Browsing by Author "Kitti Photikitti"
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ItemFactors impacting on online purchasing behaviour toward consumers in Bangkok, Thailand(Assumption University Press, 2020) Kitti PhotikittiThis research aimed to analyzethe factors that affect online purchasing behavior of consumers who live in Bangkok, Thailand. The variables that have been used in this study framework were perceived risks, perceived advantages, hedonic motivations, trust and security, and website content. The questionnaire was conducted and selected from 407 respondents in Bangkok area only by using non-probability sampling method as convenience and snowball sampling. The main method used to apply for this research are multiple linear regression which shows that website design and content is the most impacted factor toward consumers’ online shopping behavior. Thus, it showed that design and content of website towards online merchandise are the most important in determining online purchasing behavior of Bangkok consumers.Thefinding suggestedthat by enhancingthe consumer purchasingintentions, the online stores should rather focus on website design and content factors than address reliability and trust issues.
ItemA framework for risk management in AI system development projectsIt has been well-known that the chance of successfully delivering a software project within an allocated time and budget is very low. Most of the researches in this area have concluded that “user's requirements” of the systems is one of the most difficult risks to deal with in this case. Interestingly, until today, regardless of amount of effort put into this area, the possibility of project failure is still very high. The issue with requirement can be significantly increased when developing an artificial intelligence (AI) system, where one would like the systems to autonomously behave. This is because we are not only dealing with user's requirements, but we must also be able to deal with “system's behavior” that, in many cases, do not even exist during software development. This chapter discusses a preliminary work on a framework for risk management for AI systems development projects. The goal of this framework is to help project management in minimizing risk that can lead AI software projects to fail due to the inability to finish the projects on time and within budget.