• 마케팅과학연구
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• 제19권3호
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• pp.17-27
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• 2009

典型的价格促销是指降低一定数量产品的价格或以相同的价 格获得更多数量的产品, 从而增加价值和创造经济的激励购买. 价格促销经常用来鼓励没有消费过产品或服务的用户试用产品或服务. 因此, 理解价格促销对那些从来没有使用过促销品牌的消费者的此品牌质量认知的影响是很重要的. 然而, 如果消费者通过价格促销获得的产品的质量不好, 促销可能达不到用经济的刺激方法来增加销售的效果. 相反则有可能发生. 具体来说, 通过价格促销消费者产生低的质量的认知会削弱经济的和心理上的激励, 减少购买的可能性. 因此, 对市场营销人员来说理解品牌的价格促销信息如何影响消费者对此品牌的质量的不良认知是非常重要的. 先前的有关价格促销对质量认知的影响的研究有不一致的解释. 一些是关注价格促销对消费者认知的不利影响. 但是其他的研究显示价格促销并没有提高消费者对品牌的不良认知. 之前的研究发现这些不一致的结果和价格促销曝光的时机以及相关的试验得出的质量评估有关. 而且, 消费者是否经历过产品促销都可能会调节这些影响. 一些研究把产品类别的不同作为基本的因素. 本研究的目的是探讨在不同的情况下, 价格促销信息对消费者的不良的质量认知产生的影响. 作者控制了促销曝光的时机, 过去的各种促销形式以及信息发布的方式. 与以往的研究不同, 作者通过控制以前个人使用此产品的经验的潜在调节作用来测试事先设定限制的价格促销的影响. 这样的操作可以解决相关的有可能产生的争议. 这种方法对实际工作方面也是有意义的. 价格促销不仅适用于已存在的目标消费者, 而且可以鼓励没有使用过产品和服务的消费者尝试此产品或服务. 因此, 对市场营销人员来说理解品牌的价格促销信息如何影响消费者对此品牌的质量的不良认知是非常重要的. 如果没有使用过这个品牌的消费者通过价格促销获得的产品的质量不好, 促销可能达不到用经济的刺激方法来增加销售的效果. 相反则有可能发生. 另外, 如果价格促销结束, 购买了这个产品的消费者可能会出现明显的减少再购买行为. 通过文献回顾, 假设1用来探讨消费者通过过去的价格促销获得的质量认知的调节作用. 消费者对没有使用过的品牌的价格促销而产生的质量认知的影响会被此品牌过去的价格促销活动所调节. 换句话说, 消费者会对没有进行过价格促销的没有使用过的品牌产生不良的质量认知. 假设2-1:未使用过的品牌进行首次价格促销的时候, 价格促销的信息发布的方式将影响价格促销的成败. 假设2-2:消费者越不在意价格促销的原因, 越容易对产品的质量产生不良的认知. 通过测试1, 简要地解释了产品和品牌在提供四种价格促销形式之前并解释说明了每种价格促销形式. WAVEX这个虚拟品牌的质量的认知被评估为7. 网球拍被选中的原因是由于选定的产品组必须过去几乎没有价格促销活动来消除促销的平均次数对价格促销信息的影响, 正如Raghubir和Corfman(1999)所提出的. 测试2也用网球拍作为产品组, 主持测试2的管理者与测试1相同. 随着测试1, 选择了对产品组熟悉而对产品不熟悉的受访者. 每个受访者被分配到代表WAVEX价格促销的两种不同信息发布方式的两组中的一组. 在评估WAVEX的质量认知为7以前, 受访者看了每个促销信息. 不熟悉的实验品牌的价格促销对消费者的质量认知的影响被证明为会被以前有过或没有价格促销活动所调节. 与过去的促销行为一致是使品牌评估变得更糟的不良影响的重要变量. 如果此品牌从未进行过价格促销, 价格促销活动会对消费者的质量认知产生不良的影响. 第二, 不熟悉的品牌进行首次价格促销时, 促销信息的发布方式会影响公司促销的成败. 当消费者进行性格归因和情境归因的比较时, 质量认知的不良影响会更大. 与先前主要关注具有或不具有情境/性格归因中良好或不良的动机的研究不同, 本研究的焦点是检验如果公司提出了具有说服性的理由, 即使消费者在价格促销行为中有性格归因, 情境归因也可以被推断出的事实. 这种方法, 在学术方面取得了很大的成果, 意义在于它运用非数学的问题来解释固定和调整过程而不像以前的研究大部分是把它用于数学问题来解释. 换句话说, 根据基本属性错误, 有很大的倾向去性格地归因其他的行为. 当这种情况出现在价格促销时, 我们可以推断出消费者很有可能性格地归因公司的价格促销行为. 反而, 即使在这种情况下, 公司可以调整消费者的锚定性来降低性格归因的可能性. 另外, 不像多数对价格促销的长/短期影响的以往的研究, 只考虑价格促销对消费者的购买行为影响, 本 研究测试对质量认知的影响, 一个影响消费者购买行为的因素. 这些结果在实际工作方面有重要启示. 本研究的结果可以作为新产品有效的提供促销信息的指南. 如果品牌要避免错误的暗示, 比如在施行价格促销战略时被认为是产品的质量不好, 一定要为促销提供清晰合理的理由. 尤其是对那些以前没有进行过价格促销活动的公司来说, 提供明确的理由尤其重要. 不一致的行为可以导致消费者的不信任和焦虑. 这也是无止境的价格战的风险的重要因素之一. 没有事先通知的价格促销会使消费者怀疑, 但不会影响市场份额.

• Asia pacific journal of information systems
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• 제24권4호
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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.