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The research evaluated the feasibility of 3D dynamic fit utilizing female compression tops by comparatively analyzing the virtual and actual dynamic fit.

Six female participants were 3D body-scanned and photographed in compression tops in four types of athletic movements (pull-up, kettlebell swing, circle-crunch and sit-up). Fit measurements, waist cross-sectional areas, waist width, waist depth, numerical simulation of clothing pressure (kPa) and objective pressure measurements (kPa) were collected from 3D virtual animation, 3D fit scan data and actual photos with the four types of athletic motions. The data were comparatively investigated between virtual and actual dynamic fit.

The 3D-animated body was not reflected with human body deformation because only bone structure was changed while maintaining the constant forms of muscle and body surface in athletic movements. Due to this consistency of virtual dynamic fit, there were significant differences with the actual dynamic fit at the top length, shoulder width and waist cross-sectional areas. Also, the virtual dynamic pressure indicated significantly higher levels than the objective dynamic pressure while presenting no significant correlations at the front neckline, breast, lateral waist, upper back, back armhole and back waist.

This study is the first to verify multiple aspects of virtual dynamic fit using 3D digital technology. This study provided useful information about which aspects of the current virtual animation need to be improved to apply in the dynamic fit evaluation.

This study aims to examine the role of location autonomy (i.e. autonomy over where to work) in shaping employee mental distress during their working days.

A total of 316 employees from 6 organizations in the UK provided data for 4,082 half-day sessions, over 10 working days. Random intercept modeling is used to analyze half-day data nested within individuals.

Results show that location autonomy, beyond decision-making autonomy and work-method autonomy, is positively associated with the perception of task-environment (TE) fit which, in turn, contributes to lower mental distress during each half-day session. Results of supplementary analysis also show that location autonomy can contribute to higher absorption, task proficiency and job satisfaction via TE fit during each half-day session.

This study reveals the importance and uniqueness of location autonomy in shaping employees' outcomes, offering implications for how organizations can use this in the work–life flexibility policies to support employee mental health.

The agricultural supply chain is susceptible to disruptive geopolitical events. Therefore, agri-food firms must devise robust resilience strategies to hasten recovery and mitigate global food security effects. Hence, the central aim of this paper is to investigate how supply chains could leverage digital technologies to design resilience strategies to manage uncertainty stemming from the external environment disrupted by a geopolitical event. The context of the study is the African agri-food supply chain during the Russian invasion of Ukraine.

The authors employ strategic contingency and dynamic capabilities theory arguments to explore the scenario and conditions under which African agri-food firms could leverage digital technologies to formulate contingency strategies and devise mitigation countermeasures. Then, the authors used a multi-case-study analysis of 14 African firms of different sizes and tiers within three main agri-food sectors (i.e. livestock farming, food-crop and fisheries-aquaculture) to explore, interpret and present data and their findings.

Downstream firms (wholesalers and retailers) of the African agri-food supply chain are found to extensively use digital seizing and transforming capabilities to formulate worst-case assumptions amid geopolitical disruption, followed by proactive mitigation actions. These capabilities are mainly supported by advanced technologies such as blockchain and additive manufacturing. On the other hand, smaller upstream partners (SMEs, cooperatives and smallholders) are found to leverage less advanced technologies, such as mobile apps and cloud-based data analytics, to develop sensing capabilities necessary to formulate a “wait-and-see” strategy, allowing them to reduce perceptions of heightened supply chain uncertainty and take mainly reactive mitigation strategies. Finally, the authors integrate their findings into a conceptual framework that advances the research agenda on managing supply chain uncertainty in vulnerable areas.

This study is the first that sought to understand the contextual conditions (supply chain characteristics and firm characteristics) under which companies in the African agri-food supply chain could leverage digital technologies to manage uncertainty. The study advances contingency and dynamic capability theories by providing a new way of interacting in one specific context. In practice, this study assists managers in developing suitable strategies to manage uncertainty during geopolitical disruptions.

Drawing upon a systematic literature review in new technology, innovation transfer and diffusion theories, and from interviews with technology leaders in digital transformation programs in the US Oil & Gas (O&G) industry, the authors explore the relationships among O&G industry dynamics, organization's absorptive capacity and resource commitment for new digital technology adoption-implementation process.

The authors employed the empirical survey method to gather the data (a sample size of 172) in the US O&G industry and used structural equation modeling (SEM) to test the measurement model for validity and reliability and the conceptual model for hypothesized structural relationships.

The results provide support for the study’s causal model of adoption and implementation with positive and direct relationships between the initiation and trial stages, between the trial stages and the evaluation of effective outcomes and between the effective outcomes and the effective implementation stages of digital technologies. The results also reveal partial mediating relationships of industry dynamics, absorptive capacity and resource commitment between respective stages.

