• Korean journal of communication and information
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• v.32
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• pp.49-73
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• 2006

During the past decades, public opinion polls have become an ubiquitous tool for probing the complexity of people's beliefs and attitudes on a wide variety of issues. Especially since the late 1970s, the use of polls by news organizations has increased dramatically. Along with the proliferation of traditional polls, in the past few years pollsters and news organizations have come to recognize the advantages of online polls. Increasingly there has been more effort to take the pulse of the public through the Internet. With the Internet's rapid growth during the past years, advocates of online polling often emphasize the relative advantages over traditional polls. Researchers from Harris Black International Ltd., for example, argue that "Internet polling is less expensive and faster and offers higher response rates than telephone surveys." Moreover, since many of the newer online polls draw respondents from large databases of registered Internet users, results of online polls have become more balanced. A series of Harris Black online polls conducted during the 1998 gubernatorial and senatorial elections, for example, has accurately projected the winners in 21 of the 22 races it tracked. Many researchers, however, severely criticize online polls for not being representative of the larger population. Despite the often enormous number of participants, Internet users who participate in online polls tend to be younger, better educated and more affluent than the general population. As Traugott pointed out, the people polled in Internet surveys are a "self selected" group, and thus "have volunteered to be part of the test sample, which could mean they are more comfortable with technology, more informed about news and events ... than Americans who aren't online." The fact that users of online polls are self selected and demographically very different from Americans who have no access to the Internet is likely to influence the estimates of what the majority of people think about social or political issues. One of the goals of this study is therefore to analyze whether people perceive traditional and online public opinion polls differently. While most people might not differentiate sufficiently between traditional random sample polls and non representative online polls, some audiences might perceive online polls as more useful and representative. Since most online polls allow some form of direct participation, mostly in the form of an instant vote by mouse click, and often present their findings based on huge numbers of respondents, consumers of these polls might perceive them as more accurate, representative or reliable than traditional random sample polls. If that is true, perceptions of public opinion in society could be significantly distorted for those who rely on or participate in online polls. In addition to investigating how people perceive random sample and online polls, this study focuses on the perceived impact of public opinion polls. Similar to these past studies, which focused on how public opinion polls can influence the perception of mass opinion, this study will analyze how people perceive the effects of polls on themselves and other people. This interest springs from prior studies of the "third person effect," which have found that people often tend to perceive that persuasive communications exert a stronger influence on others than on themselves. While most studies concerned with the political effects of public opinion polls show that exit polls and early reporting of election returns have only weak or no effects on the outcome of election campaigns, some empirical findings suggest that exposure to polls can move people's opinions both toward and away from perceived majority opinion. Thus, if people indeed believe that polls influence others more than themselves, perceptions of majority opinion could be significantly altered because people might anticipate that others will react more strongly to poll results.

• 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.