1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

In this innovative approach to the practice of social science, Charles Ragin explores the use of fuzzy sets to bridge the divide between quantitative and qualitative methods. Paradoxically, the fuzzy set is a powerful tool because it replaces an unwieldy, "fuzzy" instrument—the variable, which establishes only the positions of cases relative to each other, with a precise one—degree of membership in a well-defined set. Ragin argues that fuzzy sets allow a far richer dialogue between ideas and evidence in social research than previously possible. They let quantitative researchers abandon "homogenizing assumptions" about cases and causes, they extend diversity-oriented research strategies, and they provide a powerful connection between theory and data analysis. Most important, fuzzy sets can be carefully tailored to fit evolving theoretical concepts, sharpening quantitative tools with in-depth knowledge gained through qualitative, case-oriented inquiry. This book will revolutionize research methods not only in sociology, political science, and anthropology but in any field of inquiry dealing with complex patterns of causation.

Fuzzy-Set Social Science

本文对国际科学计量学杂志《Ｓｃｉｅｎｔｏｍｅｔｒｉｃｓ》１９７９－１９９１年的研究论文内容、栏目、作者及国别和编委及国别作了计量分析，揭示出科学计量学研究的重点、活动的中心及发展趋势，说明了学科带头人在发展科学计量学这门新兴学科中的作用。

国际刊物《Scientometrics》文献计量研究

The purpose of this research was to explore teaching and learning when mobile computing devices, such as cellphones and smartphones, were implemented in higher education. This paper presents a portion of the findings on students' perceptions of learning with mobile computing devices and the roles social media played. This qualitative research study focused on students from three universities across the US. The students' teachers had been integrating mobile computing devices, such as cellphones and smartphones, into their courses for at least two semesters. Data were collected through student focus group interviews. Two specific themes emerged from the interview data: (a) advantages of mobile computing devices for student learning and (b) frustrations from learning with mobile computing devices. Mobile computing devices and the use of social media created opportunities for interaction, provided opportunities for collaboration, as well as allowed students to engage in content creation and communication using social media and Web 2.0 tools with the assistance of constant connectivity.

Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones & social media

Redesigning Social Inquiry Fuzzy Sets And Beyond

Even if m-learning is spreading rapidly in many regions of the world, research addressing the driving factors of m-learning adoption is in short supply Built on the Technology Acceptance Model, this paper proposes a hypothesized model of m-learning adoption Employing structural equation modeling technology, the model was assessed based on the data collected from 230 participants using a survey questionnaire Results indicate that perceived near-term/long-term usefulness and personal innovativeness have significant influence on m-learning adoption intention, while perceived long-term usefulness significantly affects the perceived near-term usefulness Personal innovativeness is a predictor of both the perceived ease of use and perceived long-term usefulness as well Of all variables, the perceived long-term usefulness contributes to the most influential predictor of m-learning adoption The model accounts for approximately 608% of the variance of behavioural intention The results indicted that offing high-quality contents complying with students' future targets is key to the success of m-learning in China Both theoretical and practical implications are discussed

Factors driving the adoption of m-learning: An empirical study

A multitude of evidences show that impulse purchase is prevalent online, yet relatively limited knowledge is available on this phenomenon. The study borrows marketing wisdom to information systems space to quantify how the website cues (products availability, website ease of use and visual appeal) affect personality traits (instant gratification, normative evaluation and impulsiveness) to urge the impulse purchase online. Structural equation modeling technologies are employed to evaluate the research model based on a survey questionnaire. The results show that personality factors of instant gratification, normative evaluation and impulsiveness are key determinants of urge to buy impulsively, while perceived website cues of visual appeal, website ease of use and product availability are important precursors. Through combining marketing and IS wisdom, a number of new insights are offered which enrich our understanding on the determinants of online impulse purchase decision as well as on how a proper IS design alters consumer shopping experience to engender more online impulse purchase.

Website attributes in urging online impulse purchase: An empirical investigation on consumer perceptions

Purpose – The purpose of this paper is to examine and quantify how various uncertainties result in different perceived risk dimensions that hinder mobile payment (m-payment) acceptance. Design/methodology/approach – An uncertainty-risk-value framework was proposed based on perceived risk theory, prospect theory, and perceived value theory. Structural equation modeling method was used to test the research model. Findings – Perceived information asymmetry, perceived technology uncertainty, perceived regulatory uncertainty, and perceived service intangibility are confirmed as the main determinants of perceived risk, while perceived performance risk, perceived financial risk, and perceived privacy risk were found to have strong negative effects on perceived value and acceptance intention. Practical implications – The findings may help businesses and policy makers better understand the sources of perceived risk and help support the development of appropriate strategies to mitigate the risk concerns consumers h...

Understanding perceived risks in mobile payment acceptance

– The purpose of this research is to examine the effect of flow experience on mobile social networking service (SNS) users' loyalty., – Based on 305 valid responses collected from a survey questionnaire, structural equation modeling (SEM) technology was employed to examine the research model., – The results show that both information quality and system quality significantly affect users' trust and flow experiences, which further determine their loyalty. The results indicate that flow experience is the strongest determinant of users' loyalty., – Mobile SNS providers need to consider user experience when seeking users' loyalty. They should enhance information quality and system quality in order to improve user trust and flow experience., – Although much research has been conducted to explore the effects of extrinsic motivations, such as perceived usefulness, on mobile commerce user behavior, the effect of intrinsic motivations, such as flow experience, is seldom tested. This research found the effect of flow experience on mobile SNS users' loyalty to be significant.

Yong Liu

Papers

Factors driving the adoption of m-learning: An empirical study

Website attributes in urging online impulse purchase: An empirical investigation on consumer perceptions

Understanding perceived risks in mobile payment acceptance

The effect of flow experience on mobile SNS users' loyalty

Exploring the impact of use context on mobile hedonic services adoption: An empirical study on mobile gaming in China