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An omni-channel is a retailing strategy that the behavior of companies adopts many retail channel types to combine and integrate cross-channel sales to meet the comprehensive needs of customers in shopping, entertainment and social networking both online and offline. This leads to several research questions of retailing omni-channel in this study. First, do channel brand trust (CBT) and store image (SI) affect re-patronage intentions through customer satisfaction (CS)? Second, regarding online rating (OR) and online involvement (OI), will CS be determined by consumer perception as well as the relevance of those attributes to the customer's re-patronage intentions? Third, do OR and OI have a role in exploring the moderating effect in the research model? Fourth, if there are positive effects from this relationship, it can generate a positive power return online. In addition, online-to-offline moves on a path for case firm omni-channel with customers' OR and OI with a reciprocal positive influence.

This study aims to investigate the relationship between CBT, SI, CS and re-patronize intention in an omni-channel. By using structural equation models (SEMs), this study aims to investigate offline-to-online and online-to-offline re-patronizing in the Taiwan Chunghwa Telecom (CHT) omni-channel (N = 1,642). Two moderated mediation models are investigated in this study.

This study first found that CBT and CS use SI to influence re-patronize intention in the omni-channel. SI plays a mediating role in this process; OR and OI influence the relationships of CBT, CS and re-patronize intention with two moderating roles.

This study first found that there is a reciprocal way with two paths in an omni-channel, starting with offline-to-online, in terms of confirming the relationship of CBT, CS and re-patronize intention in an omni-channel. There are positive effects from this relationship, and it can generate a positive power return online. In addition, we found that online-to-offline moves on a path that has a stronger influence of re-patronize intention for omni-channel with customers' OR and OI.

Research comparing offline and cyberbullying is relatively sparse, with scholars suggesting the need for empirical investigations to clarify whether cyberbullying and offline bullying are similar or different constructs.

Using an experimental vignette methodology, the current study of 163 working participants obtained via social media examines the effect of medium (offline vs cyberbullying), type (person-related vs work-related) and the interaction between medium and type on perceptions of definitional criteria (severity, frequency, power and intent) and outcomes (negative emotion, fairness, job satisfaction and turnover intention).

Significant differences between offline and cyberbullying were seen only for ratings of severity, job satisfaction and turnover intention, with cyberbullying perceived as more severe and as having a more detrimental impact on job satisfaction and turnover intention. Stronger effect sizes emerged for type of bullying, with person-related bullying having a stronger negative impact on definitional criteria and outcomes than work-related bullying. Moreover, interaction effects suggested differences between the two media were dependent on type of act – with person-related/cyberbullying acts seen more negatively than other acts.

This paper is the first to use a vignette approach to test the similarity or difference hypothesis between offline and cyberbullying. Overall, limited support is seen for the notion that offline bullying and cyberbullying are perceived as different constructs, with type of behaviour suggesting a more complex relationship between the two.

Offline reinforcement learning (RL) acquires effective policies by using prior collected large-scale data, while, in some scenarios, collecting data may be hard because it is time-consuming, expensive and dangerous, i.e. health care, autonomous driving, seeking a more efficient offline RL method. The purpose of the study is to introduce an algorithm, which attempts to sample the high-value transitions in the prioritized buffer, and uniformly sample from the normal experience buffer, improving sample efficiency of offline reinforcement learning, as well as alleviating the “extrapolation error” commonly arising in offline RL.

The authors propose a new structure of experience replay architecture, which consists of double experience replies, a prioritized experience replay and a normal experience replay, supplying samples for policy updates in different training phases. At the first training stage, the authors sample from prioritized experience replay according to the calculated priority of each transitions. At the second training stage, the authors sample from the normal experience replay uniformly. The combination of the two experience replies is initialized by the same offline data set.

The proposed method eliminates out-of-distribution problem in an offline RL regime, and promotes training by leveraging a new efficient experience replay. The authors evaluate their method on D4RL benchmark, and the results reveal that the algorithm can achieve superior performance over the state-of-the-art offline RL algorithm. The ablation study proves that the authors’ experience replay architecture plays an important role in terms of improving final performance, data-efficiency and training stability.

Because of the extra addition of prioritized experience replay, the proposed method increases the computational burden and has the risk of changing data distribution due to the combined sample strategy. Therefore, researchers are encouraged to use the experience replay block effectively and efficiently further.

Offline RL is susceptible to the quality and coverage of pre-collected data, which may be not easy to be collected from specific environment, demanding practitioners to handcraft behavior policy to interact with environment for gathering data.

