• Title/Summary/Keyword: Affect Heuristics

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Effects of Heuristic Type on Purchase Intention in Mobile Social Commerce : Focusing on the Mediating Effect of Shopping Value (모바일 소셜커머스에서 휴리스틱 유형이 구매의도에 미치는 영향 : 쇼핑가치의 매개효과를 중심으로)

  • KIM, Jin-Kwon;YANG, Hoe-Chang
    • Journal of Distribution Science
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    • v.17 no.10
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    • pp.73-81
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    • 2019
  • Purpose - The purpose of this study was to examine the effect of the heuristic type of consumers affecting purchase decision making and the intention of shopping value in their relationship to derive mobile social commerce purchase promotion plans. Research design, data, and methodology - A research model was constructed to relate the mediating effect of shopping value between heuristic types and purchase intentions. A total of 233 valid questionnaires were used for analysis for users using mobile social commerce. The statistical program used SPSS 24.0 and AMOS 24.0, and correlation analysis, regression analysis, and 3-step parametric regression analysis were used for the analysis. Results - The results of the analysis showed that representativeness heuristics, availability heuristics, adjustment heuristics, and affect heuristics had a statistically significant effect on the utilitarian value and the hedonic value. On the other hand, affect heuristics among the heuristic types were found to have the greatest influence not only on the utilitarian value but also on the hedonic value. The two types of shopping value were found to be partially mediated between representativeness heuristics and purchase intentions, between adjustment heuristics and purchase intentions, and fully mediated between availability heuristics and purchase intentions, affect heuristics and purchase intentions. Conclusions - These findings suggest that mobile social commerce companies should check in advance how consumer heuristic types affect purchase intentions. In particular, affect heuristics are caused by consumers' emotional mood such as mood or external stimulus being more important to decision making than rational decision making. Therefore, the result of this study suggests that it can be an important factor to secure the competitiveness that the potential customers who access to use mobile social commerce can feel enough fun and enjoyment in the platform provided by the company. It is also worth paying attention to the utilitarian and hedonic values perceived by consumers. This is because the judgment regarding the economic, convenience and important information provided by the mobile social commerce users affects the purchase intention through the trust of the information, past use, and shopping experience displayed on the mobile social commerce platform.

Decentralized Supply Chain Coordination with Revenue Sharing Mechanism: Transfer Pricing Heuristics and Revenue Share Rates

  • Chen, Hung-Yi;Wu, Hsiao-Chung
    • Industrial Engineering and Management Systems
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    • v.8 no.4
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    • pp.213-220
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    • 2009
  • A revenue sharing contract is one of the mechanisms that coordinate decision makers in a decentralized supply chain toward the consensual goal. The transfer prices between different echelons in the supply chain influence the total supply chain profits. The study aims to explore various transfer pricing heuristics on the supply chain coordination in terms of the supply chain profits and their interactions with the revenue sharing rate. A model is proposed for formulating the collaborative production and distribution planning in a decentralized supply chain with the revenue sharing mechanism. Experiment results indicate that the transfer price and the revenue sharing rate affect significantly the coordination. Among the studied pricing heuristics, the variable-cost pricing method led to the best SC profits. Raising the revenue sharing rate reduced the SC profits no matter what heuristics were employed. Furthermore, the experiments provide us clues for finding the optimal transfer price for the supply chain.

The Effect of Warehouse Layout Design on Order Picking Efficiency

  • Kim, Hyun;Hur, Yun-Su;Bae, Suk-Tae
    • Journal of Navigation and Port Research
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    • v.33 no.7
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    • pp.477-482
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    • 2009
  • In this paper the order picking problem in warehouses is considered, a topic which has received considerable attention from the international academic body in recent years. The order picking problem deals with the retrieval of order items from prespecified locations in the warehouse, and its objective is usually the minimization of travel time or travel distance. Hence, a well-thought order picking policy in combination with an appropriate storage policy will enhance warehouse efficiency and reduce operational costs. This paper starts with a literature overview summarizing approaches to routing order pickers, assigning stock-keeping units to pick locations and designing warehouse layouts. Since the layout design might affect both storage and routing policies, the three factors are interdependent with respect to order picking performance. To test these interdependencies, a simulation experiment was set up, involving two types of warehouse layout, four types of storage policy, five well-known heuristics and five sizes of order picking list. Our results illustrate that from the point of view of order picking distance minimization it is recommended to equip the warehouse with a third cross aisle, although this comes at the cost of a certain space loss. Additionally, we propose a set of most appropriate matches between order picking heuristics and storage policies. Finally, we give some directions for further research and recommend an integrated approach involving all factors that affect warehouse efficiency.

