• Journal of Animal Science and Technology
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• v.45 no.1
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• pp.69-78
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• 2003

This experiment was carried out to evaluate the value of total mixed fermentation feeds(TMFF) as completely mixed ration and to observe the effect of various kinds of TMFF on the palatability, feed intake, and milk performance in Holstein cows. The dry matter (DM) content of TMFF used in the experiment was 23.98-28.42% range, and CP, TDN, ADF and NDF were 16.2${\sim}$19.2%, 58.3-65.1%, 34.4-39.6% and 46.9${\sim}$49.9% levels, respectively. The relative feed value (RFV) in rape-, alfalfa-, grass-, oat-, corn-TMFF groups were 138.6, 133.9, 116.5, 111.8, 111.4 and 108.1, respectively. Among these groups, RFV of rye-TMFF group was lowest. Dry matter disappearance(DMD) showed 0.8${\sim}$.9% to the all kinds of TMFF groups. The pH was 3.89${\sim}$.87 and $NH_3$-N concentration was 6.93-8.66 mg/$d\ell$. The acetic acid concentration in the raw material of TMFF showed low level of 0.19${\sim}$0.57%, lactic acid showed high level of 1.17${\sim}$3.21% and butyric acid was very high as 0.03${\sim}$0.32%. Therefore, these results provide evidence that the quality of TMFF was not so bad. In the daily fresh matter intake on the alfalfa-, grass-, rape-, corn-, oats- and rye-TMFF were showed 62.85, 60.48, 58.04, 57.11, 54.61 and 45.74 kg respectively. All TMFF showed high palatability as daily dry matter intake of 1.95 to 2.90% by body weight of experimental cows. Body condition score(BCS) was gradually increased in during 60 days of the experiment term. Average daily gain(ADG) showed about 140.0${\sim}$326.7g. In alfalfa-TMFF group, the ADG was higher than in the other groups (p<0.05). Also, the increase in BCS was observed in grass-TMFF group (3.07 to 3.34) and rye-TMFF group was decreased in 3.07 to 3.34 (p<0.05). The milk yield appropriately showed a range of 16.16${\sim}$18.95 kg in all groups. Among these groups, alfalfa-TMFF group was highest(P<0.05). Average milk fat contents showed high levels of 4.06${\sim}$4.79% and the level was high in order of rape-, grass-, corn-, alfalfa-, rye- and oats-TMFF. Milk protein was highest in forage-TMFF and level of lactose in milk was approximately 4.56% in overall groups. Solid non fat(SNF) and total solid(TS) contents were 8.75% and 12.8%, respectively. However, milk composition was not significantly affected by TMFF.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.