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Aging has increased the burden of social medical care. Mobile health (mHealth) services provide an effective way to alleviate this pressure. However, the actual usage of mHealth services for elderly users is still very low. The extant studies mainly focused on elderly users’ mHealth adoption behavior, but resistance behavior has not been sufficiently explored by previous research. A present study tried to remedy this research gap by examining the effect of overload factors on the mHealth application resistance behavior based on the stimulus-organism-response (SOR) framework. The results indicated that information overload and system feature overload of an mHealth application increased the fatigue and technostress of the elderly user, which further increased their resistance behavior. Meanwhile, we integrated the intergeneration support with the SOR model to identify the buffer factor of the elderly user’s resistance behavior. The results showed that intergenerational support not only directly decrease the elderly user’s mHealth application resistance behavior, but also moderates (weaken) the effects of fatigue and technostress on resistance behavior. The present study also provided several valuable theoretical and practical implications.
Yuanyuan Cao; Junjun Li; Xinghong Qin; Baoliang Hu. Examining the Effect of Overload on the MHealth Application Resistance Behavior of Elderly Users: An SOR Perspective. International Journal of Environmental Research and Public Health 2020, 17, 6658 .
AMA StyleYuanyuan Cao, Junjun Li, Xinghong Qin, Baoliang Hu. Examining the Effect of Overload on the MHealth Application Resistance Behavior of Elderly Users: An SOR Perspective. International Journal of Environmental Research and Public Health. 2020; 17 (18):6658.
Chicago/Turabian StyleYuanyuan Cao; Junjun Li; Xinghong Qin; Baoliang Hu. 2020. "Examining the Effect of Overload on the MHealth Application Resistance Behavior of Elderly Users: An SOR Perspective." International Journal of Environmental Research and Public Health 17, no. 18: 6658.
The environmental input of a store brand product’s green supply chain plays an important role in improving the product brand image and expanding the product demand. According to the difference of the initial one-off environmental investment of the store brand product, it can be divided into three modes: direct OEM, retailer’s full participation and retailer’s partial participation. The research methods employed in this study include model establishment, numerical analysis and comparison under three entrustment modes based on retailers’ negotiation strength. In addition, sensitivity analysis was used to test the influence of parameter variations on the results. The research results show that: (i) the direct OEM mode is the best choice for retailers when the retailer is in a weak position, but it is not the best choice for the manufacturer. With the increase of the retailers’ negotiation strength, the profits of both sides will decline, causing the problem of double marginal profit decreasing; (ii) the retailer’s full participation mode is the best choice for the manufacturer when the retailer is in a strong position, but not the best choice for the retailer. It is not the best choice for both sides when the retailer is in a weak position; (iii) the greenness and total profit of the supply chain are no relative with the negotiation strength of the retailer under the partial participation mode, and the greenness and total profit of the supply chain are the same as the condition under the integrated control to achieve the best coordination effect.
Shaobo Wu; Shiping Wen; Quan Zhou; Xinghong Qin. Coordination of Store Brand Product’s Green Supply Chain Based on Negotiation. Sustainability 2020, 12, 3637 .
AMA StyleShaobo Wu, Shiping Wen, Quan Zhou, Xinghong Qin. Coordination of Store Brand Product’s Green Supply Chain Based on Negotiation. Sustainability. 2020; 12 (9):3637.
Chicago/Turabian StyleShaobo Wu; Shiping Wen; Quan Zhou; Xinghong Qin. 2020. "Coordination of Store Brand Product’s Green Supply Chain Based on Negotiation." Sustainability 12, no. 9: 3637.
Disasters such as hurricanes, earthquakes and floods continue to have devastating socioeconomic impacts and endanger millions of lives. Shelters are safe zones that protect victims from possible damage, and evacuation routes are the paths from disaster zones toward shelter areas. To enable the timely evacuation of disaster zones, decisions regarding shelter location and routing assignment (i.e., traffic assignment) should be considered simultaneously. In this work, we propose a risk-averse stochastic programming model with a chance constraint that takes into account the uncertainty in the demand of disaster sites while minimizing the total evacuation time. The total evacuation time reflects the efficacy of emergency management from a system optimal (SO) perspective. A conditional value-at-risk (CVaR) is incorporated into the objective function to account for risk measures in the presence of uncertain post-disaster demand. We resolve the non-linear travel time function of traffic flow by employing a second-order cone programming (SOCP) approach and linearizing the non-linear chance constraints into a new mixed-integer linear programming (MILP) reformulation so that the problem can be directly solved by state-of-the-art optimization solvers. We illustrate the application of our model using two case studies. The first case study is used to demonstrate the difference between a risk-neutral model and our proposed model. An extensive computational study provides practical insight into the proposed modeling approach using another case study concerning the Black Saturday bushfire in Australia.
Bian Liang; Dapeng Yang; Xinghong Qin; Teresa Tinta. A Risk-Averse Shelter Location and Evacuation Routing Assignment Problem in an Uncertain Environment. International Journal of Environmental Research and Public Health 2019, 16, 4007 .
AMA StyleBian Liang, Dapeng Yang, Xinghong Qin, Teresa Tinta. A Risk-Averse Shelter Location and Evacuation Routing Assignment Problem in an Uncertain Environment. International Journal of Environmental Research and Public Health. 2019; 16 (20):4007.
Chicago/Turabian StyleBian Liang; Dapeng Yang; Xinghong Qin; Teresa Tinta. 2019. "A Risk-Averse Shelter Location and Evacuation Routing Assignment Problem in an Uncertain Environment." International Journal of Environmental Research and Public Health 16, no. 20: 4007.