A Study on the Relationship between Brand image, Product liking, Heuristic and Purchase Intention According to Psychological Power

  • Jin-Kwon KIM;Ik-Jun CHO;Tony-DongHui AHN
    • The Journal of Economics, Marketing and Management
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    • v.11 no.5
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    • pp.69-80
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    • 2023
  • Purpose: The purpose of this study is to identify factors that affect decision-making for e-commerce users and to present ecommerce companies with the company's strategic directions for consumer purchases. Research design, data, and methodology: In this study, a structured research model was derived to confirm the relationship between brand image, product liking, heuristic and purchase intention and the difference according to psychological power. For analysis a total of 212 valid questionnaires from e-commerce users were used. confirmatory factor analysis, correlation analysis, and structural equations were conducted to verify. Results: Both brand image and product liking had a significant effect on purchase intention as well as heuristics. However, heuristics did not affect the purchase intention. It was found that the relationship between brand image, product liking, heuristic, and purchase intention differed depending on the psychological power. Conclusions: Companies should seek ways to increase the positive brand image and likability of products so that consumers can quickly purchase products. In the relationship between brand image and heuristic, the low-psychological group has more influence on heuristic, and in case of product liking, the high-psychological group has more influence on heuristic. In the relationship between brand image and product liking for purchase intention, both in the high psychological power group affect more influence on purchase intention. Since the process of purchasing products varies depending on the consumer psychological power tendency, it is necessary to identify the characteristics of consumers and establish strategies for purchasing promotion measures.

Cognitive Bias and Information Security Research: Research Trends and Opportunities

  • Park, Jongpil;Oh, Chang-Gyu
    • Asia pacific journal of information systems
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    • v.26 no.2
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    • pp.290-298
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    • 2016
  • Human cognition and decision-making related to information systems (IS) is a major area of interest in IS research. Among these areas, cognitive bias rooted in behavioral economics is gaining considerable attention from researchers. In the present study, we identify the role of cognitive biases and discuss how they shape the information security behavior. We also seek research opportunities to provide directions and implications for future research.

Path Selection Algorithms for Localized QoS Routing (로컬 QoS 라우팅을 위한 경로선택 알고리즘)

  • 서경용
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.40 no.12
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    • pp.38-45
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    • 2003
  • Recently, localized QoS routing scheme was recently proposed for overcome drawbacks of global state QoS routing schemes. Localized QoS routing dose not exchange QoS states among routers, but use virtual capacity based routing scheme instead. In localized QoS routing, to archive good performance, a set of candidate paths must be selected between the source and the destination effectively. In this paper we propose a few heuristics for effective path selection and develop path selection algorithms based on the heuristics. More detail analysis of the proposed algorithm is presented with simulation results which demonstrate that the path selection method can very affect the performance of localized QoS routing.

Learning Heuristics for Tactical Path-finding in Computer Games (컴퓨터 게임에서 전술적 경로 찾기를 위한 휴리스틱 학습)

  • Yu, Kyeon-Ah
    • Journal of Korea Multimedia Society
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    • v.12 no.9
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    • pp.1333-1341
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    • 2009
  • Tactical path-finding in computer games is path-finding where a path is selected by considering not only basic elements such as the shortest distance or the minimum time spend but also tactical information of surroundings when deciding character's moving trajectory. One way to include tactical information in path-finding is to represent a heuristic function as a sum of tactical quality multiplied by a weighting factor which is.. determined based on the degree of its importance. The choice of weighting factors for tactics is very important because it controls search performance and the characteristic of paths found. In this paper. we propose a method for improving a heuristic function by adjusting weights based on the difference between paths on examples given by a level designer and paths found during the search process based on the CUITent weighting factors. The proposed method includes the search algorithm modified to detect search errors and learn heuristics and the perceptron-like weight updating formular. Through simulations it is demonstrated how different paths found by tactical path-finding are from those by traditional path-finding. We analyze the factors that affect the performance of learning and show the example applied to the real game environments.

