The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that: • a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.

Structured Abstract: PurposeThe study is to examine determinants of continuous brand-customer relationship via company-hosted SNSs (social networking sites). Factors that influence fans to continue using fast-fashion brands' Facebook fan pages and to maintain the brand-customer relationship are firstly discussed. Subsequently, predictors of fans' engagement and affective commitment to a fast-fashion brand are examined with aim to explore key elements which nurture brand-customer relationship via brands' SNSs. Design/methodology/approachQuantitative research was conducted and structural equation modeling was used, to test the hypotheses on a sample of 202 fast-fashion Facebook fan-page users in Taiwan. FindingsResults demonstrate that engagement, affective commitment and continued intention to use are predominantly influenced by, in turn, social interaction tie, content value and affective commitment. Research limitations/implicationsThe study is limited because it investigated the fast-fashion fan page users in on Asian country, so the findings cannot be generalised to other contexts. Practical implicationsOur findings suggest fan page managers' initiation and involvement in conversations, frequent responses, listening to fans' opinions, and improving fans' experiential value may facilitate them to engage in the brand's activities at a higher level. Originality/valueFindings of this integrated model suggest managerial guidelines for brand managers in this industry regarding how to maintain the brand-customer relationship through social media strategy and they contribute to theory building in continuance intention of SNSs.

Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractA segmentation approach is presented using both traditional demographics segmentation bases (age, social class/occupation and working status) and a segmentation by benefits sought. The benefits sought is in this case are utilitarian and informational reinforcement, variables developed from the Behavioral Perspective Model (the BPM). Using data from 1847 consumers and a total of 76,682 individual purchases brand choice and price and reinforcement responsiveness was assessed for each segment across the UK cookie (biscuits) market. Building on previous work the results suggest that the segmentation of brand choice using benefits sought is useful. This is especially the case alongside demographic variables. This paper provides a theoretical and practical segmentation approach to both the behavioral psychology literature and the wider marketing segmentation literature.

Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details.

Viral marketing campaigns are often negatively affected by overexposure. Overexposure occurs when users become less likely to favor a promoted product after receiving information about the product from too large a fraction of their friends. Yet, existing influence diffusion models do not take overexposure into account, effectively overestimating the number of users who favor the product and diffuse information about it. In this work, we propose the first influence diffusion model that captures overexposure. In our model, Latency Aware Independent Cascade Model with Overexposure (LAICO), the activation probability of a node representing a user is multiplied (discounted) by an overexposure score, which is calculated based on the ratio between the estimated and the maximum possible number of attempts performed to activate the node. We also study the influence maximization problem under LAICO. Since the spread function in LAICO is non-submodular, algorithms for submodular maximization are not appropriate to address the problem. Therefore, we develop an approximation algorithm that exploits monotone submodular upper and lower bound functions of spread, and a heuristic that aims to maximize a proxy function of spread iteratively. Our experiments show the effectiveness and efficiency of our algorithms.