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Analyzing the trends of E-marketing from 2001 to 2010 with the use of bibliometrics and text mining

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... We then ran a series of bibliometric analyses in order to analyze trends in the data. Bibliometric analysis is an analytic technique that has been used by an increasing number of scholars to identify trends and clusters in the literature (Chabowski et al. 2013;Doh and Lucea 2013;Fetscherin et al. 2010;He 2013;He et al. 2012;Ramos-Rodriguez and Ruiz-Navarro 2004;Schildt et al. 2006). Although meta-analysis can also help researchers summarize a body of research, it is typically used as an attempt to reconcile fragmented results. ...
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This study provides an overview of the international strategic management literature from 2000 through 2013. By drawing from a sample of 736 articles, we employ bibliometric and text mining analyses in identifying 10 distinct subfields of international strategic management research. Our study serves as a resource for future research by shedding light on how trends in international strategic management research have evolved over time. The results of our analysis reveal a substantial increase in the volume of international strategic management articles published in high quality journals over this period of time. Specifically, our results demonstrate that certain subfields of international strategic management research, such as business strategy formulation, internal coordination, decision-making, corporate strategy implementation, international diversification, and national culture, are increasing in scholarly interest. However, other subfields of international strategic management research, such as political risk, corporate strategy formulation, business strategy implementation, and strategic alliances, have either stabilized or recently declined in scholarly interest. We also identify and report the most prominent theories employed within each subfield. We find that institutional theory, the resource-based view, organizational learning theory, social network theory, and the knowledge-based view have been the most frequently employed theories in the international strategic management literature.
... We then ran a series of bibliometric analyses in order to analyze trends in the data. Bibliometric analysis is an analytic technique that has been used by an increasing number of scholars to identify trends and clusters in the literature (Chabowski et al. 2013;Doh and Lucea 2013;Fetscherin et al. 2010;He 2013;He et al. 2012;Ramos-Rodriguez and Ruiz-Navarro 2004;Schildt et al. 2006). Although meta-analysis can also help researchers summarize a body of research, it is typically used as an attempt to reconcile fragmented results. ...
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This study provides an overview of the global strategy literature from 2000 to 2010. By drawing from a sample of 489 articles, we employ bibliometric and text mining analyses in identifying 10 distinct subfields of global strategy research. Our results reveal a substantial increase in the volume of global strategy articles published in high quality journals over this period of time. Specifically, our results demonstrate that certain subfields of global strategy research, such as political risk and international diversification, are of increasing scholarly interest. However, other subfields of global strategy research, such as business-level strategy implementation and decision making, have either leveled-off or declined in scholarly interest. We also identify theories that have been most frequently employed in the literature and report the most prominent theories employed in each subfield. Furthermore, our study serves as a resource for future research by shedding light on how trends in global strategy research have evolved over time.
... Some major applications of text mining include: clustering (Duan et al., 2007), information extraction (text summarization) and link analysis (Hung, 2012;He et al., 2012;Zhong et al., 2012). Currently, there are a wide range of tools that can be used for text mining and analysis, such as the SPSS Modeler (formerly Clementine), Leximancer, SAS Enterprise Miner and NVivo. ...
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Purpose – The existing mashup literature paid little attention to the actual adoption and diffusion of mashups in an organizational context. As more and more organizations are engaged in mashup initiatives, more research efforts focussing on the mashup use and adoption issues from the organizational perspective are needed to ensure that organizations can receive the maximum benefits from their mashup initiatives. Two studies are conducted to increase the understanding of the use and adoption issues with social media mashups. The paper aims at discussing these issues. Design/methodology/approach – The paper first used a text mining approach to analyze relevant posts on blogs and messages in a major online mashup forum in order to understand the current status of social media mashup as well as representative themes and issues with social media mashups in general. Subsequently, the paper reviewed a number of social media mashup sites created by higher education institutions (HEIs) in the USA. Findings – The paper identified some representative themes and issues with social media mashups in general. The paper also identified the approaches that were used to design the interface of social media mashup sites by HEIs. Based on the two studies, this paper provides recommendations and insights to guide social media mashup development and adoption in an organizational context. Originality value – This is the first article to discuss the use and adoption of social media mashups in organizational environments. This paper can be used as a starting point to motivate other researchers to further explore the diffusion of social media mashups in different industries. This paper also helps organizations improve their social media mashup initiatives.
... Hung (2012) used clustering analysis as an exploratory technique to examine e-learning literature and visualized patterns by grouping sources that share similar words, attribute values and coding rules. Some major applications of text mining include: automatic classification (clustering), information extraction (text summarization), and link analysis (He, Chee, Chong, & Rasnick, 2012;Hung, 2012;Perera, Kay, Koprinska, Yacef, & Zaiane, 2009). In particular, clustering analysis is a well-studied technique in data mining (Lin et al., 2009) and has the advantage of uncovering unanticipated trends, correlations, or patterns from data (Ananiadou, 2008;Chen & Liu, 2004). ...
Article
Many CBR systems have been developed in the past. However, currently many CBR systems are facing a sustainability issue such as outdated cases and stagnant case growth. Some CBR systems have fallen into disuse due to the lack of new cases, case update, user participation and user engagement. To encourage the use of CBR systems and give users better experience, CBR system developers need to come up with new ways to add new features and values to the CBR systems. The author proposes a framework to use text mining and Web 2.0 technologies to improve and enhance CBR systems for providing better user experience. Two case studies were conducted to evaluate the usefulness of text mining techniques and Web 2.0 technologies for enhancing a large scale CBR system. The results suggest that text mining and Web 2.0 are promising ways to bring additional values to CBR and they should be incorporated into the CBR design and development process for the benefit of CBR users.
... Some major applications of text mining include: clustering, information extraction (text summarization), and link analysis (He, Chee, Chong, & Rasnick, 2012;Hung, 2012;Ingvaldsen & Gulla, 2012;Wetzstein, Leitner, Rosenberg, Dustdar, & Leymann, 2011). In particular, clustering analysis is a well-studied technique in data mining (Lin, Hsieh, & Chuang, 2009) and has the advantage of uncovering unanticipated trends, correlations, or patterns from data (Ananiadou, 2008). ...
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