The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. service quality and purchasing experience in e-service quality as dominant customer satisfaction factors. Furthermore, this study suggests that Chinese e-retailers to be competitive have to focus more on logistics and delivery of products compared to other intangible service quality factors. The outcome of the study would be highly beneficial to the Chinese electronic retailers to fine tune their strategy to satisfy the growing demand. This study would also guide third party logistics to be more competitive in future. Furthermore, this study can supplement government policy makers to regulate the growing volatile market.

In this study we focus on how e-retailers who deal with innovative products in the era of the Internet of Things (IoT) select product delivery service providers to ensure timely and efficient delivery to customers. Based on the Asset-Process-Performance framework, we propose a triadic model that includes e-retailers, delivery service providers and customers to achieve synergy and customer satisfaction in the era of the IoT. We find that substantive selective criteria should include consideration of service provider's hard and soft infrastructure. In addition, flexibility is a key criterion that will strengthen the relationship between e-retailers and delivery service providers to improve the competitiveness of e-retailers as well as to satisfy the customers. We validate the model using data from 148 Taobao e-retailers. Our results indicate that both hard and soft infrastructures have positive influence on flexibility which in turn has a positive impact on customer satisfaction. Indeed, flexibility fully mediates the relationship between hard and soft infrastructures and customer satisfaction. Our theoretical triadic model is one of the first attempts in providing product delivery service provider selection criteria for e-retailers selling innovative products and its influence on customer satisfaction. Our findings provide guidelines for both e-retailers and product delivery service providers to improve their competitiveness.

Purpose -This paper provides quantitative evidence of natural disasters' effect on corporate performance and studies the mechanisms through which the supply chain moderates and mediates the link. Design/methodology/approach -Using two major natural disasters as quasiexperiment, namely the 2011 Japanese earthquake-tsunami (JET) and Thai flood (TF), and data over the period 2010Q1-2013Q4, effect of these events on end assemblers' performance is studied, with a focus on the personal computer (PC) supply chain. The moderating influence of delivery and sourcing -as supply chain flexibility and agility -are examined through end assemblers' and suppliers' inventory. The suppliers' mediating role is captured as disruption in obtaining PC components through their sales. Findings -Only JET had any negative effect, further quantified as short-term and long-term. The TF instead portrays an insignificant but positive aftermath, which is construed as showing learning from experience and adaptability following JET. Inventory matters, but differently for the two events, and suppliers only exhibit a moderating influence on the assemblers' disaster-performance link. Originality/value -Natural disasters, as catastrophic vulnerabilities, are distinct from other vulnerabilities in that they are hard to predict and have significant impact. Since little is known about the impact of natural disasters on firm performance and how supply chain mechanisms moderate or mediate their impact, they should be distinctly modelled and empirically studied from other vulnerabilities. This paper sheds light on supply chain resilience to such events with the role of dynamic capabilities.

In this chapter, we will introduce practical issues and implementation challenges from the industry perspective. In particular, we explain three aspects based on the panel discussions from the set of representatives participated in a big data conference from three dominant industries such as e-commerce, health care and computer hardware, which are sought of big data for their growth and development. We introduce overall challenges and explain typical industry based practical issues, how they visualize the big picture for their strategic development and how industries are gearing towards converting the challenges to big opportunities through the partnership of universities. Finally, based on the content analysis we offer potential trends and future research directions.

This chapter discusses the scholarly views on big data analytics with respect to the challenges in terms of visualization and data driven research in smart cities and ports. The prominent challenges and emerging research on structuring data, data mining algorithms and visualization aspects are shared by academic experts based on their ongoing research experience. Scholars agreed that being able to analyze huge data at once is highly critical for the embracement and success of big data research and the utilization of its findings particularly for entities with highly dynamic and complex demands such as cities and ports. It was noted that developing robust ways of handling and clean qualitative social media data as well as getting well-trained and highly skilled human resources in all aspects of big data analysis and interpretation remains a major challenge.