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The purpose of this theme issue is to explore the enduring changes and innovations shaping the future of the event industry in the post-pandemic world. While much of the existing literature focuses on the immediate impacts of COVID-19, this issue aims to provide a comprehensive analysis of the broader transformations, including the integration of sustainability, emerging technologies, and evolving event formats.

The theme issue encompasses a range of methodologies, including systematic reviews, bibliometric analyses, and in-depth case studies. The papers examine various aspects of the event industry, such as the adoption of hybrid event formats, the role of new technologies, and the importance of sustainability in event planning. Each paper contributes unique insights into the future direction of the industry by analyzing trends, technologies, and practices that are defining the next era of event management.

The findings highlight a significant shift in the event industry towards sustainability, with an increasing emphasis on eco-friendly practices, waste reduction, and the use of sustainable materials. Emerging technologies are also transforming the landscape, enabling more personalized and immersive event experiences. The rise of hybrid and micro-events is identified as a key trend, providing flexibility and inclusivity while maintaining the benefits of in-person interactions. These developments suggest a permanent change in consumer expectations and engagement strategies within the event industry.

This theme issue offers a holistic analysis of the innovative practices, technologies, and trends that are defining the future of the event industry. By bridging the gap between immediate pandemic responses and long-term industry transformations, it provides valuable insights for academics, practitioners, and policymakers looking to navigate the next era of event management.

The purpose of this paper is first, to investigate empirically the plurality of understanding surrounding sustainability held by those working in the business sector, and second, to consider the likelihood of a dialogic accounting that would account for the plurality of perspectives identified.

The subjects of this study are those people actively working to incorporate sustainability within New Zealand business, both business people and their sustainability advisors. Participant’s subjective understanding is investigated using Q methodology, a method used widely by social science researchers to investigate typical views on a particular topic, from an analysis of the order in which participants individually sort a sample of stimuli. In this study, the stimuli were opinion statements.

Five typical understandings of sustainable development were identified, including understandings more usually attributed to business antagonists than business. Conflicts between environment and development are acknowledged by most participants. However, an agonistic debate that will create spaces, practices, and institutions through which marginalised understandings of sustainable development might be addressed and contested, is yet to be established and will not be easy.

The paper contributes to the few empirical investigations of the plurality of understandings of sustainability held by those people working to incorporate sustainability within business. It is further distinguished by the authors attempt to describe divergent beliefs and values, absent from their immediate business context, and absent from any academic priming. The paper also provides an illustrative example of the application of Q methodology, a method not commonly used in accounting research.

THE catalogue, as a library appliance of importance, has had more attention devoted to it than, perhaps, any other method or factor of librarianship. Its construction, materials, rules for compilation and other aspects have all been considered at great length, and in every conceivable manner, so that little remains for exposition save some points in the policy of the catalogue, and its effects on progress and methods. In the early days of the municipal library movement, when methods were somewhat crude, and hedged round with restrictions of many kinds, the catalogue, even in the primitive form it then assumed, was the only key to the book‐wealth of a library, and as such its value was duly recognized. As time went on, and the vogue of the printed catalogue was consolidated, its importance as an appliance became more and more established, and when the first Newcastle catalogue appeared and received such an unusual amount of journalistic notice, the idea of the printed catalogue as the indispensable library tool was enormously enhanced from that time till quite recently. One undoubted result of this devotion to the catalogue has been to stereotype methods to a great extent, leading in the end to stagnation, and there are places even now where every department of the library is made to revolve round the catalogue. Whether it is altogether wise to subordinate everything in library work to the cult of the catalogue has been questioned by several librarians during the past few years, and it is because there is so much to be said against this policy that the following reflections are submitted.

Construction plant breakdown affects projects by prolonging duration and increasing costs. Therefore, prediction of plant breakdown, as a precursor to conducting timely maintenance works, cannot be underestimated. This paper thus sought to develop a model for predicting plant breakdown time from a sequence of discrete plant breakdown measurements that follow non‐random orders. An ARIMA (1,1,0) model was constructed following experimentation with exponential smoothening. The model utilised breakdown observations obtained from six wheeled loaders that had operated a total of 14,467 hours spread over a 300‐week period. The performance statistics revealed MAD and RMSE of 5.03 and 5.33 percent respectively illustrating that the derived time series model is accurate in modelling the dependent variable. Also, the F‐statistics from the ANOVA showed that the type and frequency of fault occurrence as a predictor variable is significant on the model's performance at the five percent level. Future work seeks to consider a more in depth multivariate time series analyses and compare/contrast the results of such against other deterministic modelling techniques.

