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The objective of this research is to evaluate and rank the factors influencing omnichannel (OC) logistics, while also investigating the significant impact of big data analytics in improving these drivers of OC logistics.

Using exploratory sequential mixed method design, an in-person interview survey was conducted to identify and stratifies the enablers of OC retailing. These interviews were supplemented with a case study in an apparel firm to prioritise the enablers of OC logistics. Further, a survey was conducted to understand the role of big data analytics in improving drivers of OC logistics as well as the role of Individual capability and organisational capability in big data usage for omnichannel retailing.

Findings represent that information management is the most important driver followed by inventory management and network design for improving OC logistics. Further, significant relationship between big data analytics and drivers of omnichannel logistics has been reported.

This study identifies and classifies the drivers of OC retailing relating to their level of criticality in OC logistics which will assists practitioners to prioritise their tasks for the successful development of OC logistics. The study will also help practitioners to use BDA for developing the drivers of OC.

The study substantiates and adds to the BDA literature by emphasising the positive role of BDA in development of OC driver and highlighting the significant role of drivers of BDA in its usage.

As an important form of the e-commerce industry, online group buying is under the spotlight from with two sides: cheaper price but longer waiting time. The purpose of this paper is to adequately investigate the interaction between saving and waiting time of group buying comprehensively.

To fill the research gap, the authors elaborate a dual-channel supply chain (SC) with regular retail (individual buying) and group-buying channel, and formulate the demand based on the consumer utility with the positive effect of saving money and the negative effect of wasting time.

The authors find that power structure only changes the optimal prices, instead of the waiting time. The selling price mainly influences consumer demands, instead of the price discount of group buying. The SC profits are only positive to the channel preference, and it is the decisive parameter of consumers' choice. The price sensitivity lays a more remarkable impact on the SC compared to the time sensitivity. Above all, the price is the main factor of group buying, instead of time.

These results underscore the improvement for the dual-channel SC of group buying, providing managerial insights for the group-buying industry.

Gig workers form the backbone of any crowdsourcing platform where they showcase their talent and choose a job of their choice and freedom. The study explores the role of information quality (IQ) and social-mediated dialogue (SMD) in evaluating gig worker engagement and productivity on crowdsourcing platforms. The authors also propose to understand how gig worker productivity could be improved under the moderating effect of game elements.

A conceptual model was developed and empirically tested by integrating media richness theory and dialogic public relation theory. Data were collected from gig workers that are involved in crowdsourcing activities for the past three years. An overall sample of 346 gig workers contributing to at least one of the crowdsourcing platforms was collected. The authors tested the hypotheses using Warp PLS 7.0. Warp PLS 7.0 uses partial least square (PLS) structured equation modeling (SEM) and has been used widely to test path analytical models.

Results reveal that the information quality plays an essential role in the SMD, thereby fostering gig workers' productivity and engagement, which could be improved in the presence of game elements due to their nature of supporting rewards. However, engagement in the platform leading to improved productivity was not supported.

The study lays practical foundations for crowdsourcing platforms as it sets the importance of both IQ and dialogic communication channels. The two-way communication between gig workers and the platforms via accurate, timely, valuable and reliable information forms the key to the task's success. The introduction of the right game element will help to achieve better engagement and productivity.

This study also offers a new dimension to media richness theory and dialogic public relation theory in crowdsourcing platforms. The results would help platform designers and gig employers understand gig workers' quality and performance in a platform economy. The study uniquely positions itself in the area of crowdsourcing platforms by using game elements.

The objective of this research is to analyze how omnichannel consumer journey design (OCJD) influences the online customer experience (OCE) and e-satisfaction in consumers' multirooming behavior (searching for information in online and offline channels and purchasing the product online).

The problem-solving theory and experiential marketing perspective are the theoretical background that enables the establishment of five hypotheses. A survey is conducted on multiroomers who had purchased a product online, following an online and offline research journey.

The results showed that OCJD directly and indirectly (through online consumer experience) influences e-satisfaction. Females and younger individuals exhibited higher levels of e-satisfaction.

First, this research analyzes consumers' multichannel search strategies. Second, the consumer journey is incorporated into the study of multichannel retailing. Third, an emergent typology of cross-channel free-riding behavior is analyzed: multirooming.

The paper attempts to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a two-part tariff coordination mechanism.

To deal with this pricing conflict problems of dual-channel supply chain consisting of dominant manufacturer and a retailer, considering the fact that online reviews and in-sale service are important factors on consumers’ purchase decisions, the authors establish some basic models and exploit them to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a profit-sharing coordination mechanism.

The results show that the optimal online direct selling price is positively correlated with product perceived quality obtained from online reviews and negatively correlated with the in-sale service. The traditional retail price is positively correlated with the in-sale service and weakly correlated with online reviews. For the manufacturer and retailer, whether decentralized decision or coordination contract, their profits increase with the increase of the in-sale service in a certain range and quality perceived from spontaneous online reviews. Online reviews and in-sale service are important factors on consumers’ purchase decisions. Positive in-sale services and online reviews can provide consumers with a better shopping experience, thereby promoting their enthusiasm for shopping and improving their quality of life. The two-part tariff coordination mechanism improves the profits of the manufacturer and the traditional retailer, respectively, through the transfer fee.

The proposed approach can well analyze the channel conflicts and pricing problems between retailers and manufacturers with respect to product offline price and online price. The analysis and results can inform decision-making for manufacturers and retailers.

Product discounts have been widely applied in digital commerce as a method to attract and retain customers to purchase in China. Given that digital channels differ in their attributes, customers may behave differently when they respond to the same discount across channels. However, little attention has been paid to explore the heterogeneity of customer responses to discounts across channels. This study aims to fill in the gap by exploring how customers’ purchase responses to price discounts differ across digital channels.

