شبکه های یادگیری سازمانی که می تواند بهره وری شرکت های مشاوره IT را افزایش دهد. یک مطالعه موردی برای مشاوران ERP
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|13400||2014||11 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 41, Issue 1, January 2014, Pages 126–136
This paper considers the use of social learning networks to increase the productivity of IT consulting companies. We advocate that using a carefully designed social learning network can reduce the learning time for enterprise software developers and consultants. By viewing learning as a social act, a consulting company can increase its productivity. Increased productivity is based on hastening the learning process. The focus of this paper is to identify the ways in which social networks catalyze the process of knowledge sharing in order to increase the productivity in the enterprise resource planning (ERP) consulting sector. We present a set of detailed practical results that were obtained from experiments with an original knowledge sharing method that was applied to training young software developers to enable them to work for some of the world’s most demanding IT companies. The experimental data were collected from 2004 to 2011 during 12 training sessions conducted by an IBM partner in conjunction with the Computer Science Department of a large Eastern European University. The main results of this study were: (1) designed a learning community that reduced the time needed to insert junior consultants into ERP projects; and (2) statistical data were generated that measured the increase in productivity that an ERP consulting company could obtain by employing organizational learning networks. We also discuss the positive impacts of social networks that can be established between private companies and universities.
There has been substantial research in the area of organizational learning. By definition, organizational learning is the acquisition of information knowledge and skills by individuals (Argyris and Schon, 1995 and Easterby-Smith and Lyles, 2011). Organizational learning networks have been previously studied with regard to their relationships with the productivity of IT consulting companies. Skerlavaj, Dimovski, Mrvar, and Parhor (2010) found that social learning networks had a positive impact inside IT consulting companies, including those involved in enterprise resource planning (ERP) consulting. One of the most prominent researchers in this field claimed that the only sustainable competitive advantage for a company was its ability to learn faster than its competitors (Geus, 1988 and Kumar et al., 2011). Learning is crucial for an IT consulting company because it only sells knowledge and, thus, it has to be better than its competitors. A consulting company’s productivity is not always easily defined. Nachum (1999) observed that productivity models developed in the manufacturing industry did not apply to professional companies. These models depend on the particular type of service that is being offered. The main issue that an IT consulting company must solve when it comes to its productivity is the considerable time needed to insert a consultant into a project that is unknown to that consultant. In terms of ERP software packages, the time that a person must spend learning before (s)he can start working autonomously is much longer that in other industries. According to Lazowska (2011), who cites a report from the US Bureau of Labor Statistics, we are currently facing a shortage of computer specialists that will continue to grow until at least 2018. In the US alone, from 2008 to 2018 the job market will be in demand for an extra 1.4 million new computer specialists. This is not a new situation, as it has been occurring for many years. The US President’s Council of Advisors on Science & Technology stated in December 2010 that “all indicators – all historical data, and all projections – argue that (computer science) is the dominant factor in America’s science and technology employment” (Lazowska, 2011). This shortage of skills also applies to ERP consulting companies, as ERP has been a hot sector since the mid 1990s. This paper was written based on the assumption that the productivity of a consulting company in an area with a shortage of resources is directly proportional to the number of new junior consultants that it manages to successfully insert into projects over a certain period of time. Reducing the time needed to train a junior consultant in order to become stand-alone is crucial for increasing a consulting company’s productivity. Additional details regarding the interpretation of productivity and statistical data that confirm this assumption are provided in the following chapters. This paper has four main parts: (1) background, in which the problem is formulated in detail; (2) the learning model and the proposed social learning network; (3) the learning process that was conducted and the statistical data that were obtained; and (4) a discussion on productivity gains and answers to some questions and criticisms.
نتیجه گیری انگلیسی
The first important conclusion is that using a carefully designed social learning network reduces the learning time in the some ERP technologies. By choosing the design presented here, this reduction in training time can be highly significant from 24 months, which is the ‘‘classical’’ industry standard, to 6–7 months. This is an impor- tant means to bridge the gap between the level of the average uni- versity graduate and the skills demanded by international consulting companies. A second conclusion is that the efficiency of this process is greatly influenced by factors that can be controlled by the organiz- ers. Incentives are very important in this process and choosing them carefully has a major impact on the efficiency of the process. Seductive prizes appear to have the greatest impact on efficiency. A possible explanation for this is that learning occurs by interacting within a social network and such prizes stimulate the creation of networks. These results can be used to design strategies for accelerating the educational process of young software developers who are needed in today’s rapidly growing knowledge-based economy. We are now in discussions with many large companies that are interested in creating teams of skilled software experts in Eastern Europe. Other investigators who want to use this method are advised to pay attention to the participants’ ages, the maturity of the com- puter science department of the university they are partnering with, and ensure that there is active support by consulting compa- nies where the students will acquire their episodic knowledge. The sponsorship of high level management is mandatory for success- fully creating a social learning network. A social learning networkis like a living organism, as it needs to be cared for on a daily basis to ensure its proper growth. Regarding future research, we intend to use different motiva- tional factors and test the efficiency of these sessions. Another area of interest is to use a tool for mapping the links that are created be- tween the members of the learning community. This tool should track the messages exchanged by the members and identify the relationships among them