• Title/Summary/Keyword: Cognitive inference

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The Effects of Intention Inferences on Scarcity Effect: Moderating Effect of Scarcity Type, Scarcity Depth (소비자의 기업의도 추론이 희소성 효과에 미치는 영향: 수량한정 유형과 폭의 조절효과)

  • Park, Jong-Chul;Na, June-Hee
    • Journal of Global Scholars of Marketing Science
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    • v.18 no.4
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    • pp.195-215
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    • 2008
  • The scarcity is pervasive aspect of human life and is a fundamental precondition of economic behavior of consumers. Also, the effect of scarcity message is a power social influence principle used by marketers to increase the subjective desirability of products. Because valuable objects are often scare, consumers tend to infer the scarce objects are valuable. Marketers often do base promotional appeals on the principle of scarcity to increase the subjective desirability their products among consumers. Specially, advertisers and retailers often promote their products using restrictions. These restriction act to constraint consumers' ability th take advantage of the promotion and can assume several forms. For example, some promotions are advertised as limited time offers, while others limit the quantity that can be bought at the deal price by employing the statements such as 'limit one per consumer,' 'limit 5 per customer,' 'limited products for special commemoration celebration,' Some retailers use statements extensively. A recent weekly flyer by a prominent retailer limited purchase quantities on 50% of the specials advertised on front page. When consumers saw these phrase, they often infer value from the product that has limited availability or is promoted as being scarce. But, the past researchers explored a direct relationship between the purchase quantity and time limit on deal purchase intention. They also don't explored that all restriction message are not created equal. Namely, we thought that different restrictions signal deal value in different ways or different mechanism. Consumers appear to perceive that time limits are used to attract consumers to the brand, while quantity limits are necessary to reduce stockpiling. This suggests other possible differences across restrictions. For example, quantity limits could imply product quality (i.e., this product at this price is so good that purchases must be limited). In contrast, purchase preconditions force the consumer to spend a certain amount to qualify for the deal, which suggests that inferences about the absolute quality of the promoted item would decline from purchase limits (highest quality) to time limits to purchase preconditions (lowest quality). This might be expected to be particularly true for unfamiliar brands. However, a critical but elusive issue in scarcity message research is the impacts of a inferred motives on the promoted scarcity message. The past researchers not explored possibility of inferred motives on the scarcity message context. Despite various type to the quantity limits message, they didn't separated scarcity message among the quantity limits. Therefore, we apply a stricter definition of scarcity message(i.e. quantity limits) and consider scarcity message type(general scarcity message vs. special scarcity message), scarcity depth(high vs. low). The purpose of this study is to examine the effect of the scarcity message on the consumer's purchase intension. Specifically, we investigate the effect of general versus special scarcity messages on the consumer's purchase intention using the level of the scarcity depth as moderators. In other words, we postulates that the scarcity message type and scarcity depth play an essential moderating role in the relationship between the inferred motives and purchase intention. In other worlds, different from the past studies, we examine the interplay between the perceived motives and scarcity type, and between the perceived motives and scarcity depth. Both of these constructs have been examined in isolation, but a key question is whether they interact to produce an effect in reaction to the scarcity message type or scarcity depth increase. The perceived motive Inference behind the scarcity message will have important impact on consumers' reactions to the degree of scarcity depth increase. In relation ti this general question, we investigate the following specific issues. First, does consumers' inferred motives weaken the positive relationship between the scarcity depth decrease and the consumers' purchase intention, and if so, how much does it attenuate this relationship? Second, we examine the interplay between the scarcity message type and the consumers' purchase intention in the context of the scarcity depth decrease. Third, we study whether scarcity message type and scarcity depth directly affect the consumers' purchase intention. For the answer of these questions, this research is composed of 2(intention inference: existence vs. nonexistence)${\times}2$(scarcity type: special vs. general)${\times}2$(scarcity depth: high vs. low) between subject designs. The results are summarized as follows. First, intention inference(inferred motive) is not significant on scarcity effect in case of special scarcity message. However, nonexistence of intention inference is more effective than existence of intention inference on purchase intention in case of general scarcity. Second, intention inference(inferred motive) is not significant on scarcity effect in case of low scarcity. However, nonexistence of intention inference is more effective than existence of intention inference on purchase intention in case of high scarcity. The results of this study will help managers to understand the relative importance among the type of the scarcity message and to make decisions in using their scarcity message. Finally, this article have several contribution. First, we have shown that restrictions server to activates a mental resource that is used to render a judgment regarding a promoted product. In the absence of other information, this resource appears to read to an inference of value. In the presence of other value related cue, however, either database(i.e., scarcity depth: high vs. low) or conceptual base(i.e.,, scarcity type special vs. general), the resource is used in conjunction with the other cues as a basis for judgment, leading to different effects across levels of these other value-related cues. Second, our results suggest that a restriction can affect consumer behavior through four possible routes: 1) the affective route, through making consumers feel irritated, 2) the cognitive making route, through making consumers infer motivation or attribution about promoted scarcity message, and 3) the economic route, through making the consumer lose an opportunity to stockpile at a low scarcity depth, or forcing him her to making additional purchases, lastly 4) informative route, through changing what consumer believe about the transaction. Third, as a note already, this results suggest that we should consider consumers' inferences of motives or attributions for the scarcity dept level and cognitive resources available in order to have a complete understanding the effects of quantity restriction message.