The proposed approach focuses on the experience replay architecture for offline RL, and empirically demonstrates the superiority of the algorithm on data efficiency and final performance over conservative Q-learning across diverse D4RL tasks. In particular, the authors compare different variants of their experience replay block, and the experiments show that the stages, when to sample from the priority buffer, play an important role in the algorithm. The algorithm is easy to implement and can be combined with any Q-value approximation-based offline RL methods by minor adjustment.

The purpose of this research is to investigate how to introduce a financing scheme to tackle the manufacturer's capital constraint problem, discuss the effects of data-driven marketing (DDM) quality, cross-channel-return (CCR) rate and financing interest rate on the members' pricing and delivery-lead-time decisions and optimal performances, and analyzes `how to achieve the coordination within a dual-channel supply chain (DSC) by contract coordination.

This work establishes a DSC model with DDM, and the offline retailer can provide internal financing to the capital-constrained online manufacturer. The demand under the price is determined based on DDM quality, customer channel preference and delivery lead time. Then, combined with the Stackelberg game, the optimal pricing and delivery-lead-time decisions are discussed under the inconsistent and consistent pricing strategies with decentralized and centralized systems. Furthermore, it designs a manufacturer-revenue sharing contract to coordinate the members under the two pricing strategies.

(1) The increase of DDM quality will reduce the delivery-lead-time under the inconsistent or consistent pricing strategy and will push the selling prices; (2) The growth of the CCR rate will raise selling prices and extend the delivery-lead-time under the decentralized decision; (3) Under price competition, the offline selling price is higher than the online selling price when customers prefer the offline channel and vice versa; (4) The retailer and the manufacturer can achieve a win-win situation through a manufacturer-revenue sharing contract.

This paper contributes to the studies related to DSC by investigating pricing and delivery-lead-time decisions based on DDM, CCR, internal financing and supply chain contract and proposes some managerial implications.

Enterprises' multichannel operations provide various avenues for customer interaction; however, existing literature investigating customer-to-customer interaction (CCI) mainly focuses on a single channel. The purpose of this paper is to investigate the spillover effect of CCI and potential underlying mediating mechanisms in different information channels.

Three between-subjects experiments with 946 participants were employed to empirically validate the proposed hypotheses in the context of an experiential product and a material product.

Results suggest the clear spillover effect of CCI, indicating that positive CCI improves focal customers' satisfaction and purchase intention, whereas negative CCI reduces focal customers' satisfaction and purchase intention. Moreover, CCI's spillover effect varies based on the CCI channel. Offline CCI has a stronger positive spillover effect than online CCI. Contrarily, online CCI has a stronger negative spillover effect than offline CCI. Customer experience and trust are demonstrated to have mediating roles in this process.

This study is the first to comprehensively understand and compare the CCI spillover effect of the two information channels. The findings add to the existing knowledge of information processing in the psychological mechanisms influencing the belief in addition to providing insights for companies engaged in multichannel operations management across different channels.

To examine the effectiveness of a multichannel strategy, this study mainly investigates two issues: (1) whether customers' five value perceptions (i.e. product quality, service quality, innovation, price and store image) extend from e-stores to physical stores and (2) whether customers' five value perceptions derived from e-stores/physical stores facilitate purchase intention within and beyond the channel context.

This study develops a research model to elaborate on the relationships between the focal constructs and collects 177 useable responses via an online community and personal contacts survey. Partial least squares structural equation modeling (PLS-SEM) methods and mediation analyses are conducted to validate the proposed hypotheses.

The results show that the values perceived in e-stores/physical stores generally motivate online/offline purchase intention, respectively. Next, based on Tversky's belief/feature matching process, the five value perceptions correlate with their counterparts across online and offline channels. The results of the mediation analyses suggest that the advantages established in online channels may be contagious to offline channels at the belief level. Specifically, four of the five online value perceptions may have different effects on offline purchase intention: (1) product quality perceived in e-stores directly (negative) and indirectly (positive) results in offline purchase intention, demonstrating cannibalization effects and (2) service quality, innovation and store image perceived in e-stores indirectly and positively contribute to offline purchase intention, indicating synergetic effects.

The findings of this study provide several important theoretical and practical implications for multichannel and omnichannel retailing strategies.

This paper aims to explore the interaction between consumer empowerment and social interactions as fundamental social media elements. It demonstrates their relationship in both experiential and informative social media setting where social media complements an offline consumer activity. The study aims to contribute to the literature on social media by demonstrating its complementary role on offline activities through these fundamental elements.

The paper reports three experimental designs that manipulate the empowering and the socializing elements of complementary activities to show their effects on both the complementary online and the complemented offline activities.

