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This paper highlights the social context of common mental disorders in primary care and the paucity of evidence relating to effective social interventions. It introduces the ABC‐E Model of Emotion, which combines social interventions with psychological therapy, and discusses how the implementation of the new role of graduate primary care mental health worker (GPCMHW) provides an opportunity for holistic practice in helping individuals experiencing mild to moderate mental health difficulties in primary care. It provides a case example of the implementation of the ABC‐E model and makes recommendations for further research including the evaluation of the model and GPCMHW training programmes.

This paper aims to investigate the prevalence of asset misappropriation at the workplace and examines the dominant factors that influence individuals to misappropriate assets at the workplace. Relying on the most recent theory on fraud (the stimulus/pressure, capability, opportunity, rationalization and ego (S.C.O.R.E. model) as the theoretical basis, the study examines the effect of pressure, rationalization, capability, opportunity/strength of internal control system and ego on asset misappropriation at the workplace while controlling for the effect of ethical values.

A total of 883 valid responses from individuals working in various organizations in Ghana were collected by means of a self-administered questionnaire. The hypothesized relationships of the study were tested by means of a structural model analysis using the partial least square based structural equation modelling technique.

Results from the structural model analysis demonstrate that individuals misappropriate assets at their workplace due to pressures they face, their ability to rationalize their actions as not wrong, their capabilities and their egos. The results, however, indicate that the extent to which an individual will misappropriate asset depends, to a large extent, on the person’s perception of the strength of internal control mechanisms at the workplace. The findings of the study make significant contributions to the fraud discourse.

Theoretically, the study is among the first to provide empirical support for the applicability of the S.C.O.R.E. model in the fraud literature. Again, this study extends knowledge on occupational fraud literature by examining an area that has received the least research attention: asset misappropriation. The study also highlights the important role of internal controls in reducing the occurrence of asset misappropriation at the workplace.

This paper aims to elaborate on the theory of fraud by enhancing the existing theories behind the factors that force people to commit fraud.

The paper reviews the most commonly used and widely accepted models for explaining why people commit fraud – the fraud triangle, the fraud diamond, the fraud scale and the MICE model. The author argues that these models need to be updated to adapt to the current developments in the field and the ever-growing fraud incidents, both in frequency and severity, and builds on the theoretical background to create a new model so as to enhance the understanding behind the major factors which lead to the commitment of fraud.

The author identifies a major element – ego – which plays a crucial role in compelling people to commit fraud and concludes in the formation of the S.C.O.R.E. model, which is graphically depicted in the fraud pentagon. He goes further by adding the factor collusion to better apply in cases of white-collar crimes.

The paper develops the S.C.O.R.E. model to contribute to the development of fraud theory by identifying the key factors that play a major role in whether fraud will actually occur and acting as a theoretical benchmark for all future reference.

This study aims to use a novel methodology to investigate the performance of several multivariate value at risk (VaR) and expected shortfall (ES) models implemented to assess the risk of an equally weighted portfolio consisting of high-frequency (1-min) observations for five foreign currencies, namely, EUR/USD, GBP/USD, EUR/JPY, USD/JPY and GBP/JPY.

By applying the multiplicative component generalised autoregressive conditional heteroskedasticity (MC-GARCH) model on each return series and by modelling the dependence structure using copulas, the 95 per cent intraday portfolio VaR and ES are forecasted for an out-of-sample set using Monte Carlo simulation.

In terms of VaR forecasting performance, the backtesting results indicated that four out of the five models implemented could not be rejected at 5 per cent level of significance. However, when the models were further evaluated for their ES forecasting power, only the Student’s t and Clayton models could not be rejected. The fact that some ES models were rejected at 5 per cent significance level highlights the importance of selecting an appropriate copula model for the dependence structure.

To the best of the authors’ knowledge, this is the first study to use the MC-GARCH and copula models to forecast, for the next 1 min, the VaR and ES of an equally weighted portfolio of foreign currencies. It is also the first study to analyse the performance of the MC-GARCH model under seven distributional assumptions for the innovation term.

The increasing societal requirement requests higher education institutions to be more responsive to socioeconomic needs and new governmental demands. This study aims to present a self-developed multidimensional quality assurance and assessment model for higher education institutions – R.I.S.E model (relevance, impact, significance and excellence) – as a tool for quality assessment in higher education institutions.

The model was first described at a conceptual level, followed by the examination of its applicability by presenting a case of a university in Macau to substantiate the model with real-life evidence.

Results showed that the model can be used as an assessment tool to analyze, evaluate and reflect upon the status quo of higher education institutions. Facilitators can use all or part of the model either as a useful baseline to assess performance and prioritize “next steps” or to compare performance across time to determine progress in achieving goals and objectives.

The new model proposed in this study presents multiple perspectives when assessing higher education systems, especially in the transforming stage of a university, to meet upgrading requirements from both the society and the academic community.

The purpose of this study is to examine the accuracy of combined models with the individual models in terms of forecasting Euro against US dollar during COVID-19 era. During COVID, the euro shows sharp fluctuation in upward and downward trend; therefore, this study is keen to find out the best-fitted model which forecasts more accurately during the pandemic.