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Generation of Fuzzy Rules for Fuzzy Classification Systems (퍼지 식별 시스템을 위한 퍼지 규칙 생성)

  • Lee, Mal-Rey;Kim, Ki-Tae
    • Korean Journal of Cognitive Science
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    • v.6 no.3
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    • pp.25-40
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    • 1995
  • This paper proposes a generating method of fuzzy rules by genetic and descent method (GAGDM),and its applied to classification problems.The number of inference rules and the shapes of membership function in the antecedent part are detemined by applying the genetic algorithm,and the real numbers of the consequent parts are derived by using the descent method.The aim of the proposed method is to generation a minmun set of fuzzy rules that can correctly classify all training patterns,and fiteness function of GA defined by the aim of th proposed method.Finally,in order to demonstrate the effectiveness of the present method,simulation results are shown.

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Solving the Monkey and Banana Problem Using DNA Computing (DNA 컴퓨팅을 이용한 원숭이와 바나나 문제 해결)

  • 박의준;이인희;장병탁
    • Korean Journal of Cognitive Science
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    • v.14 no.2
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    • pp.15-25
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    • 2003
  • The Monkey and Banana Problem is an example commonly used for illustrating simple problem solving. It can be solved by conventional approaches, but this requires a procedural aspect when inferences are processed, and this fact works as a limitation condition in solving complex problems. However, if we use DNA computing methods which are naturally able to realize massive parallel processing. the Monkey and Banana Problem can be solved effectively without weakening the fundamental aims above. In this paper, we design a method of representing the problem using DNA molecules, and show that various solutions are generated through computer-simulations based on the design. The simulation results are obviously interesting in that these are contrary to the fact that the Prolog program for the Monkey and Banana Problem, which was implemented from the conventional point of view, gives us only one optimal solution. That is, DNA computing overcomes the limitations of conventional approaches.

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A Genetic Algorithm-based Construction Mechanism for FCM and Its Empirical Analysis of Decision Support Performance : Emphasis on Solving Corporate Software Sales Problem (유전자 알고리즘을 이용한 퍼지인식도 생성 메커니즘의 의사결정 효과성에 관한 실증연구 : 기업용 소프트웨어 판매 문제를 중심으로)

  • Chung, Nam-Ho;Lee, Nam-Ho;Lee, Kun-Chang
    • Korean Management Science Review
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    • v.24 no.2
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    • pp.157-176
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    • 2007
  • Fuzzy cognitive map(FCM) has long been used as an effective way of constructing the human's decision making process explicitly. By taking advantage of this feature, FCM has been extensively used in providing what-if solutions to a wide variety of business decision making problems. In contrast, the goal-seeking analysis mechanism by using the FCM is rarely observed in literature, which remains a research void in the fields of FCM. In this sense, this study proposes a new type of the FCM-based goal-seeking analysis which is based on utilizing the genetic algorithm. Its main recipe lies in the fact that the what-if analysis as well as goal-seeking analysis are enabled very effectively by incorporating the genetic algorithm into the FCM-driven inference process. To prove the empirical validity of the proposed approach, valid questionnaires were gathered from a number of experts on software sales, and analyzed statistically. Results showed that the proposed approach is robust and significant.

