Setting Up and Running a Q-Methodology Study in an Online Survey Research Suite

The q-method, as a graphic (visual) elicitation, has existed since the mid-1930s. Setting up a q-method, with q-sort capabilities, in an online survey platform, extends the reach of this method, even as data has to be processed in a quantitative data analytics suite. This chapter describes the setting up of a visual q-sort and the related debriefing on the Qualtrics Research Suite. The available data may be extracted and analyzed in a basic statistical analysis tool for factors and preference clusters.

A Primer on Q-Method and the Study of Technology

Qualitative methods are under-represented in the articles published by the main journals in Information Systems, which seem to privilege quantitative studies and statistical representativity of results, following the R logic. This chapter provides an in-depth description of Q-method and demonstrates how its use could be beneficial to studies of technology and could reinforce the transparency and validity of other qualitative methods. The focus of this chapter lies in explaining how Q-method works, so that readers are equipped to set up their own Q-studies. It is based on prior literature and ongoing reflections being held by Q-methodologists online.

View analysis of personal information leakage and privacy protection in big data era—based on Q method

PurposeIn the era of big data, people are more likely to pay attention to privacy protection with facing the risk of personal information leakage while enjoying the convenience brought by big data technology. Furthermore, people’s views on personal information leakage and privacy protection are varied, playing an important role in the legal process of personal information protection. Therefore, this paper aims to propose a semi-qualitative method based framework to reveal the subjective patterns about information leakage and privacy protection and further provide practical implications for interested party.Design/methodology/approachQ method is a semi-qualitative methodology which is designed for identifying typologies of perspectives. In order to have a comprehensive understanding of users’ viewpoints, this study incorporates LDA & TextRank method and other information extraction technologies to capture the statements from large-scale literature, app reviews, typical cases and survey interviews, which could be regarded as the resource of the viewpoints.FindingsBy adopting the Q method that aims for studying subjective thought patterns to identify users’ potential views, the authors have identified three categories of stakeholders’ subjectivities: macro-policy sensitive, trade-offs and personal information sensitive, each of which perceives different risk and affordance of information leakage and importance and urgency of privacy protection. All of the subjectivities of the respondents reflect the awareness of the issue of information leakage, that is, the interested parties like social network sites are unable to protect their full personal information, while reflecting varied resistance and susceptibility of disclosing personal information for big data technology applications.Originality/valueThe findings of this study provide an overview of the subjective patterns on the information leakage issue. Being the first to incorporate the Q method to study the views of personal information leakage and privacy protection, the research not only broadens the application field of the Q method but also enriches the research methods for personal information protection. Besides, the proposed LDA & TextRank method in this paper alleviates the limitation of statements resource in the Q method.

Chinese Visitors in the Tourist Bubble: Exploring the Seoul Destination Experience Using Q Method

With the acceleration of globalization, international tourism has developed rapidly, especially in Seoul. Tourist bubble phenomenon appears with the development of international tourism. The term “tourist bubble” was originally proposed by Cohen, which conceptualized as the “protective walls” to reduce strangeness when tourist encounter a new environment and create a psychological space. The tourist bubble comprises a concentrated geographic area of tourist-oriented facilities and attractions, which is separated from its surrounding environment by spatially or psychologically created boundaries. Many studies focus more on the classification and formation process of the tourist bubble, but rarely involve tourists’ perception of tourist bubbles and the destination experience of tourists in the tourist bubble. Therefore, in this paper, it used Chinese tourists traveling in the tourist bubble of Seoul as a case to analyze the perception of international tourists on the tourist bubble phenomenon and the destination experience of tourists. It classified 5 types of Chinese tourists to identify their experience in Seoul. By using Q methodology, a technique designed for the systematic study of subjectivity in terms of beliefs, opinions, and attitudes, to find the subjectivity of Chinese tourists in the tourist bubble. It aims to provide reasonable tourism planning suggestions that how to make use of the tourist bubble phenomenon to make better tourism marketing for the Korean international tourism market.