Attribute Non-attendance as an Information Processing Strategy in Stated Preference Choice Experiments: Origins, Current Practices, and Future Directions

2020 ◽  
Vol 35 (3) ◽  
pp. 285-317 ◽  
Author(s):  
Daniel K. Lew ◽  
John C. Whitehead
Keyword(s):  
Information Processing ◽  
Stated Preference ◽  
Choice Experiments ◽  
Processing Strategy ◽  
Future Directions ◽  
Information Processing Strategy ◽  
Current Practices

scholarly journals Not Too Much and Not Too Little: Information Processing for a Good Purchase Decision

2021 ◽  
Vol 12 ◽  
Author(s):  
Claudia Vogrincic-Haselbacher ◽  
Joachim I. Krueger ◽  
Brigitta Lurger ◽  
Isabelle Dinslaken ◽  
Julian Anslinger ◽  
...  
Keyword(s):  
Information Processing ◽  
Two Dimensions ◽  
Consumer Information ◽  
Decision Quality ◽  
Ecological Rationality ◽  
Processing Strategy ◽  
Amount Of Information ◽  
Information Processing Strategy ◽  
Focus Information

When deciding on an online purchase, consumers often face a plethora of information. Yet, individuals consumers differ greatly in the amount of information they are willing and able to acquire and process before making purchasing decisions. Extensively processing all available information does not necessarily promote good decisions. Instead, the empirical evidence suggests that reviewing too much information or too many choice alternatives can impair decision quality. Using simulated contract conclusion scenarios, we identify distinctive types of information processing styles and find that certain search and selection strategies predict the quality of the final choice. Participants (N = 363) chose a cellular service contract in a web-based environment that closely resembled actual online settings in the country of study. Using information processing data obtained with tracking software, we identify three consumer segments differing along two dimensions – the extent dimension, referring to the overall effort invested in information processing, and the focus dimension, referring to the degree to which someone focuses on the best available options. The three subgroups of respondents can be characterized as follows: (1) consumers with a low-effort and low-focus information processing strategy (n = 137); (2) consumers with a moderate-effort and high-focus information processing strategy (n = 124); and (3) consumers with high-effort and low-focus information processing strategy (n = 102). The three groups differed not only in their information processing but also in the quality of their decisions. In line with the assumption of ecological rationality, most successful search strategies were not exhaustive, but instead involved the focused selection and processing of a medium amount of information. Implications for effective consumer information are provided.

SEARCH OF OPTIMAL COMPROMISE BETWEEN REQUIREMENTS IN SPHERE OF INFORMATION PROCESSING AND RESOURCES REQUIRED FOR THESE TASKS

2019 ◽  
pp. 78-81
Author(s):  
N. Yu. Kovalchuk
Keyword(s):  
Information Processing ◽  
Integrated Assessment ◽  
System Analysis ◽  
Objective Assessment ◽  
Automated System ◽  
Processing Strategy ◽  
Complex Information ◽  
Optimal Information ◽  
Information Processing Strategy ◽  
Selection Of

The possibility of using the fundamentals of system analysis when choosing the optimal information processing strategy in the design of complex information systems with the aim of obtaining a complete and objective assessment of information resources, implemented in the interest of analyzing the technical characteristics of integrated information processing tools of complex automated systems, is considered. Information risk analysis was carried out, i.e. the process of integrated assessment of information processing in an automated system with the transition to quantitative or qualitative indicators. In addition, each indicator represents the probable damage, which depends on the information processing in the system. The process of identifying and reducing risks that can affect the information system is understood as the process of risk management. The results of the analysis are used in the selection of information processing facilities and in evaluating the effectiveness of existing and projected subsystems.

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