Fuzzy Cognitive Map-Based A, pp.oach to Causal Knowledge Base Construction and Bi-Directional Inference Method -A, pp.ications to Stock Market Analysis- (퍼지인식도에 기초한 인과관계 지식베이스 구축과 양방향 추론방식에 관한 연구 -주식시장 분석에의 적용을 중심으로-)

  • 이건창;주석진;김현수
    • Journal of Intelligence and Information Systems
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    • v.1 no.1
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    • pp.1-22
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    • 1995
  • 본 연구에서 퍼지인식도(Fuzzy Cognitive Map) 개념을 기초로 하여 (1) 특정 문제영역에 대한 전문가의 인과관계 지식(causal knowledge)을 추출하는 알고리즘을 제시하고, (2) 이 알고리즘에 기초하여 작성된 해당 문제영역에 대한 여러 전문가들의 인과관계 지식을 계층별로 분해하여, (3) 해당 계층간의 양방향 추론이 가능한 추론메카니즘을 제시하고자 한다. 특정 문제영역에 있어서의 인과관계 지식이란 해당 문제를 구성하는 여러 개념간에 존재하는 인과관계를 표현한 지식을 의미한다. 이러한 인과관계 지식은 기존의 IF-THEN 형태의 규칙과는 달리 행렬형태로 표현되기 때문에 수학적인 연산이 가능하다. 특정 문제영역에 대한 전문가의 인과관계 지식을 추출하는 알고리즘은 집합연산에 의거하여 개발되었으며, 특히 상반된 의견을 보이는 전문가들의 의견을 통합하여 하나의 통합된 인과관계 지식베이스를 구축하는데 유용하다. 그러나, 주어진 문제가 복잡하여 다양한 개념들이 수반되면, 자연히 인과관계 지식베이스의 규모도 커지게 되므로 이를 다루는데 비효율성이 개재되기 마련이다. 따라서 이러한 비효율성을 해소하기 위하여 주어진 문제를 여러계측(Hierarchy)으로 분해하여, 해당 계층별로 인과관계 지식베이스를 구축하고 각 계층별 인과관계 지식베이스를 연결하여 추론하는 메카니즘을 개발하면 효과적인 추론이 가능하다. 이러한 계층별 분해는 행렬의 분해와 같은 개념으로도 이해될 수 있다는 특징이 있어 그 연산이 간단명료하다는 장점이 있다. 이와같이 분해된 인과관계 지식베이스는 계층간의 추론메카니즘을 통하여 서로 연결된다. 이를 위하여 본 연구에서는 상향 또는 하향방식이 추론이 가능한 양방향 추론방식을 제시하여 주식시장에서의 투자분석 문제에 적용하여 그 효율성을 검증하였다.

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The Analysis of Relationship between Science Contents and Cognitive Domain of Students in Elementary Schools Through Multiple Choice items of TIMSS 2011 (TIMSS 2011의 선다형 공개 문항을 통한 초등학생의 과학 내용영역과 인지영역의 관계 분석)

  • Jeon, Seongsoo;Park, Jong-Ho
    • Journal of The Korean Association For Science Education
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    • v.35 no.3
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    • pp.487-498
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    • 2015
  • This research is for acquiring implications to science education based on learner's characteristics by analyzing the relationship between contents on science learning and cognitive domain of students in elementary schools through TIMSS 2011-based academic achievement test. Forty one multiple choice items from by TIMSS 2011 were used on 317 primary school students, fourth to sixth grade, and according to grade and achievement level of research targets, test results were analyzed. With these data, the relationship between contents on science learning and the score by cognitive domains, and through correlation by items, we drew static and negative correlations, and then compared the value. The result are as follows: First, other fields except for 'physical science' and 'inference' revealed meaningful differences by learners' grade, and the interrelationship between all contents domains and cognitive fields also appeared statically different. Second, both achievement level of contents and cognition of learners presented significant differences, but the correlation between scientific contents and cognitive field of learners showed different aspects. Third, in static and negative correlation by items, the complexity and their aspects could be classified by targets' academic achievement levels.

