research confirmed that in spite of the negative impact of COVID-19 on the financial health of companies, the main predictors of financial distress remained relatively steadfast. This indicates that standard financial distress predictors can be regarded as being impervious to extraneous financial and/or health calamities. Findings: Results using MDA indicated that more than 63% of companies in the dataset have a lower Z-score in 2020 when compared to 2019. There was also an 8% increase in distressed companies in 2020, and around 6% of companies came to be no longer healthy. As for the models built using ANNs, results show that the most important variable in predicting financial distress is the Return on Capital. The predictive accuracy for the 2019 and 2020 models measured using the area under the Receiver Operating Characteristic (ROC) graph was 87.5% and 97.6%, respectively. Recommendations for Practitioners: Decision makers and top management are encouraged to focus on the identified highly liquid ratios to make thoughtful decisions and initiate preemptive actions to avoid organizational failure. Recommendation for Researchers: This research can be considered a stepping stone to investigating the impact of COVID-19 on the financial status of companies. Researchers are recommended to replicate the methods used in this research across various business sectors to understand the financial dynamics of companies during uncertain times. Impact on Society: Stakeholders in Jordanian-listed companies should concentrate on the list of most important predictors of financial distress as presented in this study. Future Research: Future research may focus on expanding the scope of this study by including other geographical locations to check for the generalisability of the results. Future research may also include post-COVID-19 data to check for changes in results.

Purpose Project management scholars and practitioners have long debated how best to harness social interactions to optimise knowledge exchange and enhance stakeholder alignment and value. This study aims to assist project managers to understand and manage fuzziness and create enduring front-end value. It views the project life cycle as a potential source of co-created value. The paper uses a social capital lens to provide a deeper understanding of the project front-end; it uses a three-dimensional view (structural, relational, cognitive) to explore how stakeholder social capital can overcome front-end fuzziness to enhance decision-making and, thus, value creation. Design/methodology/approach Semi-structured interviews were conducted with senior managers from teleconnections companies, which, when combined with secondary data, established the impact, nature and dimensions of social capital within a project management setting. Findings The research found that social capital can help to reduce complexity, uncertainty and equivocality in the early stages of projects, making them more clearly defined and thus helping to create greater stakeholder value in the later stages of the project. A surprising finding was that some project team members engaged in intentional equivocality to try to promote their own benefits rather than those of the organisation. Originality/value This paper reconceptualises the impact of social capital on stakeholder value creation in the front-end of projects. The paper contributes to a more holistic view of the front-end of project management, focusing social capital to reduce the sources of front-end fuzziness.