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This study develops an empirical framework to address how large third-party sellers (TPSs) can apply customer acquisition strategies to improve their performance in consumers’ person-goods matching process and how the platform firm’s similar strategies moderate the effects of TPSs’ strategies.

Using data collected from the top ten TPSs from a Chinese e-commerce platform, the fixed effect model is used to validate the conceptual model and hypotheses.

The study results show that both market detection strategy and matching optimization strategy can help large TPSs improve their sales performance. Moreover, the similar market detection strategy applied by the platform firm weakens the effect of large TPSs’ customer acquisition strategies, while the similar matching optimization strategy applied by the platform firm strengthens the effect of large TPSs’ customer acquisition strategies.

This study provides firsthand evidence on the performance of large TPSs’ and the platform firm’s strategies. It demonstrates the effectiveness of large TPSs’ market detection strategy and matching optimization strategy, which can be adopted to meet consumers’ search and evaluation motivations in their person-goods matching process respectively. Moreover, it identifies the role of platform firms by showing the moderating effect of similar strategies adopted by the platform firm on the effect of large TPSs’ customer acquisition strategies.

This paper aims to explore the promotion decisions of heterogeneous sellers on a decentralized platform under competitive conditions and analyze how seller behaviors impact platform profit, seller revenue, buyer surplus and social welfare.

This paper considers a Cournot model consisting of a platform charging a commission rate and two sellers with different conversion rates and browsing costs. Promotion efforts by sellers can increase traffic, but they also incur promotion costs for sellers. The sellers decide on promotion effort by weighing these two effects. The authors also explore the equilibrium when the platform charges a fixed usage fee.

The seller’s profit improves as its conversion rate increases and worsens as browsing costs increase. Also, increasing the commission rate charged by the platform makes the seller invest less in promotional efforts. Therefore, the platform must consider this trade-off to determine an optimal rate. The analysis shows that the seller with a high conversion rate and high browsing cost plays a greater role in generating more overall revenue. When the market favors such a seller, the platform tends to charge less in order not to impair its profitability.

This paper incorporates conversion rate, buyer’s browsing cost, unit promotion cost and the fee charged by the platform into the model to study sellers’ promotion decisions on decentralized platforms.

The existence of the advertising delay effect and its impact on supply chain operations have been demonstrated in the current study. Therefore, this study develops a timely inventory control strategy for the fresh produce supply chain to address the advertising delay effect in the fresh produce supply chain.

This study proposes a game model based on the Nerlove-Arrow time delay differential equation and Pontryagin's maximum principle. Through comparative analyses of the optimal equilibrium strategies, the authors compare the optimal equilibrium strategies, product goodwill and optimal inventory trajectories for suppliers and retailers under secondary replenishment decisions and decentralized decisions.

The authors find that (1) Only when the sales cycle meets certain conditions can the overall profit of the supply chain under the secondary replenishment decision be greater than that under the decentralized decision. As the price markup coefficient increases, the total profit of the supply chain first increases and then decreases. (2) With the increase in the delay time, the replenishment quantity during the initial period gradually decreases. After the delay time elapses, the inventory depletion rate under secondary replenishment decisions is faster than that under decentralized decision-making. (3) Although there is a continuously increasing maximum value of product goodwill with the increase in delay time, it becomes difficult to achieve this value for longer delays.

The authors’ findings provide a theoretical basis for supply chain members of fresh agricultural products to select replenishment and inventory control strategies when adopting different levels of delay in advertising marketing.

Firstly, this paper explains the impact of advertising delay effect on fresh produce supply chain from a dynamic perspective, and secondly, it provides guidance on advertising formulation and inventory replenishment for fresh produce retailers under the influence of advertising delay effect.

This study aims to examine how the effect of pop-ups on an omnichannel brand’s subsequent online sales is moderated by the brand’s online price and premium promotions, paid search and popularity signaling.

Using a difference-in-differences approach, this study appraises variations in two similar Chinese apparel brands’ online sales before and after one of the brands’ implementations of its pop-ups and how the brand’s online promotions modify the pop-ups’ effect.

Unique, interactive pop-ups boost brands’ subsequent online sales. Online price promotions negatively moderate the effect; online premium promotions and paid search positively moderate it. Moreover, the product’s popularity diminishes the extent to which a pop-up stimulates online demand. These findings can be partially generalized to other categories, such as utilitarian products.