Based on the current study's findings, managers are recommended to pay attention to the evolving industry dynamics during the initiation stage of new digital technology adoption, to utilize the organization's knowledge-based absorptive capacity during digital technology trial and selection stages and to support the digital technology implementation project when the adoption decision of a particular digital technology has been made.

The empirical research contributes literature on digital technology adoption and implementation by identifying and demonstrating the importance of industry dynamics, absorptive capacity and resource commitment factors as mediating variables at various stages of the adoption-implementation process and empirically validating a process-based causal model of digital technology adoption and a successful implementation project that has been missing in the current body of literature on digital transformation.

Business models (BMs) are becoming increasingly crucial for value creation in the healthcare sector. The study explores the conceptualization and application of BM concepts within the healthcare sector and investigates their evolution in emerging economies (EEs) and developed economies (DEs). This study aims to uncover these two contexts' shared characteristics and unique variances through a comparative analysis.

The paper systematically investigates and consolidates the literature on healthcare by employing the antecedents, decisions and outcomes (ADO) framework and finally examines 71 shortlisted articles published between 2003 and 2022.

The recognition of the BM within healthcare is increasing, both in EEs and DEs. EEs prioritize value creation and capture through cost efficiency, while DEs focus on innovation. Key theories employed include a resource-based view, the network theory and the theory of innovation. Case studies are commonly used as a methodology. Further research is needed to explore the decisions and outcomes of BMs.

The study adopts stringent filtration and keyword criteria, potentially excluding relevant research. Future researchers are encouraged to broaden their selection criteria to encompass a more extensive range of relevant studies.

Beyond comparing and highlighting gaps in BMs between EEs and DEs, benchmarking DE's healthcare business models (HBMs) helps healthcare organizations in EEs align their practices, mitigate risks and establish efficient healthcare systems tailored to their specific contexts. The study adopts stringent filtration and keyword criteria, potentially excluding relevant research. Future researchers are encouraged to broaden their selection criteria to encompass a more extensive range of relevant studies.

The study analyzes HBMs using an SLR framework perspective and provides practical implications for academicians and practitioners to enhance their decision-making.

This paper aims to analyze the volatility transmission between an energy stock index and a financial stock index in emerging markets during recent high instability periods. The study considers the impact of both the period under analysis and the data frequency on the direction and intensity of the contagion, as well as the effect of the potential spillovers on the risk measures. These questions still lack definitive answers and have become more relevant in a context of financially unsettling events such as COVID-19 crises.

This study employs an extension of the dynamic conditional correlation (DCC) model that allows for the time-varying dependence relationship between the variables. This dependence is analyzed at daily, weekly and monthly basis using data from the Bloomberg platform on energy and stock market indices for emerging markets between 2001 and 2021.

The results for a sample spanning from 2001 to mid-2021 show bidirectional volatility transmission on a daily basis, whereas only evidence of volatility transmission from the financial to the energy exists for weekly and monthly frequencies. However, considering different subsamples of daily data, the authors only find volatility transmission from financial (energy) index to the energy (financial) during the Great Recession (COVID-19) as a consequence of the different source of the shock and transmission channels.

This study reveals that volatility transmission between energy and stocks in emerging markets has changed and presents a unidirectional pattern from energy to financial markets during the COVID-19 period in contrast to calm and the sub-prime crisis intervals. These results differ from previous studies, focused on global markets, that show bidirectional spillovers during this period.

This study aims to examine the effects of the characteristics of apparel professionals on their attitude toward sustainability-related technology in the context of a developing country, Bangladesh.

A quantitative approach was used to investigate the apparel professionals’ perception of sustainability-related technology. A survey was conducted, and 204 valid responses were used in data analysis. The structural equation modeling technique was used to analyze the data.

The findings demonstrate that apparel professionals’ personal innovativeness positively impacts their knowledge of apparel technology. Knowledge of apparel technology and environmental issues in apparel manufacturing both significantly and positively impact their level of awareness of sustainability-related technology in apparel manufacturing. The findings also suggest that managers’ level of awareness of sustainability-related technology has a significant positive impact on their attitude toward sustainability-related technology.

Fishbein’s attitude theory was applied to examine how the various characteristics of apparel professionals (i.e. personal innovativeness in technology, knowledge of apparel technology, knowledge of environmental issues of apparel manufacturing) affect their awareness of and attitude toward sustainability-related technology. This study expands our understanding of the causal flow among cognitive variables of apparel professionals, including their innovativeness, knowledge, awareness and attitudes. The findings of the study can be helpful to the apparel industry to improve apparel professionals’ adoption of sustainable technology.

The purpose of this study is to explore the role of direct public engagement in shaping the sustainability image of nuclear energy in the UAE and the Arabian Gulf region. The study aims to measure the conflicting viewpoints of stakeholders, particularly the local community, regarding nuclear energy's dependability, cost-effectiveness, safety and environmental friendliness. The study also seeks to assess the effectiveness of direct stakeholder engagement strategies in enhancing public confidence in nuclear energy as a safe and sustainable source of electricity.

