Borrowing Decision of Households: An Examination of the Information Search Process

2017 ◽  
Vol 28 (1) ◽  
pp. 95-106 ◽  
Author(s):  
Lu Fan ◽  
Swarn Chatterjee
Keyword(s):  
Educational Attainment ◽  
Information Search ◽  
Financial Literacy ◽  
Search Behavior ◽  
Financial Knowledge ◽  
Search Process ◽  
Financial Capability ◽  
Factors Associated ◽  
Information Search Behavior ◽  
Underserved Groups

This study uses the 2009 National Financial Capability Study dataset to examine the factors associated with information search behavior by consumers when applying for a loan. The results indicate that financial literacy, perceived financial knowledge, educational attainment, and engaging the services of a financial professional are positively associated with the likelihood of information search among consumers. The results also indicate that consumers from the traditionally underserved groups, who would benefit most from better information search, were the least likely to use it. The results of this study are important to consumers, educators, and financial practitioners. A discussion of the implications addressing the association between financial literacy, information search behavior, and household financial capability within the population is also included in this study.

scholarly journals A Study on Customer Satisfaction across Information Search Behavior Typology

2008 ◽  
Vol 10 (1) ◽  
pp. 25
Author(s):  
Wahyuningsih Wahyuningsih ◽  
Johnny Tanamal
Keyword(s):  
Customer Satisfaction ◽  
Information Search ◽  
Search Behavior ◽  
Consumer Search ◽  
Future Research ◽  
Research Directions ◽  
Level Of Satisfaction ◽  
Future Research Directions ◽  
Information Search Behavior ◽  
Search For Information

This study investigates customer satisfaction based on a typology of consumer search behavior. The findings demonstrate that the type of consumer as defined by whether and how they search for information (passive, rational-active, and relational-dependent) has different level of satisfaction. Rational-active and relational-dependent consumers are found to be the dominant consumer types who actively search for information before purchasing a product and thus perceive a higher level of satisfaction than do passive consumers. The identification of satisfaction within each type of consumer provides a reason for customers to repurchase the same product, or recommend it to other people. As a result, companies will be able to achieve an increase in profitability. Recommendations for companies and future research directions are presented.

scholarly journals Consumer Information Search Behavior for Experiential and Material Purchases

2014 ◽  
Vol 6 (3) ◽  
pp. 194-201 ◽  
Author(s):  
Asli Elif Aydin
Keyword(s):  
Direct Observation ◽  
Information Search ◽  
Experimental Studies ◽  
Search Behavior ◽  
Consumer Information ◽  
Sources Of Information ◽  
Different Types ◽  
Material Purchases ◽  
Information Search Behavior ◽  
Consumer Information Search

The objective of this study is to determine whether sources of information consulted and the extent of information search differ between experiential and material purchases. For this purpose two experimental studies were conducted. It is demonstrated that moving along the experiential-material purchase continuum; consumers’ reliance on personal sources, especially personal independent sources intensifies towards experiential purchase pole and decreases towards material purchase pole. In addition, for material purchases; direct observation is preferred more compared to personal sources of information. Finally, it is revealed that the total amount of search is greater for experiential purchases than material purchases. The results suggest that experiential and material purchases require different types of search conduct due to their distinct natures.

Information Search on the Internet

2011 ◽  
pp. 19-42 ◽  
Author(s):  
Byung-Kwan Lee ◽  
Wei-Na Lee
Keyword(s):  
Information Search ◽  
Search Behavior ◽  
Past Research ◽  
The Internet ◽  
Online Information ◽  
Consumer Decision Making ◽  
Online Purchase ◽  
Information Search Behavior ◽  
Specific Factors ◽  
Research Propositions

Information search is an integral part of the consumer decision making process. There is no doubt that the Internet contributes to, and will continue to affect, this function. However, a comprehensive understanding of what causes, motivates, and mediates information search behavior on the Internet is relatively lacking. Based on an in-depth review and critical critique of past research on information search behavior and, in particular, online information search, this chapter offers a causal model of online information search with 16 specific research propositions outlined. It argues that information search on the Internet should be investigated by considering Internet specific factors (i.e., skills, prior online purchase experience, attitude toward the Internet) as well as various antecedents including situational, product-related, and individual factors. Contribution and implications of the model for further understanding of information search behavior in the context of the Internet are also discussed.

Tourists' Mobile Information Seeking Behavior

2017 ◽  
Vol 7 (1) ◽  
pp. 58-76 ◽  
Author(s):  
Jing Yi Gong ◽  
Fred Schumann ◽  
Dickson W.K. Chiu ◽  
Kevin K.W. Ho
Keyword(s):  
Information Search ◽  
Information Seeking ◽  
Information Needs ◽  
Search Behavior ◽  
Information Seeking Behavior ◽  
Republic Of China ◽  
Seeking Behavior ◽  
Independent Travel ◽  
Information Search Behavior ◽  
Usage Preference

The Internet is considered to be one of the most effective search channels for people to get a variety of information. This is especially true, for young tourists within the 18-30 year range, who prefer free independent travel tours. Many tend to have strong information needs about their travel destinations and the use of mobile technology for information search is rapidly becoming a popular trend, especially with this demographic. This study aims to investigate the associations between the mobile device usage preference and information search behavior of young travelers, between the ages of 18 and 30, in the People's Republic of China (PRC). For this purpose, a sample of 133 respondents is used. Results of the survey are provided and followed by a discussion of the overall context. Study limitations and directions for future development are suggested.

scholarly journals Eye-Tracking-Based Classification of Information Search Behavior Using Machine Learning: Evidence from Experiments in Physical Shops and Virtual Reality Shopping Environments

2020 ◽  
Vol 31 (3) ◽  
pp. 675-691 ◽  
Author(s):  
Jella Pfeiffer ◽  
Thies Pfeiffer ◽  
Martin Meißner ◽  
Elisa Weiß
Keyword(s):  
Virtual Reality ◽  
Recommender Systems ◽  
Eye Movement ◽  
Information Search ◽  
Search Behavior ◽  
Movement Data ◽  
Conversion Rates ◽  
Shopping Environments ◽  
Information Search Behavior

How can we tailor assistance systems, such as recommender systems or decision support systems, to consumers’ individual shopping motives? How can companies unobtrusively identify shopping motives without explicit user input? We demonstrate that eye movement data allow building reliable prediction models for identifying goal-directed and exploratory shopping motives. Our approach is validated in a real supermarket and in an immersive virtual reality supermarket. Several managerial implications of using gaze-based classification of information search behavior are discussed: First, the advent of virtual shopping environments makes using our approach straightforward as eye movement data are readily available in next-generation virtual reality devices. Virtual environments can be adapted to individual needs once shopping motives are identified and can be used to generate more emotionally engaging customer experiences. Second, identifying exploratory behavior offers opportunities for marketers to adapt marketing communication and interaction processes. Personalizing the shopping experience and profiling customers’ needs based on eye movement data promises to further increase conversion rates and customer satisfaction. Third, eye movement-based recommender systems do not need to interrupt consumers and thus do not take away attention from the purchase process. Finally, our paper outlines the technological basis of our approach and discusses the practical relevance of individual predictors.

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