Only certain online strategies enhance the effect of pop-ups on brands’ online sales, so practitioners should strategically select appropriate promotion combinations when they operate pop-ups and allocate resources across channels. In addition, the moderating influence of online promotions on pop-ups depends on the type of product being promoted.

Pop-ups offer proven abilities to deliver sensory experiences to online shoppers, reinforce brand awareness and loyalty and boost online sales. This study extends prior research by examining how various online promotions moderate pop-ups’ effects.

Few studies illustrate how contextual effects (e.g. assimilation and contrast) in pay-per-click ad design may impact consumers' attitudes and purchase intention. To fill this research gap, the authors provide theoretical predictions and empirical evidence on how ad design may prompt an assimilation and/or a contrast effect that may influence consumers' attitudes toward the ad and the brand and purchase intention. They also investigate whether the impact of contextual effects on consumers' decisions depends on the level of vividness in the ad.

A 2 (vividness: dynamic motion vs. static page) × 2 (information design: assimilation vs. contrast) × 2 (aesthetic design: assimilation vs. contrast) between-subjects experimental design is used to examine the effects of vividness, information design and aesthetic design. Conditional process analysis is used to assess the mediating role of attitudes toward the ad and the brand in the relationship between contextual effects and purchase intention.

For dynamic ads (i.e. high vividness) but not for static ads (i.e. low vividness), combined information contrast and aesthetic contrast designs generate a more favorable attitude toward the brand and a higher purchase intention than do combined information assimilation and aesthetic assimilation designs. Notably, combined information contrast and aesthetic contrast designs have the strongest effects than any other combination of assimilation and contrast designs of information and aesthetics. Attitudes toward the ad and the brand are significant mediators between contextual factors and intention to purchase.

The study examines the effectiveness of online ads from a new theoretical angle based on the attributes of pay-per-click ads.

The results suggest that when advertisers decide to use dynamic ads, they should adopt a contrast design for both the ad information and its aesthetics.

This study fills a research gap in the contextual effects literature, including providing evidence of an underlying process in the relationship between certain contextual effects and purchase intent. It also extends previous findings of assimilation/contrast in information design to aesthetics design and advances the literature on vividness by examining a moderation effect of vividness.

Allocation of the marketing budget has become increasingly challenging due to the diverse channel exposure to customers. This study aims to enhance global marketing knowledge by introducing an ensemble attribution model to optimize marketing budget allocation for online marketing channels. As empirical research, this study demonstrates the supremacy of the ensemble model over standalone models.

The transactional data set for car insurance from an Indian insurance aggregator is used in this empirical study. The data set contains information from more than three million platform visitors. A robust ensemble model is created by combining results from two probabilistic models, namely, the Markov chain model and the Shapley value. These results are compared and validated with heuristic models. Also, the performances of online marketing channels and attribution models are evaluated based on the devices used (i.e. desktop vs mobile).

Channel importance charts for desktop and mobile devices are analyzed to understand the top contributing online marketing channels. Customer relationship management-emailers and Google cost per click a paid advertising is identified as the top two marketing channels for desktop and mobile channels. The research reveals that ensemble model accuracy is better than the standalone model, that is, the Markov chain model and the Shapley value.

To the best of the authors’ knowledge, the current research is the first of its kind to introduce ensemble modeling for solving attribution problems in online marketing. A comparison with heuristic models using different devices (desktop and mobile) offers insights into the results with heuristic models.

Several inferential procedures are advocated in the literature. The most commonly used techniques are the frequentist and the Bayesian inferential procedures. Bayesian methods afford inferences based on small data sets and are especially useful in studies with limited data availability. Bayesian approaches also help incorporate prior knowledge, especially subjective knowledge, into predictions. Considering the increasing difficulty in data acquisition, the application of Bayesian techniques can be hugely beneficial to managers, especially in analysing limited data situations like a study of expert opinion. Another factor constraining the broader application of Bayesian statistics in business was computational power requirements and the availability of appropriate analytical tools. However, with the increase in computational power, connectivity and the development of appropriate software programmes, Bayesian applications have become more attractive. This chapter attempts to unravel the applications of the Bayesian inferential procedure in marketing management.

