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Using of Social Media Data Analytics for Applying Digital Twins in Product Development

机译:使用社交媒体数据分析应用数字双胞胎在产品开发中的应用

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摘要

Product development as an iterative combination of different disciplines like design, process planning, engineering, manufacturing, logistics, marketing and sales is a challenging issue. Researchers have argued that high product mortality rate, is not only down to factors related with the design of a certain product, but also the fact that consumer engagement and customer behavior are decisive in the product development stages. Dealing with consumers is a big challenge due to the enormous variety of feedback data and qualitative aspects of them. Mostly, the communication channels with consumers are through Social Media (SM) which are usually unstructured and hard to be analyzed. This research has investigated the importance and influence of the emotional behavior of users in accepting new products through a social media analytical approach. The paper has developed a framework to relate the user emotions and new product feature development plan through SM platforms such as Twitter. It is discovered that emotions can be considered as one the important elements for identifying the subjective nature of product attributes. The paper shows that diverse emotions and their role in New Product Development (NPD) processes, specifically in prelaunch phase. A case study has been designed to show the capabilities of the proposed framework in this research. The pre-launch and post-launch emotion Comparisons indicate the possibility of shifting users’ behavioral focus for the new product while considering the required market indicators.
机译:产品开发作为不同学科的迭代组合,如设计,流程规划,工程,制造,物流,营销和销售是一个具有挑战性的问题。研究人员认为,高产品死亡率,不仅使其与某种产品的设计有关的因素,而且是消费者参与和客户行为在产品开发阶段决定性的事实。由于巨大的反馈数据和它们的定性方面,处理消费者是一个很大的挑战。主要是,与消费者的通信渠道通过社交媒体(SM),这些媒体通常是非结构化的,并且难以分析。本研究对用户通过社交媒体分析方法的接受新产品的情感行为的重要性和影响。本文开发了一个框架,通过Twitter等SM平台将用户情绪和新产品特征开发计划联系起来。发现情绪可以被视为识别产品属性的主观性的重要元素。本文表明,不同的情绪及其在新产品开发(NPD)流程中的作用,特别是在预升级阶段。案例研究旨在展示本研究拟议框架的能力。发布前和发布后的情感比较表明,在考虑所需的市场指标时将用户行为关注推翻用户的行为关注。

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