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In-feed native ads have become a major social media advertising format. The purpose of this paper is to investigate strategies for leveraging native advertising in terms of content creation and platform selection on social media, proposing that variations in content and platform reduce the intrusiveness of native ads, thereby resulting in enhanced brand attitude and purchase intent.

Two experiments were conducted with online samples, employing a 2 (content strategy: repeated ads vs varied ads) × 2 (platform strategy: single platform vs multiple platforms) between-subject factorial design. ANCOVA and structural equation modeling were used to test the hypotheses.

When repeated ads were used, the use of multiple platforms reduced ad intrusiveness, resulting in more favorable brand attitude and greater purchase intent as opposed to the use of a single platform. In contrast, when varied ads were used, there were no significant differences in the outcome variables between a single platform and multiple platforms. The results were largely consistent across the two experiments.

This study contributes to theory advancement by unpacking the underlying mechanisms of processing native advertising and shedding light on which content and platform strategies are the most effective on social media.

As an extension to Assael’s (2011) review on media synergy, this chapter examines the latest evolvement of media synergy research in the past 10 years by integrating studies from a wide range of leading journals.

We searched a total of 17 major journals in advertising, communication, and marketing from 2005 to 2014 and identified a total of 42 articles on media synergy. These studies were reviewed to assess the current status of media synergy research.

Studies of inter-media interaction at the individual level provide mixed support for a media synergistic effect, and the occurrence of this effect demands certain boundary conditions. Research on multi-media engagement has been gaining momentum in the past few years and is a promising subject in media synergy research.

We envision two growing approaches in future media synergy research: the neuroscientific approach and the data mining approach.

This chapter posits that media synergy research has evolved in the most recent years to a new phase, which is multi-media engagement. Hence, this chapter extends Assael’s work in terms of explicating media synergy in the context of social media engagement and identifying research gaps in current literature.

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

This paper explores whether fintech paves the way for the transition to carbon neutrality in the context of China’s climate policy uncertainty (CCPU) and the influence of the ocean carbon sink market.

We apply a novel wavelet analysis technique to investigate the time-frequency dependence between the CCPU index, the CSI (China Securities Index) Fintech Theme Index (CFTI) and the Carbon Neutral Concept Index (CNCI).

The empirical results show that CCPU and CFTI have a detrimental effect on CNCI in high-frequency bands. Furthermore, in low-frequency domains, the development of CFTI can effectively promote the realization of carbon neutrality.

Our findings show that information from the CCPU and CFTI can be utilized to forecast the movement of CNCI. Therefore, the government should strike a balance between fintech development and environmental regulation and, hence, promote the use of renewable energy to reduce carbon emissions, facilitating the orderly and regular development of the ocean carbon sink market.

The development of high-quality fintech and positive climate policy reforms are crucial for achieving carbon neutrality targets and promoting the growth of the marine carbon sink market.