What people talk about online and what they intend to do: related perspectives from text mining and path analysis
Sheng-Yen Chang (),
Virginia Bodolica (),
Huei-Hsia Hsu () and
Hsi-Peng Lu ()
Additional contact information
Sheng-Yen Chang: NTUST
Virginia Bodolica: American University of Sharjah
Huei-Hsia Hsu: CUST
Hsi-Peng Lu: NTUST
Eurasian Business Review, 2023, vol. 13, issue 4, No 7, 956 pages
Abstract:
Abstract Nowadays, it remains unclear whether the accumulation of Internet buzz can accurately predict customer preferences and buying intentions. We study two related perspectives with regard to what people talk about online and what they intend to do in the adoption phase to offer advice to companies aiming to excel in online marketing efforts. Drawing on the consumption value theory, we examine buyers’ discussions about and intention to use wearable devices for a sample of consumers in Taiwan. A framework is advanced to explore the results of big data analysis employing text-mining techniques (i.e., what people talk about) and survey-based research using structural equation modelling (i.e., what people intend to do). Functional, emotional and conditional values surfaced as the highest Internet buzzes of wearable devices. Conversely, emotional, epistemic and functional values emerged as the most influential drivers of customers’ adoption intention. Our findings suggest that different value dimensions are relevant at different points of the purchase-related decision-making process. Some values animate Internet discussions that pertain to the pre-purchase information search stage, and others appear significant during the formation of people’s purchase intentions. We discuss the theoretical and practical implications of our study and provide suggestions for future research.
Keywords: Online consumer behavior; Electronic word-of-mouth; Big data; Text mining; Consumption value theory; Wearable devices (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s40821-022-00221-4
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