This study uses a quantitative-methods research design and used a sample of 318 participants. The SPSS AMOS application was used to conduct a structural equation model analysis. The purpose of this analysis is to examine the relationships among variables that constitute the key constructs of the study. In addition, confirmatory factor analysis was used to assess the reliability of the testing approach. Various fit indices and measurements, such as chi-square ratio, degrees of freedom, GFI, CFI and RMSEA, were used to evaluate the adequacy of the model.

The study finds that the construct “Direct Stakeholder Engagement (DSE)” has a positive effect on the dependent variables “Trust in Nuclear Sustainability (TNS)” and “Perception of Nuclear Energy as Safe (PNE)” with a probability value of (0.003, p < 0.05). Therefore, the hypothesis of the study is deemed acceptable. Hence, it can be concluded that each of the foregoing variables (DSE1, 2, 3, 4 and 5) and (TNS1, 2, 3, 4 and 5) with (PNE1, 2 and 3) have been observed and analysed in this study, and based on this analysis, it is plausible that the public's trust in nuclear sustainability and their acceptance of nuclear energy as a safe source of their nation's electricity can be positively affected by direct stakeholder engagement.

The study's findings have implications for policymakers and managers of nuclear power plants in the UAE and the Arabian Gulf region. The study provides insights into effective stakeholder engagement strategies that can enhance public participation and confidence in nuclear energy. The study's recommendations highlight the importance of incorporating public opinion in policymaking and management practices to address conflicting viewpoints and enhance public trust in nuclear sustainability. The study's findings also contribute to the ongoing discourse on nuclear sustainability and provide insights into the role of direct public engagement in shaping public perception of nuclear energy.

This study's originality lies in its focus on the UAE and the Arabian Gulf region, where nuclear energy is a critical source of electricity. The study contributes to the limited research on stakeholder engagement and public perception of nuclear energy in the region. The study's novel framework of stakeholder engagement, tailored to cultural dimensions, provides insights into effective engagement strategies that can enhance public participation and confidence in nuclear energy. The study's quantitative-methods research design also provides a comprehensive understanding of the conflicting viewpoints of stakeholders, enhancing the understanding of the role of direct public engagement in shaping public perception of nuclear energy.

This study aims to examine the price and income elasticities of short- and long-run industrial electricity demand in Brazil between 2003 and 2020. The research also examines the impacts of COVID-19 in Brazil’s industrial electricity sector, including an analysis in states more and less industrialized.

Dynamic adjustments models in panel data are used to present robust estimates and analyze the impact of different methodologies on reported elasticities.

The short-run price elasticity is estimated at −0.448, while the long-run values are around −1.60. Regarding income elasticity, the value is 0.069 in the short-run and is concentrated in 0.25 in the long-run. The inelastic results of income show that the industrial demand for electric energy follows the trend of loss of competitiveness of the Brazilian industry in the past years. In addition, the price of natural gas, the level of employment, and, in specific cases, the level of imports also influence industrial electricity demand.

The research is a pioneer in the investigation of the industrial behavior of electricity of the Brazilian industrial branch, using as control variables, the average temperature, and the level of rainfall, this one, so important for a country whose main source is hydroelectric. In addition, to the best of the authors’ knowledge, it is the first study, which is prepared to analyze the effects of COVID-19 on electric consumption in the industrial sector, investigating these impacts, including in the states considered more and less industrialized. The estimates generated may help in the design of the Brazilian energy policy.

Existing research on innovation has mainly focused on how to promote technological innovation in megaprojects and management innovation (MI) in megaprojects is still an unknown research field. The purposes of this study are to examine the effect of MI on megaproject performance and how the top management team (TMT) regulatory focus affects the use of MI in projects. At the same time, the moderating effects of project uncertainties are also tested.

On the basis of an explorative/exploitative ambidextrous analysis framework, this study divides MI into two dimensions: explorative and exploitative MI, and integrates the theoretical perspectives of the TMT regulatory focus and project uncertainties into a research model. Taking 314 responses from megaprojects’ TMTs in China as research data, this study empirically tests the above model.

Results show that exploratory MI has a U-shaped relationship with megaproject performance; whereas exploitative MI has an inverted U-shaped relationship with megaproject performance. The TMT promotion focus has a positive effect on exploratory and exploitative MI; and the TMT prevention focus has a negative effect on exploratory MI but has a positive effect on exploitative MI. Project uncertainties have a positive moderating effect on the positive relationship between TMT promotion focus and exploratory MI, whereas it has a negative moderating effect on the negative relationship between the TMT prevention focus and exploratory MI.

By empirically measuring the relationship between two types of MIs and megaproject performance, this study clarifies the differential mechanism of the effect of different MIs on megaproject performance. This study also examines the MI of megaprojects from the perspective of the TMT regulatory focus and expounds how changes in uncertainties affect the relationship between the TMT regulatory focus and MI.