Effective management and utilisation of plant history data can considerably improve plant and equipment performance. This rationale underpins statistical and mathematical models for exploiting plant management data more efficiently, but industry has been slow to adopt these models. Reasons proffered for this include: a perception of models being too complex and time consuming; and an inability of their being able to account for dynamism inherent within data sets. To help address this situation, this research developed and tested a web‐based data capture and information management system. Specifically, the system represents integration of a web‐enabled relational database management system (RDBMS) with a model base management system (MBMS). The RDBMS captures historical data from geographically dispersed plant sites, while the MBMS hosts a set of (Autoregressive Integrated Moving Average – ARIMA) time series models to predict plant breakdown. Using a sample of plant history file data, the system and ARIMA predictive capacity were tested. As a measure of model error, the Mean Absolute Deviation (MAD) ranged between 5.34 and 11.07 per cent for the plant items used in the test. The Root Mean Square Error (RMSE) values also showed similar trends, with the prediction model yielding the highest value of 29.79 per cent. The paper concludes with direction for future work, which includes refining the Graphical User Interface (GUI) and developing a Knowledge Based Management System (KBMS) to interface with the RDBMS.

David M. Gordon advanced labour economics with his theory of labour market segmentation, in which jobs rather than the marginal productivity of individual workers were the unit of analysis. He advanced economic historiography and macroeconomics by conceptualising social structures of accumulation – a framework built on the foundation of his institutionalist training and enriched by his study of Marxist economics. By appropriating methods from other social science disciplines into econometrics, he augmented empirical analysis in economics. He was a founding member of the Union of Radical Political Economics and its journal, the Review of Radical Political Economics – that advanced and promoted heterodox, radical, and Marxist economists in the United States. His contributions to economics, to organised labour, and to the New School for Social Research, where I studied with him, were stunning.

Part 1 lays out some context about the New School Graduate Faculty where Gordon taught. Part 2 explores what historical forces, including his family, led to his expansive creativity. Part 3 summarises how he expanded labour economics to include the relations as well as the technology of production, linked his understanding of the production process to a historical materialist view of labour in the United States, then extended that to econometric analyses of the US macroeconomy. Part 4 presents a bibliometric analysis to provide some idea of the impact of his work. I end with some concluding remarks.

Hiring, selecting or assessing plant operatives' proficiency in the UK construction industry is an increasingly difficult task. A number of plant operator certification schemes are available to practitioners and each scheme trains to a myriad of bespoke standards. Consequently, the decision to employ a candidate often rests upon the employer's intuition and judgement and creates an unnecessary dilemma. To address this aforementioned problem, findings of research work that modelled plant operators' maintenance proficiency is presented. A UK nationwide survey was conducted to elicit plant professional opinion on what ‘training and educational’ (T&E) attributes constitute ‘good’ operator proficiency. The data was then arranged into three categories of operator maintenance proficiency: good, average and poor Multivariate Discriminant Analysis (MDA) was used on 75 percent of a simulated data set. The model utilised five T&E attributes, namely: duration of training provided, operator holder of alternative training card (not Certificate of Training Achievement (CTA) or Scottish/National Vocational Qualifications (S/NVQ)), operator's oral communication skills, operator's planning skills and operator's mechanical knowledge. Performance analysis revealed that model classification accuracy was 89.10 percent. The remaining 25 percent hold out sample was then modelled for validation purposes using the derived MDA model. Accuracy of the sub‐sample model was high at 77.60 percent whilst a paired sample T‐tests for the 75 percent and 25 percent sample data established that there was no significant statistical difference between actual and predicted classifications. Future work is proposed that aims to model other factors that influence operator maintenance proficiency; namely, work situational, motivational management and personal factors.