Search results

Wearable health devices (WHDs) have demonstrated significant potential in assisting elderly adults with proactive health management by utilizing sensors to record and monitor various aspects of their health, including physical activity, heart rate, etc. However, limited research has systematically explored older adults’ continued usage intention toward WHD. By utilizing the extended unified theory of acceptance and use of technology (UTAUT2), this paper aims to probe the precursors of elderly adults’ continuance intention to use WHD from an enabler–inhibitor perspective.

The research model was developed based on UTAUT2 and examined utilizing the partial least squares technique (PLS). The research data were collected through in-person meetings with older people (n = 272) in four cities in China.

Results reveal that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic values and perceived complexity are the positive predictors of elderly adults’ continuance intention to use WHDs. Technology-related anxiety and usage cost negatively influence the formation of older people’s continuance intention.

This work is an original empirical investigation that draws on several theories as guiding frameworks. It adds to the existing literature on the usage of wearable technologies and offers insights into how the elderly’s intentions to continue using WHDs can be developed. This study broadens the scope of the UTAUT2 application and presents an alternative theoretical framework that can be utilized in future research on the usage behavior of wearable devices by individuals.

Corporate social responsibility (CSR) promotes society, reduces risk, and encourages ethical business practices. Due to its relevance, we study how CSR influences firms' sustainable development. We analyze data from 427 New York Stock Exchange (NYSE)-listed firms from 2008 to 2022. The Refinitiv environmental and social score is used to measure CSR, whereas for firms' sustainable development we rely on corporate sustainable growth rate (SGR) and market-based metrics. The analysis employs various econometric techniques, including ordinary least square, fixed effect regression, two-stage least square, generalized method of moment, and simultaneous quantile regression. The results indicate that CSR has a positive and significant effect on firms' sustainable development across all models. This relationship supports the notion that socially responsible business can contribute to long-term financial sustainability in line with “stakeholder theory”, indicating that companies should accommodate the concerns of various stakeholders, including society and the environment, to achieve sustainable development. We evaluate how the conditional distributions of SGR and firms’ value are affected by CSR, categorizing them into high, moderate, and low regimes. The quantile regression estimates indicate that the effect of CSR is more pronounced at upper quantiles, followed by moderate and low regimes. These findings underscore the importance of considering CSR in assessing the SGR and enterprises market value. We also confirm that our results are robust under range of different econometrics' methods. Finally, we enlighten current literature, and our research has useful policy implications for management and investors.

Impulse purchases are a phenomenon of interest in recent years that provides a high revenue stream for companies compared to planned purchases. Airports are a unique shopping environment. Travellers usually need to arrive at the airport early and can only utilise limited time to shop at duty-free stores, which makes the shopping experience time-constrained and has the potential to make impulse purchases. The main purpose of this research is to create a model to examine whether “time pressure” and “hedonic shopping motivation” lead to impulse shopping through the formation of “positive emotion” in the context of airport duty-free shops.

A questionnaire-based survey was conducted in this study. The data collection for this study targeted individuals who had previously used airline services for international travel and visited duty-free shops at international airports. A total of 502 valid subjects participated in this survey.

The findings indicated that time pressure and consumers’ hedonic motivations have a positive impact on emotions. Positive emotions have a positive impact on the occurrence of impulse purchases. Music and light can moderate the impact of hedonic motivation on emotion but cannot reduce the influence of time pressure on emotion. Social factor significantly moderates the positive association between hedonic shopping motivation and emotion.

The research collected data from various international airports and social media, enabling the findings to be generalised.

With the development of inclusive financial business in China in recent years, this case describes the credit risk control of “mobile credit”, a smart online credit platform launched by Shanghai Mobanker Co. Ltd. (referred to as “Mobanker”, previously named as “Shanghai Mobanker Financial Information Service Co., Ltd.”) which provides technical services for inclusive finance industry.

