International Journal of Information Management 

Abstract: PART ONE: CONCEPTUAL ISSUES IN THE USE OF QUALITATIVE METHODS The Nature of Qualitative Inquiry Strategic Themes in Qualitative Methods Variety in Qualitative Inquiry Theoretical Orientations Particularly Appropriate Qualitative Applications PART TWO: QUALITATIVE DESIGNS AND DATA COLLECTION Designing Qualitative Studies Fieldwork Strategies and Observation Methods Qualitative Interviewing PART THREE: ANALYSIS, INTERPRETATION, AND REPORTING Qualitative Analysis and Interpretation Enhancing the Quality and Credibility of Qualitative Analysis

Abstract: We define what is meant by big data.We review analytics techniques for text, audio, video, and social media data.We make the case for new statistical techniques for big data.We highlight the expected future developments in big data analytics. Size is the first, and at times, the only dimension that leaps out at the mention of big data. This paper attempts to offer a broader definition of big data that captures its other unique and defining characteristics. The rapid evolution and adoption of big data by industry has leapfrogged the discourse to popular outlets, forcing the academic press to catch up. Academic journals in numerous disciplines, which will benefit from a relevant discussion of big data, have yet to cover the topic. This paper presents a consolidated description of big data by integrating definitions from practitioners and academics. The paper's primary focus is on the analytic methods used for big data. A particular distinguishing feature of this paper is its focus on analytics related to unstructured data, which constitute 95% of big data. This paper highlights the need to develop appropriate and efficient analytical methods to leverage massive volumes of heterogeneous data in unstructured text, audio, and video formats. This paper also reinforces the need to devise new tools for predictive analytics for structured big data. The statistical methods in practice were devised to infer from sample data. The heterogeneity, noise, and the massive size of structured big data calls for developing computationally efficient algorithms that may avoid big data pitfalls, such as spurious correlation.

Abstract: The growing popularity of the Internet has resulted in exciting opportunities for companies to reach out for customers with very little additional costs In order to communicate with the potential customers through WWW effectively, a well-designed Web page is needed Yet, the factors that affect customer's perception about the acceptance of a Web site are unclear This paper addresses why users accept or reject a Web site and how user's acceptance is affected by the features (ie information quality of a Web site, response time and system accessibility) provided by a Web site A study with 139 users of a Web site was conducted to test the hypothesised model The results showed that the technology acceptence model (TAM) fully mediated the usage behaviour even in the Internet environment, accounting for 64% of the variance in usage Furthermore, response time of a Web site is an important factor in affecting the user's beliefs of such a Web site This showed that Web page providers not only have to make the content informative and timely, but they also need to design a speedy Web page by not putting in unnecessary pictorial data as it might jeopardise the display time

Abstract: With the rapid development of mobile technology and large usage rates of mobile phones, mobile instant message (MIM) services have been widely adopted in China. Although previous studies on the adoption of mobile services are quite extensive, few focus on customer satisfaction and loyalty to MIM in China. In this study, we examine the determinants of customer satisfaction and loyalty. The findings confirm that trust, perceived service quality, perceived customer value, including functional value and emotional value, contribute to generating customer satisfaction with MIM. The results also show that trust, customer satisfaction and switching cost directly enhance customer loyalty. Additionally, this study finds that age, gender, and usage time have moderating effects. Finally, implications for the marketing of MIM are discussed.

Abstract: Educational establishments continue to seek opportunities to rationalize the way they manage their resources. The economic crisis that befell the world following the near collapse of the global financial system and the subsequent bailouts of local banks with billions of tax payers' money will continue to affect educational establishments that are likely to discover that governments will have less money than before to invest in them. It is argued in this article that cloud computing is likely to be one of those opportunities sought by the cash-strapped educational establishments in these difficult times and could prove to be of immense benefit (and empowering in some situations) to them due to its flexibility and pay-as-you-go cost structure. Cloud computing is an emerging new computing paradigm for delivering computing services. This computing approach relies on a number of existing technologies, e.g., the Internet, virtualization, grid computing, Web services, etc. The provision of this service in a pay-as-you-go way through (largely) the popular medium of the Internet gives this service a new distinctiveness. In this article, some aspects of this distinctiveness will be highlighted and some light will be shed on the current concerns that might be preventing some organizations from adopting it.