The paper presents three empirical studies that reveal the effects of two fundamental social media elements (i.e. empowerment and socialization) on consumers’ responses toward consumption episodes that consist of complementary online and complemented offline activities. It reveals that that these elements increase positive consumer responses toward both the online and the offline activities through psychological empowerment. However, the interaction between the elements changes with respect to specific empowerment types.

The paper contributes to the literature on social media by demonstrating its complementary role on offline activities through its empowering and socializing elements. It bridges research on consumer empowerment and socialization in a way that reveals their interaction beyond the extant definitions of empowerment resulting from enhanced communication among consumers. The paper also demonstrates the complementary role of social media on offline consumer behaviors through the effects of these two fundamental elements.The participants of the experimental studies are presented with hypothetical scenarios and asked about their behavioral intentions. Thus, future studies should address the research questions in real-world settings.

The paper includes implications for social media usage as a complementary activity to offline real-life consumer behavior through the effects of consumer empowerment and social interactions. Thus, it may benefit marketers seeking to optimize the empowering and socializing components of their social media strategies.

This paper fulfils an identified need to study how social media may affect real-life consumer behavior. It also identifies the interaction between the empowering and the socializing elements of social media offerings in both experiential and informative settings.

The purpose of this article is to investigate if and how social capital offline – stemming from face-to-face interactions – and social capital online – stemming from social digital media – can influence early-stage entrepreneurs, i.e. ventures with up to 42 months of existence.

The authors used herein a qualitative research approach. The method used was the case study. The authors investigated three early-stage entrepreneurs in order to achieve the objective of the paper. These entrepreneurs are both the unit of analysis and the unit of observation.

The outcomes of this research indicate (1) the combined importance of social capital offline and online; (2) the different performance of the two different types of social capital (they seem to operate in relatively distinct ways) and (3) the existence of recursiveness between resources stemming from the two social spheres (offline and online).

As research limitations, the authors point out the following: (1) the use of semistructured interviews as the only data collection instrument; (2) the limitation of the outcomes to entrepreneurs only (3) the absence of information on the performance of the business ventures; the focus of the paper was only on establishing causality between social capital offline and online and entrepreneurial performance.

This paper provides important research contributions. Initially, the paper presents a range of offline and online variables, which can be used in further research. At the same time, the paper emphasizes the combined impact of social capital offline and online, expanding the literature related to entrepreneurship. Moreover, this study proposes the creation of an integrative model. Finally, the authors point out the need for new theoretical and empirical studies on the subject, which still presents a gap in the literature.

The purpose of this paper is to investigate the effects of multichannel integration (MCI) on customer loyalty. The specific objectives are to provide an appropriate reliable measure of the construct, and to analyse the impact of MCI on offline and online loyalty, both directly and by mediation of customer satisfaction.

The paper focusses on the retail apparel sector of Spain and the UK. The authors applied a scale development process and tested the model with data of 761 multichannel apparel shoppers. The proposed theoretical model was estimated through EQS 6.1 and a mediation test was calculated.

The findings show, first, that the construct of channel integration has two dimensions: reciprocity, which refers to the possibility of crossing the channels while shopping, and coordination, which refers to the alignment of offline and online offers. Second, that MCI affects positively both offline and online loyalty both directly and through satisfaction, which partially mediates the relationship.

Culture might play a moderating role in the relationships found that are not analysed.

The findings have implications for the managers of multichannel retail companies as they help to understand the benefits of channel integration in creating a loyal customer base both online and offline.

This paper contributes to the literature on multichannel retailing in two main ways: first, by developing a scale to measure MCI, and second, by demonstrating that MCI has strong effects on customer satisfaction and loyalty.

The purpose of this paper is to understand loyalty in the multichannel retail context. The paper analyses the interplay between offline and online loyalty and the direct and indirect effects on loyalty of brand trust and brand attachment, in a cross-cultural study.

Online survey answered by 761 multichannel apparel shoppers in two countries (UK and Spain). Structural equation model multigroup analysis is performed to test the hypothesized relations and the role of culture as a moderating variable.

Online loyalty is largely driven by offline loyalty, which is also positively affected by brand trust and brand attachment. These relationships hold across the two different cultures.

The findings confirm the validity of applying the theory of cognitive dissonance to explain multichannel shopping behaviours. The authors did not find culture that affects the relationships in the model; however, the validity of these findings should be tested considering other cultural variables different from nationality.

Multichannel retailers should focus on building trust and attachment towards the brand if they want to get online and offline loyalty. The efforts to build stronger bonds between the customer and the retail brand translate into higher loyalty, particularly towards the offline channels.

This paper extends the literature on the interactions between online and offline behaviour by focussing on the power of the brand to build strong customer bonds. The model considers the role of brand attachment together with brand trust in offline and online loyalty simultaneously.