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Knowledge extraction from a large on-line survey: a case study for a higher education corporate marketing

机译:大型在线调查中的知识提取:以高等教育公司营销为例

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For a higher education public institution, young in relative terms, featuring local competition with another private and both long-established and reputed one, it is of great importance to become a reference university institution to be better known and felt with identification in the society it belongs to and ultimately to reach a good position within the European Higher Education Area. These considerations have made the university governors setting up the objective of achieving an adequate management of the university institutional brand focused on its logo and on image promotion, leading to the establishment of a university shop as it is considered a highly adequate instrument for such promotion. In this context, an on-line survey is launched on three different kinds of members of the institution, resulting in a large data sample. Different kinds of variables are analysed through appropriate exploratory multivariate techniques (symmetrical methods) and regression-related techniques (non-symmetrical methods). An advocacy for such combination is given as a conclusion. The application of statistical techniques of data and text mining provides us with empirical insights about the institution members' perceptions and helps us to extract some facts valuable to establish policies that would improve the corporate identity and the success of the corporate shop.
机译:对于相对而言年轻的,具有本地竞争优势且相对长期存在且久负盛名的一所私立高等教育机构而言,成为一所在社会上被人们更好地认识和认同的参考大学机构至关重要。属于欧洲高等教育区并最终在欧洲高等教育区中占据良好位置。这些考虑因素使大学管理者设定了目标,即以徽标和形象推广为重点,实现对大学机构品牌的适当管理,从而建立了一家大学商店,因为它被认为是进行这种推广的充分手段。在这种情况下,对机构的三种不同成员进行了在线调查,从而产生了大量的数据样本。通过适当的探索性多元技术(对称方法)和回归相关技术(非对称方法)分析了不同种类的变量。结论是对这种结合的提倡。数据和文本挖掘的统计技术的应用为我们提供了有关机构成员看法的经验性见解,并帮助我们提取了一些有价值的事实,这些事实对于建立可以改善企业形象和企业成功的政策很有帮助。

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