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Road safety has become a worldwide public health concern. Although many factors contribute to collisions, pedestrian behaviors can strongly influence road safety outcomes. This paper presents results of a survey investigating the effects of age, gender, attitudes towards road safety, fatalistic beliefs and risk perceptions on self-reported pedestrian behaviors in a Chinese example. The study was carried out on 543 participants (229 men and 314 women) from 20 provinces across China. Pedestrian behaviors were assessed by four factors: errors, violations, aggressions, and lapses. Younger people reported performing riskier pedestrian behaviors compared to older people. Gender was not an influential factor. Of the factors explored, attitudes towards road safety explained the most amount of variance in self-reported behaviors. Significant additional variance in risky pedestrian behaviors was explained by the addition of fatalistic beliefs. The differences among the effects, and the implications for road safety intervention design, are discussed. In particular, traffic managers can provide road safety education and related training activities to influence pedestrian behaviors positively.

Currently, Storage-as-a-Service (StaaS) clouds offer multiple data storage and access pricing options which usually consist of hot and cold tiers. The cold tier storage option offers a lower storage price while the hot tier storage option offers a lower access price. Cloud users need to choose an optimal tier to store their data objects economically based on the frequency of accesses to their data objects. Besides, StaaS cloud users can transfer data objects between these two tiers to save cost according to the varying frequency of accesses to their data objects. Therefore, in order to make optimal transferring decisions, future access curves are needed to be predicted. However, for cloud users, it is difficult to precisely predict future access frequencies for their data objects. In this paper, we propose an online algorithm to guide StaaS cloud users in making decisions on whether and when to transfer their data objects between cold and hot tiers for achieving cost optimizations, while users do not need to have any prior knowledge of future access frequencies. We prove theoretically that the proposed online algorithm can achieve guaranteed competitive ratios for data objects stored in a two-tier StaaS cloud. Finally, through extensive experiments, we validate the effectiveness of our proposed online algorithm and show that it can save costs significantly compared with always keeping data objects in one tier or always transferring data objects from one tier to the other when their access frequencies begin to vary.INDEX TERMS Cost optimization, online algorithms, competitive analysis, StaaS cloud, tiered cloud storage.

Purpose The purpose of this paper is to investigate whether responsible purchasing (relational commitment and supplier evaluation) and responsible supply (supplier firm information sharing and supplier performance) affect the two factors of supply chain responsiveness including process efficiency and customer knowledge management capability, which, in turn, affect other three factors of supply chain responsiveness, such as dyadic quality performance, innovation capability and buyer‒supplier relationship improvement. Design/methodology/approach This study used questionnaire survey and statistical analytical methods. Employing path analysis, this study tested hypothesized relationships using data collected from manufacturers. Findings The findings of this study support the theorized links. Responsible purchasing and supply enhance supply chain responsiveness, which is reflected through process efficiency, customer knowledge management capability, dyadic quality performance, innovation capability and buyer‒supplier relationship improvement. Originality/value Grounded in the goal interdependence theory, this study investigates the effects of responsible purchasing and supply on supply chain responsiveness in the context of Chinese manufacturers. This study offers managerial implications and theoretical contribution.