To further promote application of BIM technology in construction of prefabricated buildings, influencing factors and evolution laws of willingness to apply BIM technology are explored from the perspective of willingness of participants.

In this paper, a tripartite game model involving the design firm, component manufacturer and construction firm is constructed and a system dynamics method is used to explore the influencing factors and game evolution path of three parties' application of BIM technology, from three perspectives, cost, benefit and risk.

The government should formulate measures for promoting the application of BIM according to different BIM application willingness of the parties. When pursuing deeper BIM application, the design firm should pay attention to reducing the speculative benefits of the component manufacturer and the construction firm. The design firm and the component manufacturer should pay attention to balancing the cost and benefit of the design firm while enhancing collaborative efforts. When the component manufacturer and the construction firm cooperate closely, it is necessary to pay attention to balanced distribution of interests of both parties and lower the risk of BIM application.

This study fills a research gap by comprehensively investigating the influencing factors and game evolution paths of willingness of the three parties to apply BIM technology to prefabricated buildings. The research helps to effectively improve the building quality and construction efficiency, and is expected to contribute to the sustainability of built environment in the context of circular economy in China.

The purpose of this study is to get benefits from manufacturing harmful wastes is by using them as a reinforcement with epoxy matrix composite materials to improve the damping characteristics in applications such as machine bases, rockets, satellites, missiles, navigation equipment and aircraft as large structures, and electronics as such small structures. Vibration causes damaging strains in these components.

By adding machining chips with weight percentages of 5, 10, 15 and 20 Wt.%, with three different chip lengths added for each percentage (0.6, 0.8 and 1.18 mm), the three-point bending and damping characteristics tests are utilized to examine how manufacturing waste impacts the mechanical properties. Following that, the optimal lengths and the chip-to-epoxy ratio are determined. The chip dispersion and homogeneity are assessed using a field emission scanning electron microscope.

Waste copper alloys can be used to enhance the vibration-dampening properties of epoxy resin. The interface and bonding between the resin and the chip are crucial for enhancing the damping capabilities of epoxy. Controlling the flexural modulus by altering the chip size and quantity can change the damping characteristics because the two variables are inversely related. The critical chip size is 0.8 mm, below which smaller chips cannot evenly transfer, and disperse the vibration force to the epoxy matrix and larger chips may shatter and fracture.

The main source of problems in machine tools, aircraft and vehicle manufacturing is vibrations generated in the structures. These components suffer harmful strains due to vibration. Damping can be added to these structures to get over these problems. The distribution of energy stored as a result of oscillatory mobility is known as damping. To optimize the serving lifetime of a dynamic suit, this is one of the most important design elements. The use of composites in construction is a modern method of improving a structure's damping capacity. Additionally, it has been demonstrated that composites offer better stiffness, strength, fatigue resistance and corrosion resistance. This research aims to reduce the vibration effect by using copper alloy wastes as dampers.

For ranking aggregation in crowdsourcing task, the key issue is how to select the optimal working group with a given number of workers to optimize the performance of their aggregation. Performance prediction for ranking aggregation can solve this issue effectively. However, the performance prediction effect for ranking aggregation varies greatly due to the different influencing factors selected. Although questions on why and how data fusion methods perform well have been thoroughly discussed in the past, there is a lack of insight about how to select influencing factors to predict the performance and how much can be improved of.

In this paper, performance prediction of multivariable linear regression based on the optimal influencing factors for ranking aggregation in crowdsourcing task is studied. An influencing factor optimization selection method based on stepwise regression (IFOS-SR) is proposed to screen the optimal influencing factors. A working group selection model based on the optimal influencing factors is built to select the optimal working group with a given number of workers.

The proposed approach can identify the optimal influencing factors of ranking aggregation, predict the aggregation performance more accurately than the state-of-the-art methods and select the optimal working group with a given number of workers.

