Social media big data offers insights that can be used to make predictions of products' future demand and add value to the supply chain performance. The paper presents a framework for improvement of demand forecasting in a supply chain using social media data from Twitter and Facebook. The proposed framework uses sentiment, trend, and word analysis results from social media big data in an extended Bass emotion model along with predictive modelling on historical sales data to predict product demand. The forecasting framework is validated through a case study in a retail supply chain. It is concluded that the proposed framework for forecasting has a positive effect on improving accuracy of demand forecasting in a supply chain.

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Purpose The purpose of this paper is to investigate the perceptions of food anti-consumption in fast growing markets within an emerging economy context of Turkey. Design/methodology/approach Recently posted customer comments, complaints and suggestions related to the selected fast-food chains were examined from the following domains: Facebook, Instagram, Twitter and Sikayetvar.com. These comments were reviewed, assessed and classified by four trained independent raters. After examining the comments one-by-one the raters arrived at the final (triangulated) decision regarding the comment’s category after an iterative process including cross-examination. Findings Reasons for fast-food avoidance were primarily linked to customers’ negative past experiences (experiential avoidance). Identity avoidance, moral avoidance and interactivity avoidance. Originality/value The paper adds to the anti-consumption literature by examining the food avoidance framework of Lee et al. (2009) in an emerging market context. New categories were identified for reasons of food avoidance which have not been identified before in the anti-consumption literature such as interactivity avoidance.

In order to provide a seamless customer experience, researchers and practitioners have proposed creation of an omnichannel retailing environment by integrating online and offline channels. Channel integration necessitates use of digital technologies and there are myriads of technological solutions available. However, retailers are struggling with selection and implementation of suitable technologies to add value through channel integration. Despite the strong practical need, this issue has not been effectively addressed in the academic literature. This paper presents an omnichannel value chain underpinned by Porter's value chain model. We identify ten channel integration activities for value creation by carrying out a synthesis of current research on omnichannel retailing. Enabling digital technologies are then mapped to these activities using technology implementation examples and provide a guideline for retailers to select appropriate technologies for the identified value creation activities.

Most retailers are currently undergoing a major transformation in the process of becoming omnichannel retailers. This case addresses the challenges of an Irish company in the transition from an offline focused retailer to an omnichannel company. Building on its strong expertise in traditional offline retail, the company is aiming to establish itself as an omnichannel retailer that allows for increasing its customer base in Ireland and overseas. The case describes actual challenges along the journey, including the strategic, operational, and technological challenges. It provides an opportunity for students to discuss and understand the practical aspects of the retail transformation process and the linkage between technology and business strategy. The case enables discussions on the multiple aspects in the process of transformation toward omnichannel retail and promotes the development of innovative solutions for transferring customer experience provided in offline retail to online platforms.