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Spotlights consumer complaints as an important signalling device — government action is undertaken as a result of them and they provide an index of consumer dissatisfaction which increases in importance as further data becomes available. Ranges across data relating to England and Wales which demonstrates that consumer durables, as a purchase category, are more likely to be involved in more complaints than other purchases. Determines that consumer complaints, therefore, are an important signalling device — even governments take action as a result of them. Proclaims that, despite the importance, consumer complaints have attracted little attention in the marketing, management and economics literature (this omission is much more marked in the UK than in the USA or the rest of western Europe). Announces that this work is primarily concerned with the 'economic determinants of consumer complaints' rather than with the socio‐economic or psychological characteristics of complaints. Continues in the second section by advancing some hypotheses concerning consumer complainants. Follows in the third section by describing the data, plus limitations, used for testing these hypotheses. Concludes in the final part with results and offers conclusive points.

Klaus Schmidbauer presented a paper entitled “On the Price Structure in Consumer Markets: Results of a Secondary Analysis of Price Comparisons of Consumer Durables”. The paper analysed price data on consumer durables collected by the German Institut für angewandte Verbraucherforschung in order to throw some light on two important issues in consumer policy. First, Schmidbauer considered the shape and form of the distributions of prices of given makes and models of consumer durables found in local markets. Inspection of these empirical distributions permitted the author to reach some conclusions about the usefulness of providing price comparison information on a public good basis. Secondly, the variety of different prices on offer in a local market (as measured by the coefficient of variation) was suggested as a measure of local price competition. Simple correlations were found between the number of prices quoted for a model and the range of those prices (positive); the average variability of prices between sellers and the price level in a given local market (negative); and the size of the local market and the price level (negative). Overall these results were taken as confirming the notion that increased price competition is reflected in an increased variation in price.

The attitudes and perceptions of New Zealanders toward current consumerism issues are outlined and compared with four other countries. Many of the opinions expressed are critical of the existing practices of business and appear to be common in the other four countries. The theory of consumer product life cycle suggesting the development of national consumer movements was not supported by the data obtained in New Zealand.

The Commission appointed jointly by the World Health Organization and the Food and Agricultural Organization continues to plod its weary way towards the establishment of Codex standards for all foods, which it is hoped will eventually be adopted by all countries, to end the increasing chaos of present national standards. We have to go back to 1953, when the Sixth World Health Assembly showed signs of a stirring of international conscience at trends in food industry; and particularly expressed “the view that the increasing use of various chemical substances had … , created a new public health problem”. Joint WHO/FAO Conferences which followed initiated inter alia international consultations and the setting up of the Joint FAO/WHO Codex Alimentarius Commission.

The purpose of this paper is to highlight the significance of placing identification marks on dentures.

This paper reviews the legislation with regard to denture marking in certain countries, various methods of denture marking and describes a simple, inexpensive, paper‐based labelling system.

Various methods have been proposed for denture marking but it is important to use a method that is simple, practical, affordable and universally acceptable.

The identification of unknown or missing persons by means of denture marking is a very successful method of identification in forensic investigation. It is also useful for patients residing in hospitals and community homes where dentures could be misplaced, particularly during cleaning by personnel where there is a chance of loss or mix‐up. The importance of denture marking should be emphasized by all law‐enforcing authorities and should be promoted among all dentists, towards making it a compulsory routine dental procedure throughout the world.

In Malaysia, denture marking, as recommended by its Ministry of Health, uses a unique coding system which can readily provide information about the wearer in whichever part of the world the person is found. The method applied is simple, practical and affordable and can easily be adapted by others. It can be of great value during times of crisis.

Outside of Europe and the United States, the knowledge on skills dynamics is scarce due to a lack of data. We therefore assess whether online data on vacancies and applications to a job board can help fill this gap. We propose a taxonomy with three broad categories – cognitive, socioemotional, and manual skills – and 14 commonly observed subcategories, which we define based on unique skills identified through keywords and expressions. The taxonomy is comprehensive but succinct, suitable for developing and emerging economies, and adapted for online data. We then develop a text-mining approach to implement the taxonomy. Based on Uruguayan data from the job board BuscoJobs, we find that our model is able to assign skills to 64% of applicants' employment spells and 94% of vacancies. While online data are usually skewed toward highly qualified work, we show that our data include meaningful numbers of vacancies and applicants of intermediate and even lower qualification levels. Our approach relies on data that are currently available in many countries, thereby allowing for country-specific analysis that does not assume that occupational skills are constant across countries. This is key as we find considerable differences between our findings and those using US O-NET data. Finally, we end with an illustration of how our approach can inform the analysis of skills dynamics. To our knowledge, we are the first to explore this approach in the context of emerging economies.

Texas instruments has a cheap starter kit for newcomers to AI computing. For a mere £135, five video tapes of the highlights of the company's satellite symposia on AI are provided. Also included are “hands‐on” PC‐compatible demonstration software, a 35 mm colour slide presentation on the theory and benefits of AI, a set of literature which contains two copies of “Understanding Artificial Intelligence” — Texas Instrument's book on AI — and a copy of an issue of Intelligence, its AI newsletter. The company will provide full details; write to: TI/AI Starter Kit, PO Box 50, Market Harborough, Leicestershire, UK.

This paper aims to demonstrate how skills taxonomies can be used in combination with machine learning to integrate diverse online datasets and reveal skills gaps. The purpose of this study is then to show how the skills gaps revealed by the integrated datasets can be used to achieve better labour market alignment, keep educational offerings up to date and assist graduates to communicate the value of their qualifications.

Using the ESCO taxonomy and natural language processing, this study captures skills data from three types of online data (job ads, course descriptions and resumes), allowing us to compare demand for skills and supply of skills for three different occupations.

This study illustrates three practical applications for the integrated data, showing how they can be used to help workers who are disrupted by technology to identify alternative career pathways, assist educators to identify gaps in their course offerings and support students to communicate the value of their training to employers.

This study builds upon existing applications of machine learning (detecting skills from a single dataset) by using the skills taxonomy to integrate three datasets. This study shows how these complementary, big datasets can be integrated to support greater alignment between the needs and offerings of educators, employers and job seekers.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.