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Construction organizations must maintain a productive workforce without sacrificing their health and safety. The global construction sector loses billions of dollars yearly to poor health and safety practices. This study aims to investigate benefits derivable from using wearable technologies to improve construction health and safety. The study also reports the challenges associated with adopting wearable technologies.

The study adopted a quantitative design, administering close-ended questions to professionals in the Nigerian construction industry. The research data were analysed using descriptive and inferential statistics.

The study found that the critical areas construction organizations can benefit from using WSDs include slips and trips, sensing environmental concerns, collision avoidance, falling from a high level and electrocution. However, key barriers preventing the organizations from adopting wearable technologies are related to cost, technology and human factors.

The time and cost lost to H&S incidents in the Nigerian construction sector can be reduced by implementing the report of this study.

Studies on WSDs have continued to increase in developed countries, but Nigeria is yet to experience a leap in the research area. This study provides insights into the Nigerian reality to provide directions for practice and theory.

Based on Kansei Engineering, this study obtained consumers' emotional preferences aiming to enhance the emotional connection between consumers and clothing to extend the service life of clothing and realize sustainable clothing design.

Six Kansei word pairs that are the most important to consumers were identified through literature reviews, magazines, websites, card sorting of consumers and cluster analysis. Finally, the consumers scored the 32 product specimens through a 5-level rating semantic differential scale questionnaire of six Kansei word pairs. The researchers verified the consumers' emotional preferences through principal component analysis and established the relationship between Kansei words and design elements of color through partial least squares.

The study found consumers' emotional preferences: elegant, minimalist, formal, casual, mature, practical and distinctive style. Besides white, black, gray, blue, consumers will also like red and yellow-red in the future. The crucial findings of this study are to get recommended guidelines that consumers' emotional preferences match the corresponding design elements.

The study's findings can be used to style the design of men's plain-color shirts and guide online marketers and designers to design apparel that meets consumers' emotional needs to develop consumers' sustainability reliance on clothing. This study also explains the overall process and methodology for integrating consumer preferences and product design elements.

This study aims to explore organizational factors that impact women’s career advancement. Knowledge of organizational practices that promote or obstruct women’s career progress is vital for women, firms and governments.

A total of 237 women participated in the study from the service sector in Johannesburg (South Africa). Participants were selected using a convenient sampling approach. Researchers used a questionnaire, consisting of demographic and open-ended questions, to gather data. Comments were analyzed using a thematic content analysis approach.

Findings reveal that prioritizing women, offering skills development opportunities, providing growth opportunities, assisting women in managing their careers, offering mentorship and having work-family support initiatives are practices that promote women’s career advancement. Conversely, practices that foster stagnation of women’s careers, distrust in women’s leadership abilities, preference for external candidates, people–related malpractices, male domination/preference, lack of role models and work-family balance support, hamper women’s career advancement.

The findings of this study will contribute to women’s empowerment. Organizations should provide a conducive atmosphere by instituting practices that promote their female employees' career advancement. Firms also should intentionally take practical steps to address practices that impede women’s career progression. The results of this study will also help the government to design appropriate policies that will promote the career progression of women employees.

This study presents findings from an analysis of qualitative data collected from 237 women to provide insight into the experiences of women working within the service industry in Johannesburg, South Africa.

Machine learning (ML), and deep learning in particular, is gaining traction across a myriad of real-life applications. Portfolio management is no exception. This paper provides a systematic literature review of deep learning applications for portfolio management. The findings are likely to be valuable for industry practitioners and researchers alike, experimenting with novel portfolio management approaches and furthering investment management practice.

This review follows the guidance and methodology of Linnenluecke et al. (2020), Massaro et al. (2016) and Fisch and Block (2018) to first identify relevant literature based on an appropriately developed search phrase, filter the resultant set of publications and present descriptive and analytical findings of the research itself and its metadata.

