Microservice Transition and its Granularity Problem: A Systematic Mapping Study

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying "micro-ing" architectures. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modelling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table

Exploring the Determinants of Hot Spring Tourism Customer Satisfaction: Causal Relationships Analysis Using ISM

To stand out in the hot spring tourism industry, customer satisfaction has become the crucial issue for competitiveness. A company cannot implement several customer satisfaction improvement practices altogether with limited resources. Researchers advocate that companies should evaluate the relationships among success factors and explore determinants for their improvement implementation. However, such a relationship evaluation has not yet been adequately performed. This paper intends to explore the determinants for improving hot spring customer satisfaction. Adopting grounded theory (GT) and using data collected from websites, Ctrip and Qunar, the first 12 key factors for customer satisfaction were identified. Then, their interrelationships were assessed by 15 experts, and interpretive structural modeling (ISM) was employed to analyze the interrelationships and the driving and dependence power among key factors. The results show that “Environment Quality”, “Special Resource”, “Convenience”, “Food”, Service Quality”, and “Facilities” were the decisive factors affecting customer satisfaction. The findings offer important implications for hot spring management and practice. The contribution of this study is using a novel approach to establish a hierarchical structural model for comprehensive understanding of factor relationships that influence hot spring tourists’ satisfaction and to explore decisive factors which can help hot spring practitioners to better plan and design effective improvement strategies to attract potential new consumers and retain their current consumers, especially with limited resources