Using blockchain to signal quality in the food supply chain: The impact on consumer purchase intentions and the moderating effect of brand familiarity

Food safety is a public health issue of paramount importance. In this regard, blockchain has emerged as a promising technology that allows users to effectively and efficiently record the origin and flow of products and eliminate or reduce harmful food fraud. Consumers can benefit from this development by receiving up-to-date and verifiable information about the origins and delivery routes of their purchases. Drawing on signaling theory and the results of two experimental studies with 151 and 152 participants, respectively, we investigate how the use of blockchain to trace food products impacts consumers’ perception of product quality as a mediating variable and subsequently their purchase intention. Our framework further considers brand familiarity as a moderating variable. The findings from the two experiments show that blockchain labels as a signaling mechanism in food supply chains help to strengthen consumers’ perceived quality of food products, which, in turn, increases their purchase intention. This effect is more pronounced for less familiar brands, which is valuable information for managers who want to build a brand’s reputation. From an academic perspective, we highlight the applicability of signaling theory to identify blockchain-based traceability systems as important drivers of perceived product quality and consequently purchase intention.     

基于结构矩阵软的件需求变化追溯方法研究

随着软件需求工程快速增长和普及,人们开始研究软件需求变化和追溯方法,以及处理需求变化的自动化方法和追溯相关问题系统方法。从三维角度研究了软件需求变化目标驱动可追溯方法：基于目标驱动用例方法研究软件开发和需求管理;建立和维护相关可追溯设计结构模型（DSM）,目的是提取可追溯树;通过DSM的分割技术,分析需求变化产生的影响。