Use of twitter data for waste minimisation in beef supply chain

Approximately one third of the food produced is discarded or lost, which accounts for 1.3 billion tons per annum. The waste is being generated throughout the supply chain viz. farmers, wholesalers/processors, logistics, retailers and consumers. The majority of waste occurs at the interface of retailers and consumers. Many global retailers are making efforts to extract intelligence from customer’s complaints left at retail store to backtrack their supply chain to mitigate the waste. However, majority of the customers don’t leave the complaints in the store because of various reasons like inconvenience, lack of time, distance, ignorance etc. In current digital world, consumers are active on social media and express their sentiments, thoughts, and opinions about a particular product freely. For example, on an average, 45,000 tweets are tweeted daily related to beef products to express their likes and dislikes. These tweets are large in volume, scattered and unstructured in nature. In this study, twitter data is utilised to develop waste minimization strategies by backtracking the supply chain. The execution process of proposed framework is demonstrated for beef supply chain. The proposed model is generic enough and can be applied to other domains as well

Business Impacts of Technology Disruption - A Design Science Approach to Cognitive Systems’ Adoption Within Collaborative Networks

Part 10: Collaborative Business StrategiesInternational audienceDigitalisation and data are stated to be significant drivers of change, technology disruption, and new business. The purpose of this study is to explore the business impacts of technology disruption, more specifically the adoption of cognitive systems within collaborative networks through a design science approach. In accordance with design studies, the relevance of the research results and the research quality are evaluated against the practices of seven companies that participated in the research process. At the crossroads of technology and business disruption the two main dimensions illustrate: (1) the technical complexity of cognitive systems adapted from conventional data utilisation to learning cognitive systems and (2) the broadness of business impacts from a company’s internal processes to changes in ecosystems

Business Roles in Creating Value from Data in Collaborative Networks

The present study investigates activities and actors’ roles in how companies utilise and adopt big data and cognitive systems in their business processes. Based on the literature review, a qualitative analysis of 18 in-depth interviews with participants from six companies and a complementary review of five illustrative case companies, we identify five different roles to create business value or new business opportunities in the collaborative networks. Based on those business roles, we also identified activities and outcomes. This study contributes to the debate regarding business roles and activities and how companies create value in adopting data and cognitive systems in collaborative networks. For practitioners, the findings show that different data-driven business roles and opportunities exist in the collaborative networks. The business roles are not exclusive, and the same company can have several roles depending on the business case.</p