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In this case study, we offer an analysis of feedback from a student experience survey completed by Black undergraduate students who received proactive, targeted coaching and mentoring support during 2021–2022. All the students were studying at a large higher education institution in the United Kingdom which offers a broad range of degree courses by distance learning.

This paper reports on the intervention delivered and analyses the student experience of being offered, and receiving, proactive coaching and mentoring. It is based on the responses of 102 students who engaged with the experience survey after having self-selected to receive the intervention. What follows is an analysis of their experiences using a qualitative in vivo approach based on word frequency in students’ free-text comments.

The findings presented are that, in this intervention, students who self-select to receive coaching and mentoring support experience tangible (self-reported) behaviour changes with potentially longer term benefits for their studies. These include improved self-confidence and self-efficacy, increased proactive help-seeking behaviour, greater recognition of strengths and achievement and personal growth and self-awareness.

In presenting this case study, we aim to contribute to the growing corpus of practitioner case studies and research papers that show the benefits of coaching and mentoring in higher education and – more specifically – why coaching and mentoring can be a worthwhile targeted intervention for students from underrepresented backgrounds. This lends support to the growing consensus that students with positive, proactive help-seeking behaviours perform better than students not able to access support (Byrne et al., 2014). We conclude the case study with some practical implications for providers looking to provide targeted support to students.

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.

This study aims to determine whether or not fashion retail brands can maintain their essence by providing personalized care through conventional face-to-face interactions or the use of e-services.

An exploratory investigation is being conducted to attain this goal. According to the findings of this research, Chatbots have an impact on consumer loyalty. The quality of a Chatbot’s system, service and information are all critical to providing a positive consumer experience.

The study concluded that Chatbot e-services might potentially enable dynamic and fascinating interactions between firms and their consumers. To personalize a Chatbot, firms might change the tone of the language used. Customers are more likely to use a Chatbot if it resembles a real person, which increases their pleasure and confidence in the product.

More precisely, the emphasis of the inquiry was on Chatbot, a relatively new digital tool that offers user-friendly, personalized and one-of-a-kind support to customers. Using information supplied by consumers, the authors examine a five-dimensional model that gauges how customers feel about Chatbots in terms of their ability to communicate with users, offer amusement, be trendy, personalize interactions and solve problems.