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Yan-Kwang Chen, Yi-Ju Chen, Fei-Rung Chiu and Cheng-Yi Wang

Abstract

Background: The rise of cloud services has led to a drastic growth of e-commerce and a greater investment in development of new cloud services systems by related industries. For SaaS developers, it is important to understand customer needs and make use of available resources at as early as the system design and development stage. Objectives: This study integrates E-commerce Systems (ECS) Success model and Importance-Performance Analysis (IPA) into empirical research of the critical factors for cloud ordering system success. Methods/Approach: A survey research is conducted to collect data on customer perceptions of the importance and performance of each attribute of the particular cloud ordering service. The sample is further divided according to the degree of use of online shopping into high-usage users and low-usage users in order to explore their views regarding the system and generate adequate coping strategies. Results: Developers of online ordering systems can refer to the important factors obtained in this study when planning strategies of product/service improvement. Conclusions: The approach proposed in this study can also be applied to evaluation of other kinds of cloud services systems.

Open access

Gencer Erdogan, Atle Refsdal, Bjørn Nygård, Ole Petter Rosland and Bernt Kvam Randeberg

Abstract

Background: During major maintenance projects on offshore installations, flotels are often used to accommodate the personnel. A gangway connects the flotel to the installation. If the offshore conditions are unfavorable, the responsible operatives need to decide whether to lift (disconnect) the gangway from the installation. If this is not done, there is a risk that an uncontrolled autolift (disconnection) occurs, causing harm to personnel and equipment. Objectives: We present a decision support model, developed using the DEXi tool for multi-criteria decision making, which produces advice on whether to disconnect/connect the gangway from/to the installation. Moreover, we report on our development method and experiences from the process, including the efforts invested. An evaluation of the resulting model is also offered, primarily based on feedback from a small group of offshore operatives and domain experts representing the end user target group. Methods/Approach: The decision support model was developed systematically in four steps: establish context, develop the model, tune the model, and collect feedback on the model. Results: The results indicate that the decision support model provides advice that corresponds with expert expectations, captures all aspects that are important for the assessment, is comprehensible to domain experts, and that the expected benefit justifies the effort for developing the model. Conclusions: We find the results promising, and believe that the approach can be fruitful in a wider range of risk-based decision support scenarios. Moreover, this paper can help other decision support developers decide whether a similar approach can suit them