- P-ISSN2287-1608
- E-ISSN2287-1616
- KCI
ISSN : 2287-1608
Vol.3 No.2
Abstract
Modern education, with special reference to higher education (HE), is far taken out of the traditional meaning of education. A number of business features have infiltrated these institutions of HE where students assume the place of a customer. In the present business scenario customer relationship management (CRM) technology assumes an important role in managing customers. Therefore a relevant question would be to know whether educational institutions need to implement this technology to manage their constituent relationships. This paper makes an attempt to evaluate studies on commercial features of a modern educational system and then present the findings of a study conducted to know the relevance of CRM Technology in HE. An evaluation is also made to know the awareness of the concept of CRM among the educators. The findings show that the educators’ awareness of CRM strategies is good, of CRM concepts is poor and of practice is average. Further, an overwhelming majority of the respondents felt that CRM is relevant for educational institutions in the present scenario.
Abstract
This article aims to examine the achievement and limitation of adaptation of supply chain management (SCM) to IT human resource development (HRD) in Korea and to derive the implication of the Korean experience to other countries. In late 1990s, the IT New Deal Policy and the quantitative expansion of IT HR were introduced. Since mid-2000s, there has been much innovation in IT products as well as increased demand of highly qualified IT experts. The SCM in IT HRD was introduced in 2004 and continuously developed more. Since the late 2000s, IT convergence expanded to traditional industries and the new IT-based-industries were created in Korea. In this regard, Korea established the Seoul Accord as an international IT engineering education accreditation system in 2008. In response to the paradigm change, in 2011, the Korean government developed TOPCIT, which is a kind of competency test for evaluating IT competency.
Abstract
This study aims to analyze the valuation of technology firms in the stock market to answer how before-market entities should be valuated. This study analyzes 230 market reports of 2012 for technology firms in the KOSDAQ under several hypotheses. The results are as follows: 90% used the 3 multiples methods consisting of PER multiples with 80%, PBR multiples 8.7% and EBITDA multiples 1.7%. The average of PER multiples was 15 with the range of 6.9 to 83. That of PBR multiples is 2.27. Forecasting for cash flow is not applied over 4 years, but mainly 2-3 years. The accuracy of forecasting was 18.8%, 34.4% and 8% according to the different definitions. No differences were found in the accuracy of forecasting between valuation methods, between the industries having more intangible assets and the industries having less, and between startups and general companies and between ages and listed ages.
Abstract
This study analyzes the factors on the determinants of research productivity. In addition, this study uncovers the relationships between research productivity and various explanatory variables, and between explanatory variables. As for research productivity, 3 indices were used such as the number of papers, patents, and a combination of them. The data is the 3-year average from 2010-2012 by 1,383 researchers from 6 disciplines such as physics, chemistry, biology, mechanical engineering, electricity and electronics, and chemical engineering, reported to the National Research Foundation of Korea. Personal factors such as sex, age, academic rank and location of affiliation show the group difference for productivity. In addition, most resource factors such as the number of graduate students and research funds showed the same result with personal factors. As for the determinants, master and doctoral students and government funds are the most powerful factors for research productivity, but industry funds for patent and overall productivity.
Abstract
This paper empirically establishes the role played by the ecosystem related parameters in the emergence and growth of high technology start-up clusters in India. It is mainly based on secondary data from six major start-up hubs in India during the period 2005-2013. Our results throw up several interesting findings. First of all, we find that traditional infrastructure related factors or robust macroeconomic situation in general are not the most important drivers. What really seem to matter are the specific start-up ecosystem related factors – such as the Internet penetration, volume of deal flow, availability of VC funding and a pre-existing critical mass of relevant high technology businesses and skill-sets. Above all, our study points out that high economic growth alone will not automatically lead to spillovers in the form of a vibrant start-up ecosystem. Rather it has to be a product of conscious and concerted policy efforts at all levels that directly address the main challenges faced by the early-stage start-ups.
Abstract
Knowledge, technology and information have special characteristics different from the ones of normal consumer products and services. Especially the value of such information varies according to external elements such as the provided environment, their method of utilization, and the level and purpose, etc. of the user. In this study, the indicators of information customer value are developed and measured to enhance customer-based values with efforts for making new customers and maintaining existing customers. The result is as follows: 14 customer value indicators were developed. Among the indicators, value gained versus effort, reduced time for research idea investigation and savings in time searching for equipment, and tools and materials got the highest score, which means that time-saving effects were the most important. The field study of this paper was conducted from information users in the field of national R&D, and thus future studies could be conducted in various industries in many countries to attain generalized results.