The authors find a strong dominance of reinforcement learning algorithms applied to the field, given their through-time portfolio management capabilities. Other well-known deep learning models, such as convolutional neural network (CNN) and recurrent neural network (RNN) and its derivatives, have shown to be well-suited for time-series forecasting. Most recently, the number of papers published in the field has been increasing, potentially driven by computational advances, hardware accessibility and data availability. The review shows several promising applications and identifies future research opportunities, including better balance on the risk-reward spectrum, novel ways to reduce data dimensionality and pre-process the inputs, stronger focus on direct weights generation, novel deep learning architectures and consistent data choices.

Several systematic reviews have been conducted with a broader focus of ML applications in finance. However, to the best of the authors’ knowledge, this is the first review to focus on deep learning architectures and their applications in the investment portfolio management problem. The review also presents a novel universal taxonomy of models used.

When the factors affecting health expenditures are examined in the literature, it is seen that one of the most important factors is income. In this context, the purpose of this study is to investigate the relationship between out-of-pocket health expenditures and disposable personal income and revealing the income elasticity of health expenditures.

Therefore, short/long-term coefficients were obtained by analyzing Westerlund (2007) co-integration analysis and pooled mean group (PMG) regression methods for 22 European Union (EU) member states during the period 2003–2017. In addition, a comparison of the long-term coefficients for each country was obtained with augmented mean group (AMG) estimator.

The results of the AMG and PMG tests show that the long-term coefficients between disposable personal income and health expenditures are 0.83 and 0.97, respectively. These results imply that there is a significant relationship between the variables, and that health care should be categorized in the group of normal goods. However, the fact that the long-term coefficient is very close to 1, despite being classified in the category of necessity goods, requires more care to be taken in evaluating whether health services are luxury goods or necessity goods.

The use of second generation econometric tests on both cross-sectional dependence and heterogeneity demonstrates the value of the study. On the other hand, obtaining similar results by investigating the relationship between variables using different appropriate econometric models reveals the importance of the methodology used in this study. It reveals important details in terms of the literature regarding the long-term and short-term results obtained in this study.

The purpose of this study is to explore and present a clear overview of innovation topics during the first year of the COVID-19 pandemic, and then organise these topics into various analyses.

The authors use multiple language analysis methods, such as text mining and latent Dirichlet allocation topic modelling, to address the research questions. A total of 440 news articles are analysed using Python and Google Colaboratory tools.

The analysis identified 20 innovation topics, highlighted sector-specific analyses and proposed phases of innovation. The authors suggest that each sector develops unique patterns and forms of innovation for long-term benefits and further research. This study expands upon existing literature on innovation and crisis at a theoretical level by incorporating an actor as the agency.

Based on the findings, the authors conclude that the COVID-19 pandemic has prompted businesses to adopt dynamic capabilities. Furthermore, the authors provide several strategic recommendations for addressing the pandemic in the developing context. The study discusses the roles of policymakers, business practitioners and academia in this context as well.

Very few studies specifically explore and identify forced innovation topics in emerging countries during the pandemic. There has been no review of forced innovations implemented in Indonesia using news media as a source. Additionally, this study presents the trajectory of innovation during the time of crises.

This paper aims to design an active shock absorber scheme for use in conjunction with a passive shock absorber to suppress the horizontal vibration of elevator cars in a smaller range and shorter time. The developed active shock absorber will also improve the safety and comfort of passengers driving in ultra-high-speed elevators.

A six-degree of freedom dynamic model is established according to the position and condition of the car. Then the active shock absorber and disturbance compensation-based adaptive control scheme are designed and simulated in MATLAB/Simulink. The results are analysed and compared with the traditional shock absorber.

The results show that, compared with traditional spring-based passive damping systems, the designed active shock absorber can reduce vibration displacement by 60%, peak acceleration by 50% and oscillation time by 2/3 and is more robust to different spring stiffness, damping coefficient and load.

The developed active shock absorber and its control algorithm can significantly reduce vibration amplitude and converged time. It can also adjust the damping strength according to the actual load of the elevator car, which is more suitable for high-speed elevators.

Current and predicted continued dramatic increases in international migration and ethnocultural diversity of older adult cohorts pose challenges for health care services. Review studies on ethnoculturally diverse older adults and health care show a lack of focus on their service use experiences. This study aims to report a meta-ethnography that addresses this knowledge gap through answering the review question: How do ethnoculturally diverse older adults who are immigrants experience health careservices?