The descriptive design has been adopted in this research. The three univariate models, i.e. autoregressive integrated moving averages (ARIMA), Naïve, exponential smoothing (ES) model, and one multivariate model, i.e. nonlinear autoregressive distributive lags (NARDL), are selected to forecast the exchange rate of Euro against the US dollar during the COVID. The above models are combined via equal weights and var-cor methods to find out the accuracy of forecasting as Poon and Granger (2003) showed that combined models can forecast better than individual models.

NARDL outperforms all remaining individual models, i.e. ARIMA, Naïve and ES. By applying a combination of different models via different techniques, the combination of NARDL and Naïve models outperforms all combination of models by scoring the least mean absolute percentage error value, i.e. 1.588. The combined forecasting of NARDL and Naïve techniques under var-cor method also outperforms the forecasting accuracy of individual models other than NARDL. It means the euro exchange rate against the US dollar which is dependent upon the macroeconomic fundamentals and recent observations of the time series.

The findings could help the FOREX market, hedgers, traders, businessmen, policymakers, economists, financial managers, etc., to minimize the risk indulged in global trade. It also helps to produce more accurate results in different financial models, i.e. capital asset pricing model and arbitrage pricing theory, because their findings may not be useful if exchange rate fluctuations do not trace effectively.

The NARDL models have been applied previously in different time series and only limited to the asymmetric or symmetric relationships. This study is using it for the forecasting exchange rate which is almost abandoned in earlier literature. Furthermore, this study combined the NARDL with univariate models to produce the accuracy which itself is a novelty. Moreover, the findings help to enhance the effectiveness of different financial theories as well.

This work aims to measure the performance of an electric motors supply chain (SC) by using the Triple E performance measurement model to assess three performance dimensions simultaneously: efficiency, efficacy and environmental impact.

This research presents a real case of a Brazilian company as an example for applying the Triple E performance measurement model and the discrete-event simulation to assess the performance of an SC.

Performance measurements for the three dimensions were the following: (1) for efficiency, a high inventory cost in the SC, driven by the distribution center (DC) (49.7% total cost); an order cycle time operating with an average of 21.7 days and a logistic channel transport capacity of 88%; (2) for efficacy, a service level of 98% for all channels; (3) for environmental impact, the SC emits a total of 395,733 kg of CO₂ annually, with the DC and the regional distribution center (RDC2) being the largest emitters.

This work allowed to measure the performance of an SC interface (manufacturing process, a DC and three regional distribution centers). It was possible to measure the inventory holding cost and out-of-stock inventory costs, order cycle time, SC service level, transport capacity utilization and CO₂ emissions in the transportation process of each SC stage and the whole SC. This study can be used as a decision support guide for academics and practitioners to measure and improve the SC performance.

Similar to other parts of the United States, its southern region is still wrestling with the implications of the resegregation of America’s schools. Unlike other parts of the country, however, the Deep South demons are rooted in a vastly different historical context. This chapter offers an historical analysis of the educational problems in the Deep South, with strong emphasis on gifted programming. Further, in this chapter, we present and describe a framework that could guide educators as they strive to identify giftedness among children of color and implement programming in a culturally responsive manner.

This paper aims to investigate barriers to employee participation in voluntary formal training and development opportunities from the perspective of employees in small engineering businesses.

An exploratory qualitative methodology involving data collection via site visits and in-depth semi-structured interviews with 20 employees in five small engineering businesses was used. Interviews explored the role of developmental proactivity and employees’ perceptions of conditions in the immediate work environment and industry sector that represent barriers to their participation in formal training and development. Interview transcripts were analysed using thematic analysis.

Three key findings are as follows. First, proactive behaviour regarding access to external training and development is muted in small business settings because of strong resource allocation norms. Second, factors in the internal work environment rather than the industry sector constitute the major barriers to training and development. Third, owner-managers and employees appear to have significantly differing perspectives of barriers to training and development.

The findings suggest avenues for future research. These include examining how workplace norms influence employee behaviour with regard to accessing formal training and development and investigating the learning strategies that employees use to compensate for a lack of access to training and development.

Research into relatively low levels of employee participation in formal training and development in small businesses is deficient because it predominantly involves surveys of owner-managers’ opinions. This study is novel because it seeks to generate new insights not previously articulated by employees. The study yielded four propositions that have practical and research implications.

This paper sets out to identify key success criteria for e‐business and consider emergent models which integrate the most value‐adding characteristics in response to the requirements of both consumers and business organisations.

In assessing differing models of B2C/C2C, the paper uses an adapted evaluation framework which brings together key factors identified from the literature. A Likert scale exercise undertaken enables the authors to subsequently rank models.

Analysis of the results from the differing models identifies 14 primary success factors from which the paper develops a modified ontology of e‐business. This is attributed to the evolving role of internet communities and social networking; the impact of “mobbing” and demand aggregation on rate of growth; and the effects of the “long tail” in differentiating markets into high‐diversity short‐run products.

It is recognised that the scoring exercise is based on a limited range of exemplars for each e‐model, which are ranked by a relatively small panel of experts. The expertise of those participating may also have constrained the validity of the results. However, there is significant consistency between the responses from each, indicating that the results are not unrealistic.

The paper discusses e‐business from a differing view to existing literature, which considers emergent trends such as the effects of the “long tail” and “mobbing” in isolation, rather than focusing on a discussion of value chain factors per se. The authors develop a modified ontology of e‐business based on a practical analysis of e‐business exemplars rather than comparative studies based solely on literature reviews.