To find out under which condition data fusion method may lead to performance improvement for ranking aggregation in crowdsourcing task, the optimal influencing factors are identified by the IFOS-SR method. This paper presents an analysis of the behavior of the linear combination method and the CombSUM method based on the optimal influencing factors, and optimizes the task assignment with a given number of workers by the optimal working group selection method.

Construction professionals (CPs) are often exposed to various challenges and pressures at work including urgent deadlines, high demands, uncertainty in tasks, and complex problems, which may induce stress and affect performance directly. Mindfulness-based stress reduction (MBSR) training has been used for several years to reduce stress among various types of people, such as nurses, teachers, and family caregivers, but its application to CPs with highly dynamic environment remains uncertain. This study aimed to investigate the impact of MBSR training on the performance of CPs via an intervention study involving two groups (MBSR and control).

Participants in both groups were assessed using a questionnaire survey and a semi-structured interview at the pre- and post-intervention stage. Multiple research methods were used to derive quantitative and qualitative analyses, including factor analysis, independent t-test, Pearson correlation, and contextual analysis.

The findings overall confirm that MBSR has a direct effect on CPs, improving their mindfulness characteristics and enhancing performance by reducing their stress.

A number of practical recommendations are made such as (1) arranging standard eight-week MBSR training for CPs; (2) giving special leave for attending the full mindfulness training; (3) establishing a suitable environment in the office for meditation;(4) allowing CPs an opportunity to pause at difficult moments to create space to respond instead of simply reacting; and (5) expressing love and kindness through gratitude, recognition, and regular feedback.

This research can be considered as valid evidence to convince construction organizations conducting MBSR to the CPs, which is indeed not too remote to enhance their performance as well as the holistic construction performance.

The purpose of this study is to explore the causal relationship between smart transportation technology innovation and green transportation efficiency.

A comprehensive framework is used in this paper to assess the level of green transportation efficiency in China based on the instrumental variable – generalized method of moments model, followed by an examination of the impact of innovation in smart transportation technology on green transportation efficiency. Additionally, their non-linear relationship is explored, as are their important moderating and mediating effects.

The findings indicate that, first, the efficiency of green transportation is significantly enhanced by innovation in smart transportation technology, which means that investing in such technologies contributes to improving green transportation efficiency. Second, in areas where green transportation efficiency is initially low, smart transportation technology innovation exerts a particularly potent influence in driving green transportation efficiency, which underscores the pivotal role of such innovation in bolstering efficiency when it is lacking. Third, the relationship between smart transportation technology innovation and green transportation efficiency is moderated by information and communication technology, and the influence of smart transportation technology innovation on green transportation efficiency is realized through an increase in energy efficiency and carbon emissions efficiency.

Advancing green transportation is essential in establishing a low-carbon trajectory within the transportation sector.

External stakeholder risks (ESRs) caused by unfavorable behaviors hinder the success of project portfolios (PPs). However, due to complex project dependency and numerous risk causality in PPs, assessing ESRs is difficult. This research aims to solve this problem by developing an ESR-PP two-layer fuzzy Bayesian network (FBN) model.

A two-layer FBN model for evaluating ESRs with risk causality and project dependency is proposed. The directed acyclic graph (DAG) of an ESR-PP network is first constructed, and the conditional probability tables (CPTs) of the two-layer network are further presented. Next, based on the fuzzy Bayesian network, key variables and the impact of ESRs are assessed and analyzed by using GeNIe2.3. Finally, a numerical example is used to demonstrate and verify the application of the proposed model.

The proposed model is a useable and effective approach for ESR assessment while considering risk causality and project dependency in PPs. The impact of ESRs on PP can be calculated to determine whether to control risk, and the most critical and heavily contributing risks and project(s) in the developed model are identified based on this.

This study extends prior research on PP risk in terms of stakeholders. ESRs that have received limited attention in the past are explored from an interaction perspective in the PP domain. A new two-layer FBN model considering risk causality and project dependency is proposed, which can synthesize different dependencies between projects.