This study applies a Poisson regression to an unbalanced data set of purchasing history from Chinese footwear brands with 3,510 customers in a two-year time window across the three digital channels (i.e. personal computer [PC], app and mobile website), with a correction for endogeneity by using the Gaussian copula method.

This paper finds that price discounts have the strongest positive effect on consumers’ purchase volumes on the PC channel, followed by the app channel, while discounts show the weakest impact in the mobile website channel. By so, this paper demonstrates that customers respond differently to online and mobile channels, and they also respond differently within mobile channels when they purchase products with price discounts.

This study is original in analyzing the difference in customers’ discount responses across digital channels, offering valuable contributions to existing research on multichannel marketing as well as mobile marketing and providing helpful insights for multichannel merchants to design digital discount strategies.

This empirical study aims to examine luxury fashion retailers' localised multiple channel distribution strategies in China.

Through case studies of 15 participating retailers, qualitative data were collected from 33 semi-structured interviews.

Strong impacts of internationalisation strategies, distribution strategies and channel length towards multiple channel retailing are revealed. Multi-channel retailing is widely employed by firms who have entered China and further developed their businesses through local partnerships and adopted a selective distribution strategy via relatively longer channels. Omni-channel retailing is only suitable for the few retailers using an exclusive distribution strategy through direct marketing and wholly owned customer relationship management. As a dynamic transformation from multi- to omni-channel retailing, cross-channel retailing is adopted by those who are withdrawing from local partnerships and shifting to wholly owned expansions and operations in host markets.

The results are potentially challenged by relatively small sample size.

Practitioners are suggested to adapt multiple channel retailing to their international expansion strategies, distribution strategies and channel length in the host markets.

This paper contributes to the literature in both multiple channel retailing and international retailing by offering insights into the motives, development patterns and suitability of multiple channel retailing in the international retail marketing context.

The purpose of this paper is to present an up-to-date survey on the non-orthogonal multiple access (NOMA) technique with co-operative strategy, a fast-evolving fifth-generation (5 G) technology. NOMA is used for serving many mobile users, both in power and code domains. This paper considers the power-domain NOMA, which is now discussed as NOMA.

The first part of the paper discusses NOMA-based cooperative relay systems using different relay strategies over different channel models. In various research works, the analytical expressions of many performance metrics were derived, measured and simulated for better performance of the NOMA systems. In the second part, a brief introduction to diversity techniques is discussed. The multiple input and multiple output system merged with cooperative NOMA technology, and its future challenges were also presented in this part. In the third part, the paper surveys some new conceptions such as cognitive radio, index modulation multiple access, space-shift keying and reconfigurable intelligent surface that can be combined with NOMA systems for better performance.

The paper presents a brief survey of diverse research projects being carried out in the field of NOMA. The paper also surveyed two different relaying strategies that were implemented in cooperative NOMA over different channels and compared several performance parameters that were evaluated and derived in these implementations.

The paper provides a scope for recognizable future work and presents a brief idea of the new techniques that can be united with NOMA for better performance in wireless systems.

This paper aims to examine why retail firms seldom achieve full integration of online and offline channels as prescribed in omni-channel literature. It examines the intermediate process of channel integration from an internal, operational perspective.

This study is composed of two parts. In the first part, the authors interviewed informants from nine firms that were engaged in channel integration. In the second part, the authors conducted case studies with three firms from the cosmetics and skincare industry against the backdrop of the COVID-19 pandemic to find evidence to support or negate the propositions made in the first part.

The first part identified six operational challenges to channel integration. The authors categorized these challenges into two groups: inter-channel communication and inter-channel competition. Inter-channel competition carries more weight at the latter stage of integration. The authors also identified two antecedents that affect the seriousness of these challenges: heterogeneity among channels in business operation and external competitive pressure. In the second part, the authors found that both inter-channel communication and inter-channel competition were improved because of the external competitive pressure exerted by the COVID-19 pandemic. However, the heterogeneity of offline channels against online channels in business operation is a double-edged sword.

The study identifies the changing effects of the challenges of channel integration and their antecedents in the midst of integration. The positive influence of a specific dimension of channel heterogeneity against other channels increases and then decreases along channel integration. The identification of the changing effects lays the foundation for a finer stage model of channel integration.

Social participation and user-generated contents have engendered an era when “any receiver can be a provider.” Although studies have emphasized on increasing the number of subscribers conducive to platform success, the issue regarding why viewers drop their registered YouTuber channels has been less addressed. This article aims to present and empirically test a causal model to account for the pattern of discontinuous intention of attention to YouTuber channels.

Inspired by the expectation–disconfirmation theory, the study proposes and examines a research model by using an empirical quantitative approach. The proposed model considers channel and YouTuber facets, as well as potential moderation effects of viewing seniority.

Analysis of a sample of 406 questionnaires revealed that ads interference is not a significant reason for discontinuation of viewing a channel, in contrast to insufficient playfulness and inconsistency. Regarding YouTubers’ features, both interaction inadequacy and negative self-disclosure are significant determinants of perceived dissatisfaction and discontinuation of viewing. The effects of determinants of discontinuity depend on viewers' seniorities, except for negative self-disclosure.

While existing studies have focused mainly on revealing the determinants associated with the behavioral intention of viewing YouTuber channels to increase self-media performance, this research contributes insights into the literature investigating why existing viewers stop following a certain YouTuber channel. From a psychological perspective, this study demonstrates the value of modeling discontinuous behaviors toward YouTuber channels in the domain of social marketing.