The purpose of this study is to explore and identify the privacy concerns of smartphone app users pertinent to app usage.

Adopting a qualitative phenomenological approach, the authors conducted semi-structured interviews with app users to explore the app users' privacy concerns.

Credibility concerns, unauthorised secondary use and vulnerability concerns are the three major privacy concerns of app users, under which these concerns have sub-concerns, i.e. popularity, privacy policy, stalking, data sharing, hacking and personal harm.

The findings are useful to app marketers, app developers and app stores. App marketers, app developers and app stores can use the findings to understand and properly address app users' privacy concerns, thereby increasing the apps usage.

By exploring the privacy concerns of app users, the authors' study extends the literature and provides a theoretical development of individuals' privacy concerns in the context of a widely used technology, i.e. smartphone applications. Accordingly, this study contributes to the consumer privacy literature.

This study scrutinizes the convergence between commercial advertising and the political vision of social movement in media advertisements. This study deliberates how commercial advertisement could be compatible with movement discourses and social resistance. Such hybridization between commercial narration and movement discourses is different from political advertising sponsored by political and civic organizations. This study uses an advertising campaign in Hong Kong which expressed outcry against police search on an outspoken media as a case study to conceptualize advertising activism with the thematic analysis of the movement discourses shown in printed advertisements. This study aims to engage with scholarly dialogue surrounding social movement studies and discuss how movement discourses could hybridize with commercial advertisement.

This study examines the discourses and textual features of an advertising campaign initiated by the public instead of political elites and social movement organizations in Hong Kong, in which various individual citizens, anonymous participants, business enterprises and civic organizations expressed their anger over a police search against an outspoken media (Apple Daily) by Hong Kong police. This bottom-up advertising campaign shows how the narration of commercial advertising could be hybridized with the activism for social resistance, which is conceptualized as advertising activism in this paper.

Based on the textual features and discourses embedded in the advertisements, this study investigates the printed advertisements mushroomed in Apple Daily since the police search in August 2020 by the thematic analysis under the concept of advertising activism: frame construction, identities mobilization and decentered solidarity. Advertising activism differs from commercial and political advertising from two ways. Firstly, its advertisements are cosponsored by numerous nonpolitically well-known individuals or organizations. Secondly, advertising activism feature with hybridization between commercial narration and political or movement discourses. Discourses of advertising activism aim to mobilize the commercial identity of consumers for noncommercial means by their consumption behaviors.

The findings illustrate a hybridization of commercial narration and movement discourses stemming from social movement and identity politics, which is coined by our conceptualization of advertising activism. While commercial and political advertising focus on business promotion and political messages, respectively, advertising activism demonstrates multiple layers of cultural meanings on the consumption behaviors which hybridize with political and movement discourses. The authors hope this study could unleash further intellectual dialogue on the social role of advertising in social movement and how movement discourses “spillover” from social events to the commercial advertisement.

This study aims to empirically test how sponsored video customization (i.e. the degree to which a sponsored video is customized for a sponsoring brand) affects video shares differently depending on influencer characteristics (i.e. mega influencer and expert influencer) and brand characteristics (i.e. brand establishment and product involvement).

This study uses a unique real-world data set that combines coded variables (e.g. customization) and objective video performance (e.g. sharing) of 365 sponsored videos to test the hypotheses. A negative binomial model is used to analyze the data set.

This study finds that the effect of video customization on video shares varies across contexts. Video customization positively affects shares if they are made for well-established brands and high-involvement products but negatively influences shares if they are produced by mega and expert influencers.

This study extends the influencer marketing literature by focusing on a new media modality – sponsored video. Drawing on the multiple inference model and the persuasion knowledge theory, this study teases out different conditions under which video customization is more or less likely to foster audience engagement, which both influencers and brands care about. The chosen research setting may limit the generalizability of the findings of this study.

The findings suggest that mega and expert influencers need to consider if their endorsement would backfire on a highly customized video. Brands that aim to engage customers with highly-customized videos should gauge their decision by taking into consideration their years of establishment and product involvement. For video-sharing platforms, especially those that are planning to expand their businesses to include “matching-making services” for brands and influencers, the findings provide theory-based guidance on optimizing such matches.

This paper fulfills an urgent research need to study how brands and influencers should produce sponsored videos to achieve optimal outcomes.