Causal reasoning studies with a focus on the Power Probabilistic Contrast Theory (힘 확률 대비 이론에 기반을 둔 인과 추론 연구)

  • Park, Jooyong
    • Korean Journal of Cognitive Science
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    • v.27 no.4
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    • pp.541-572
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    • 2016
  • Causal reasoning is actively studied not only by psychologists but, in recent years, also by cognitive scientists taking the Bayesian approach. This paper seeks to provide an overview of the recent trends in causal reasoning research with a focus on the power probabilistic contrast theory of causality, a major psychological theory on causal inference. The power probabilistic contrast theory (PPCT) assumes that a cause is a power that initiates or inhibits the result. This power is purported be understood through statistical correlation under certain conditions. The paper examines the supporting empirical evidence in the development of PPCT. Also, introduced are the theoretical dispute between the PPCT and the model based on Bayesian approach, and the current developments and implications of research on causal invariance hypothesis, which states that cause operates identically regardless of the context. Recent studies have produced experimental results that cannot be readily explained by existing empirical approach. Therefore, these results call for serious examination of the power theory of causality by researchers in neighboring fields such as philosophy, statistics, and artificial intelligence.

Trend Analysis of Artificial Intelligence Technology Using Patent Information

  • Park, Jae-Yong
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.4
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    • pp.9-16
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    • 2018
  • In this paper, we propose wide range of categorizes Artificial Intelligence technology as Learning, Inference, and Cognitive. Also, it analyzes 758 cases of open patents. For an analysis, target technologies were selected and categorized into specific areas to collect information about the patents. After removing noise, the patent information for each technology such as patent assignees and IPC code, was analyzed to evaluate the maturity of technology, the way ahead for research and development and the trends in core technology. This research presents directions of Artificial intelligence technology research and trend analysis of core Artificial Intelligent technology using quantitative analysis of patent information. Also Artificial intelligence technology requires technological development necessity through close cooperation in diverse fields.

CHART PARSER FOR ILL-FORMED INPUT SENTENCES (잘못 형성된 입력문장에 대한 CHART PARSER)

  • KyonghoMin
    • Korean Journal of Cognitive Science
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    • v.4 no.1
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    • pp.177-212
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    • 1993
  • My research is based on the parser for ill-formed input by Mellish in a paper in ACL 27th meeting Proceedings. 1989. My system is composed of two parsers:WFCP and IFCP. When WFCP fails to give the parse tree for the input sentence, the sentence is identified as ill-formed and is parsed by IFCP for error detection and recovery at the syntactic level. My system is indendent of grammatical rules. It does not take into account semantic ill-formedness. My system uses a grammar composed of 25 context-free rules. My system consistes of two major parsing strategies:top-down expection and bottem-up satisfaction. With top-down expectation. rules are retrieved under the inference condition and expaned by inactive arcs. When doing bottom-up parsing. my parser used two modes:Left-Right parsing and Right-to-Left parsing. My system repairs errors sucessfully when the input contains an omitted word or an unknown word substitued for a valid word. Left- corner and right-corner errors are more easily detected and repaired than ill-formed senteces where the error is in teh middle. The deviance note. with repair details, is kept in new inactive arcs which are generated by the error correction procedure. The implementation of my system is quite different from Mellish's. When rules are invoked. my system invokes all rules with minimal inference. My bottom up parsing strategy uses Left-to-Right mode and Right-to-Left mode. My system is bottom-up-parsing-oriented like the chart parser. Errors are repaired in two ways:using top-down hypothesis, and using Need-Chart which keeps the information of expectation and complection of expanded goals by rules. To reduce the number of top-down cycles. all rules are invoked simultaneously and this invocation information is kept in Need-Chart. This idea will be extended for the implementation of multiple error recovery system.

Plan-based Ellipsis Resolution for Utterances in Noun-Phrase-Form in Restricted Domain Dialogues (제한된 영역의 대화에서 체언구 형태의 발화 이해를 위한 계획기반 생략 처리)

  • 윤철진;서정연
    • Korean Journal of Cognitive Science
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    • v.11 no.1
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    • pp.81-92
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    • 2000
  • Elliptical fragments are common in natural language dialogues between humans. Since most elliptical fragments should be interpeted within the context. it is not easy for computers to recognize the speaker's intention from the elliptical fragments. In t this paper we propose a model to recognize speaker's intention from elliptical fragments 1 in Korean by expanding the tripartite plan-based model proposed by Lambert. We add new discourse recipes to define user's discourse actions through elliptical fragments. In order to use plan inference process. we must represent utterances as actions. e. g .. r e elliptical fragments are represented as surface speech acts. In surface speech act representation. we include the information of 'Josa' (case markers in Korean), because t the information of 'Josa' plays a very important role in analysing speakers' intention in Korean. Finally. by using an object and discourse focus theory, the system can recognize the intention that a user is trying to compare between two plans by uttering elliptical fragments

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