The authors applied a seven-phase method of meta-ethnography to guide the review. The authors conducted two literature searches (April 2018 and June 2020) in MEDLINE, CINAHL, Embase, Sociological Abstracts and Abstracts in Social Gerontology that yielded 17 papers eligible for review.

“There’s always something positive and something negative” is the overarching metaphor for answering the review question. Findings highlight positive and negative tensions within ethnoculturally diverse older adults’ health care use experiences of understanding and being understood, having trust in providers and the health care system, having needs, preferences and resources met and desire for self-care over dependency. The majority of experiences were negative. Tipping points towards negative experiences included language, fear, provider attitudes and behaviours, service flexibility, attitudes towards Western and traditional health care and having knowledge and resources.

The authors propose concrete actions to mitigate the tipping points. The authors discuss policy recommendations for health care system changes at the micro, meso and macro service levels to promote positive experiences and address mainstream service policy inequities.

Although Agtech firms have promoted digital platforms for retailing farm supplies (RFS), farmers are sceptical while purchasing them online. As a result, they struggle to generate a sustained demand. Among other approaches, these platforms onboard complementors to become full-stack farming solution providers. Whether platform complementarity can induce farmers' trust remains ambiguous. Literature on network externality theory highlights that complementarity positively affects the perceived value for buyers. The sociotechnical systems literature indicates that perceived value is an antecedent of user trust. In this vein, the authors ask: Does perceived complementarity affect farmers' trust in the RFS platform? Alternatively, the Agtech firms augment the platform's look and feel to make the digital retail setting appear “normal” to farmers. The extant research on the social cognitive theory indicates that a retail setting conforming with the generalised expectancy of buyers harbours their trust. Against this backdrop, the authors ask whether situational normality affects farmers' trust in the RFS platform.

The study is based on a questionnaire survey of 212 Indian farmers using RFS platforms. The data were analysed using structural equation modelling (SEM) analysis.

This study establishes that platforms' complementarity and situational normality ameliorate farmer trust. The authors also identify the socioeconomic factors shaping the farmers' trust in platforms.

The present study has taken all RFS together as a single umbrella category, which can be considered a limitation. Also, the study is based on the cross-sectional survey of RFS platform users; the farmers' attitudes are dynamic in nature and evolve over time; however, the temporal factors shaping the farmer attitudes have not been considered in this study.

The study establishes the epistemological relationship between complementarity, situational normality and farmers' trust in agricultural platforms.

The purpose of this paper is to investigate the impact of the COVID-19 pandemic on doctoral education. Pandemics throughout history have generated new educational theories and practices, accelerated some trends and signalled the abrupt end of others. The unpredictable effects of the COVID-19 pandemic have particularly impacted upon First Nations and transcultural communities and People of Colour throughout the globe. A second significant recent global trend that occurred at the height of the pandemic was the reignited #BlackLivesMatter (#BLM) protest campaign. This campaign drew attention to the vast inequities faced by black, transcultural (migrant, refugee, culturally diverse and international) and Indigenous peoples and triggered rapid action in higher education institutions against racism and unconscious bias.

This conceptual paper draws upon postcolonial/decolonial theory to demonstrate how the COVID pandemic and #BLM movement prompts us to revitalise doctoral education.

These two issues have created renewed urgency around the need to decolonise higher education and a desire to transform the “business-as-usual” geopolitical power dynamics that continue to privilege Northern knowledge over culturally diverse knowledge systems from First Nations and transcultural contexts. A key site where special opportunities exist to effect this transformation lies in doctoral education. Doctoral education is a significant location of new knowledge creation and the development of the world’s future researchers.

Applying post/decolonial theory enables one to rethink how doctoral education should be changed to work towards greater decolonisation.

This study applies Santos’ ideas about “the sociologies of emergence” in the global South to think about how doctoral education should be reconstructed as a liberated zone of decolonisation and epistemic justice.