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A Study of Multicast Tree Problem with Multiple Constraints (다중 제약이 있는 멀티캐스트 트리 문제에 관한 연구)

  • Lee Sung-Ceun;Han Chi-Ceun
    • Journal of Internet Computing and Services
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    • v.5 no.5
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    • pp.129-138
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    • 2004
  • In the telecommunications network, multicasting is widely used recently. Multicast tree problem is modeled as the NP-complete Steiner problem in the networks. In this paper, we study algorithms for finding efficient multicast trees with hop and node degree constraints. Multimedia service is an application of multicasting and it is required to transfer a large volume of multimedia data with QoS(Quality of Service). Though heuristics for solving the multicast tree problems with one constraint have been studied. however, there is no optimum algorithm that finds an optimum multicast tree with hop and node degree constraints up to now. In this paper, an approach for finding an efficient multicast tree that satisfies hop and node degree constraints is presented and the experimental results explain how the hop and node degree constraints affect to the total cost of a multicast tree.

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The Effect of Representativeness in News Recommendation Mechanisms on Audience Reactions in Online News Portals (대표성 기반 뉴스 추천 메커니즘이 온라인 뉴스 포탈의 독자 반응에 미치는 영향)

  • Lee, Un-Kon
    • The Journal of Society for e-Business Studies
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    • v.21 no.2
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    • pp.1-22
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    • 2016
  • News contents has been collected, selected, edited and sometimes distorted by the news recommendation mechanisms of online portals in nowadays. Prior studies had not confirmed the consensus of newsworthiness, and they had not tried to empirically validate the impacts of newsworthiness on audience reactions. This study challenged to summarize the concepts of newsworthiness and validate the impact of representativeness of both editor's and audience's perspective on audience reactions as perceived news quality, trust on news portal, perceived usefulness, service satisfaction, loyalty, continuous usage intention, and word-of-mouth intention by adopting the representativeness heuristics method and information adoption model. 357 valid data had been collected using a scenario survey method. Subjects in each groups are exposed by 3 news recommendation mechanisms: 1) the time-priority news exposure mechanism (control group), 2) the reference-score-based news recommendation mechanism (a single treatment group), and 3) the major-news-priority exposure mechanism sorting by the reference scores made by peer audiences (the mixed treatment group). Data had been analyzed by the MANOVA and PLS method. MANOVA results indicate that only mixed method of both editor and audience recommendation mechanisms impacts on perceived news quality and trust. PLS results indicate that perceived news quality and trust could significantly affect on the perceived usefulness, service satisfaction, loyalty, continuance usage, and word-of-mouth intention. This study would contributions to empathize the role of information technology in media industry, to conceptualize the news value in the balanced views of both editors and audiences, and to empirically validate the benefits of news recommendation mechanisms in academy. For practice, the results of this study suggest that online news portals would be better to make mixed news recommendation mechanisms to attract audiences.

Region Segmentation from MR Brain Image Using an Ant Colony Optimization Algorithm (개미 군집 최적화 알고리즘을 이용한 뇌 자기공명 영상의 영역분할)

  • Lee, Myung-Eun;Kim, Soo-Hyung;Lim, Jun-Sik
    • The KIPS Transactions:PartB
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    • v.16B no.3
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    • pp.195-202
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    • 2009
  • In this paper, we propose the regions segmentation method of the white matter and the gray matter for brain MR image by using the ant colony optimization algorithm. Ant Colony Optimization (ACO) is a new meta heuristics algorithm to solve hard combinatorial optimization problem. This algorithm finds the expected pixel for image as the real ant finds the food from nest to food source. Then ants deposit pheromone on the pixels, and the pheromone will affect the motion of next ants. At each iteration step, ants will change their positions in the image according to the transition rule. Finally, we can obtain the segmentation results through analyzing the pheromone distribution in the image. We compared the proposed method with other threshold methods, viz. the Otsu' method, the genetic algorithm, the fuzzy method, and the original ant colony optimization algorithm. From comparison results, the proposed method is more exact than other threshold methods for the segmentation of specific region structures in MR brain image.