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In the wake of labor shortages in the retail industry, there is value in highlighting a business case for employing neurodivergent individuals. Drawing on signaling theory, this study explores whether perceived neurodiversity management (neurodiversity policies and adjustments) helps enhance neurodiversity awareness and affective commitment and whether affective commitment leads to lower turnover intention.

A cursory content analysis of publicly available documents of randomly selected four retail organizations was undertaken, which was followed by an online survey of the Australian retail workforce, leading to 502 responses from supervisors and employees.

The content analysis shows that retail organizations barely acknowledge neurodiversity. The findings of the main study indicate that neurodiversity policies are positively associated with both neurodiversity awareness and affective commitment, while adjustments were positively linked to affective commitment. Moreover, affective commitment was negatively associated with turnover intention. Affective commitment also mediated the negative effects of neurodiversity policies and adjustments on turnover intention.

This study supports, extends and refines signaling theory and social exchange theory. It addresses knowledge gaps about the perceptions of co-workers and supervisors in regard to neurodiversity management. It provides unprecedented evidence for a business case for the positive attitudinal outcomes of neurodiversity policies and adjustments. The findings can help managers manage neurodiversity for positive attitudinal outcomes.

This study aims to evaluate the effectiveness of machine learning models to yield profitability over the market benchmark, notably in periods of systemic instability, such as the ongoing war between Russia and Ukraine.

This study made computational experiments using support vector machine (SVM) classifiers to predict stock price movements for three financial markets and construct profitable trading strategies to subsidize investors’ decision-making.

On average, machine learning models outperformed the market benchmarks during the more volatile period of the Russia–Ukraine war, but not during the period before the conflict. Moreover, the hyperparameter combinations for which the profitability is superior were found to be highly sensitive to small variations during the model training process.

Investors should proceed with caution when applying machine learning models for stock price forecasting and trading recommendations, as their superior performance for volatile periods – in terms of generating abnormal gains over the market – was not observed for a period of relative stability in the economy.

This paper’s approach to search for financial strategies that succeed in outperforming the market provides empirical evidence about the effectiveness of state-of-the-art machine learning techniques before and after the conflict deflagration, which is of potential value for researchers in quantitative finance and market professionals who operate in the financial segment.

Increasing overhang of serviced apartments poses a serious concern to the national property market. This study aims to examine the impacts of macroeconomic determinants, namely, gross domestic product (GDP), consumer confidence index (CF), existing stocks (ES), incoming supply (IS) and completed project (CP) on serviced apartment price changes.

To achieve more accurate, quality price changes, a serviced apartment price index (SAPI) was constructed through a self-developed hedonic price index model. This study has collected 1,567 transaction data in Kuala Lumpur, covering 2009Q1–2018Q4 for price index construction and data were analysed using the vector autoregressive model, the vector error correction model and the fully modified ordinary least squares (OLS) (FMOLS).

Results of the regression model show that only GDP, ES and IS were significantly associated with SAPI, with an R² of 0.7, where both ES and IS have inverse relationships with SAPI. More precisely, it is predicted that the price of serviced apartments will be reduced by 0.56% and 0.21% for every 1% increase in ES and IS, respectively.

Therefore, government monitoring of serviced apartments’ future supply is crucial by enforcing land use-planning regulations via stricter development approval of serviced apartments to safeguard and achieve more stable property prices.

By adopting an innovative approach to estimating the response of price change to supply and demand in a situation where there is no price indicator for serviced apartments, the study addresses the knowledge gap, especially in terms of understanding what are the key determinants of, and to what extent they influence, the SAPI.

Overcrowding continues to afflict emergency departments (EDs), and its attendant consequences are becoming increasingly severe. The burden of the COVID-19 pandemic is further escalating the situation worldwide. One of the most critical questions is how to adequately quantify what constitutes overcrowding and determine implications for operations management in improving service efficiency. This paper aims to discuss the aforementioned.

The authors propose the time and class complexity measures for ED service systems, taking into account important patient-level and system characteristics. Using an extensive data set from a Canadian ED, the authors investigate the performance of complexity-based measures in predicting service delays.

The authors find that the complexity measure is potentially more important than some well-known crowding metrics. In particular, EDs can improve service efficiency by managing the level of complexity within a desirable interval. Furthermore, complexity exposes how the interplay between demand-side behavioral changes and supply-side responses affects operational performance. Moreover, the results suggest that arrival patterns—the number of patients of each class arriving per time and times between events (arrivals and service completions)—increase the risk of service delays more than the demand volume.

This paper is the first to provide an extensive investigation into the application of the complexity-based measure for ED crowding. The study demonstrates potential values to be gained in ED service systems if complexity measure is incorporated into their operations management decisions.

This chapter addresses the question of what normatively binding claims can be associated with the principle of sustainability. It proposes a theoretical reading of justice that requires a new level of morality, namely a global (spatial), intergenerational (temporal) and ecological (material) extension of the scope of responsibility. This makes it plausible that responsibility for those who are distant in space and time, as well as for nature, becomes a matter of conscience. At the same time, it is shown how the binding claims resulting from the principle of sustainability can be internalised in the course of a conscience formation and how the gap between knowledge and action in questions of sustainable development can be closed by means of an emotional underpinning. Finally, it is proposed to transfer the question of conscience to spatial units and tourism through the model of ‘Destination Conscience’ and to institutionalise the idea of ‘inner commitment’ or self-commitment. One suggestion is the creation of committees that could be a collective ethical conscience for the future issues.

Research indicates a long historical connection between racism and nationalist ideologies. This connection has been highlighted in the resurgence of exclusionary nationalism in recent years, across many multicultural societies. This chapter discusses the notions of race, ethnicity and nation, and critically examines how racism shapes contemporary manifestations of nationalist discourse across the world. It explores the historical role of settler-colonialism, imperial expansions and the capitalist development in shaping the racial/ethnic aspect of nationalist development. Moreover, it provides an analysis of the interconnections between the racialisation of minorities, exclusionary ideologies and the consolidation of ethno-nationalist tropes. This chapter further considers the impact of demographic changes in reinforcing anti-migrant exclusionary sentiments. This is examined in connection with emerging nativist discourse, exploring how xenophobic racism has shaped and is shaped by nostalgic nationalism based on the sanitisation of the legacies of Empire and colonialism.

In this paper, the authors examine auditor upward feedback, which provides a unique opportunity for staff auditors to exercise their voice within an audit firm. Upward feedback can improve employee perceptions of fairness and justice while mitigating feelings of burnout and turnover intentions, thus enhancing audit quality. However, it is unclear which circumstances improve the likelihood that auditors will use their voice and give feedback to superiors. The purpose of this study is to investigate contextual factors that impact the likelihood that auditors will provide upward feedback.

Using a 2 × 2 + 2 experiment with staff auditors, the authors test the likelihood of giving feedback when presented with different feedback systems (electronic anonymous, face-to-face or no opportunity) and experiences with managers (favorable or unfavorable).

The authors find that, while feedback type alone does not change the likelihood of auditors providing upward feedback, auditors are more likely to provide feedback after a favorable manager experience than an unfavorable one. The likelihood of providing feedback after an unfavorable experience is higher, however, when the feedback type is electronic and anonymous as opposed to face-to-face. Additional analyses illustrate strong relationships between manager experience, feedback type and procedural justice, which significantly influence the turnover intentions of staff auditors.

To the best of the authors’ knowledge, the authors are the first to examine the value of subordinates’ upward feedback on firm outcomes, including burnout and turnover intention.