Understanding online purchase decision making: The effects of unconscious thought, information quality, and information quantity

Gao, Jie; Cheng, Zhang; Wang, Ke; Ba, Sulin

doi:10.1016/j.dss.2012.05.011

Cited by 139 publications

(71 citation statements)

References 49 publications

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“…It will be messy to show all these effects in one figure. Hence, keeping in line with prior published papers (Gao et al 2012;Kumar et al 2007;Sun et al 2012), we decided to present the interaction effects in three separate figures (Figure 5a, b, c). It is seen that video format as compared with text format improves perceptions for all products, with the ratio of improvement ranging from 15% to almost 50%.…”

Section: Accepted Manuscriptmentioning

confidence: 90%

Will video be the next generation of e-commerce product reviews? Presentation format and the role of product type

Chen

Santhanam

2015

Decision Support Systems

130

122

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Section: Accepted Manuscriptmentioning

confidence: 90%

Will video be the next generation of e-commerce product reviews? Presentation format and the role of product type

Chen

Santhanam

2015

Decision Support Systems

130

122

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“…In literature, research has examined various factors influencing decision quality, including information quality (Raghunathan 1999;Gao et al 2012), information quantity (Gao et al 2012), thought mode (Gao et al 2012), the quality of a decision maker (Raghunathan 1999;Malhotra et al 2007), and time pressure (Kocher and Sutter 2006). In view of the impact of information technology on firm performance, Raghunathan presented that simultaneous improvement in the quality of information and a decision maker resulted in the upgrade of decision quality using theoretical and simulation models.…”

Section: Introductionmentioning

confidence: 99%

Determining attribute weights to improve solution reliability and its application to selecting leading industries

2014

Ann Oper Res

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In multiple attribute decision analysis, many methods have been proposed to determine attribute weights. However, solution reliability is rarely considered in those methods. This paper develops an objective method in the context of the evidential reasoning approach to determine attribute weights which achieve high solution reliability. Firstly, the minimal satisfaction indicator of each alternative on each attribute is constructed using the performance data of each alternative. Secondly, the concept of superior intensity of an alternative is introduced and constructed using the minimal satisfaction of each alternative. Thirdly, the concept of solution reliability on each attribute is defined as the ordered weighted averaging (OWA) of the superior intensity of each alternative. Fourthly, to calculate the solution reliability on each attribute, the methods for determining the weights of the OWA operator are developed based on the minimax disparity method. Then, each attribute weight is calculated by letting it be proportional to the solution reliability on that attribute. A problem of selecting leading industries is investigated to demonstrate the applicability and validity of the proposed method. Finally, the proposed method is compared with other four methods using the problem, which demonstrates the high solution reliability of the proposed method.

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“…In recent years, many studies about opinion mining or sentiment analysis have been reported in literature [1,2,12,19,22,23,28,35]. However, most of the existing methods only support one dimensional analysis and visualization of opinions.…”

Section: Introductionmentioning

confidence: 99%

Multi-opinion Ring: visualizing and predicting multiple opinion orientations in online social media

Lau

et al. 2015

Multimed Tools Appl

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In the era of the Social Web, actors (e.g. people, organizations, nations, etc) of online social media often voice out their opinions towards a variety of opinion targets. Extracting and visualizing distributions of multiple opinions among actors facilitates individuals or organizations to extract valuable social intelligence from online social media. The main contribution of our research reported in this paper is the development of a novel opinion analysis methodology named Multi-opinion Ring for visualizing and predicting multiple opinion orientations held by different groups of actors in online social media. In particular, the proposed Multi-opinion Ring method combines visualization techniques with machine learning methods to predict the opinion inclinations of actors who are originally neutral to different opinion targets. A series of controlled experiments, user-based evaluations, and case studies show that the proposed Multi-opinion Ring method significantly outperforms classical visualization methods in terms of the cohesiveness of the graphical layout and the informativeness of the visualized contents.

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Understanding online purchase decision making: The effects of unconscious thought, information quality, and information quantity

Cited by 139 publications

References 49 publications

Will video be the next generation of e-commerce product reviews? Presentation format and the role of product type

Will video be the next generation of e-commerce product reviews? Presentation format and the role of product type

Determining attribute weights to improve solution reliability and its application to selecting leading industries

Multi-opinion Ring: visualizing and predicting multiple opinion orientations in online social media

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