PMC:5919942 / 1708-10821
Annnotations
{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/5919942","sourcedb":"PMC","sourceid":"5919942","source_url":"https://www.ncbi.nlm.nih.gov/pmc/5919942","text":"Introduction\nNowadays, with the proliferation of electronic commerce (e-commerce), consumers are exposed to all varieties of products with large amounts of information prior to making purchase decisions. Though perfect information may lead to a better decision, the limitation of human beings' ability to process information has made purchase decision a difficult task for consumers (Cheng et al., 2014). Human cognitive bias, which is likely to inflict negative effect upon decision quality, has thereby attracted substantial attention (Cheng et al., 2014; Gamliel et al., 2016).\nThe attribute framing effect is one of the most noted decision biases, which refers to the phenomenon that people show inconsistency in preferences or choices when identical attribute information is provided in different ways (Tversky and Kahneman, 1981). In marketing studies, price is a type of attribute information of a product and plays an import role in consumer decision making. A number of studies have probed into the influence of price framing on consumers' perceptions and purchase intentions (Chen et al., 1998; Khan and Dhar, 2010; Schmitz and Ziebarth, 2017). Chen et al. (1998) framed a discount in percentage terms (% off) vs. dollar terms ($ off) on differentially priced products, and suggested that a discount framed in dollar terms was more effective in enhancing consumer purchase intention of high-price product, whereas the opposite was true for the low-price product. Hamilton and Srivastava (2008) examined the pricing effect when the total price of a product and/or service was partitioned into two or more mandatory components. They found that consumers' reactions to price framing were moderated by the perceived consumption benefit of the components. Price framing effect was also observed in the bundling context (Khan and Dhar, 2010; Goh and Bockstedt, 2013). Bundling is a marketing practice of selling two or more products as a single package for a special price. It was noted that the purchase likelihood was higher for cross-category bundle when the price reduction was described as savings on the relatively hedonic item instead of as savings on the utilitarian item (Khan and Dhar, 2010). Moreover, consumers' intention to buy a customized bundle of information goods as well as the size of chosen bundling was greatly impacted by different multipart pricing schemes (Goh and Bockstedt, 2013).\nBundling has turned out to be a popular practice for both online and offline marketers and bundle pricing decision has become a major concern (Sheikhzadeh and Elahi, 2013; Shaddy and Fishbach, 2017). However, so far, the influence of bundle price framing upon consumer decision making has not been fully understood. It has been suggested that when people have to make a choice between two products, they tend to switch their preference from the preferred more expensive product to the less preferred but cheaper alternative when the latter is offered at zero price (namely zero-price effect), since a free product could give rise to positive affective reactions (Shampanier et al., 2007; Votinov et al., 2016; Hüttel et al., in press). In the multi-component bundling context, however, it's not clearly known how consumers would perceive and react if one price frame contains a free component while the other doesn't, provided that the total prices in different price frames are identical.\nIn addition, prior researches have generally adopted behavioral approaches to explore the price framing effect. Given the significant role of internal processes in driving cognitive bias, it is critical to gain insight into the associated underlying neural mechanisms, particularly how the price framing on bundles affects information processing in our brain and subsequent purchase decision-making. The application of neuroscientific approaches to marketing (i.e., neuromarketing) is promising in elucidating consumers' underlying thoughts, feelings, and intentions (Gajewski et al., 2016; Schaefer et al., 2016; Goodman et al., 2017; Hsu, 2017). Gajewski et al. (2016), for instance, investigated the electrophysiological brain activity during simulated purchase decisions of technical products offered at different price levels and observed enhanced conflict processing for counter-conformity decisions (buy an expensive product or not to buy a cheap one) vs. conformity decisions (buy a cheap product or not to buy an expensive one), which was reflected by longer reaction times, an increased N2 and a reduced P3. Besides, a few researchers have recently attempted to uncover the neurocognitive processes of attribute framing effect. Take Jin et al. (2017) as an example, they presented participants with two attribute frames regarding the contents of woolen products (i.e., positive frame was described as fabric contents in the products and negative frame described as artificial fabric contents in the products), and demonstrated that compared with negative frames, positive frames attracted less attention at the early stage (smaller P2 amplitude), evoked less cognitive conflict (smaller P2-N2 complex) and led to higher evaluation (larger LPP amplitude).\nTherefore, the primary aim of the current study was to uncover the neural underpinnings of the price framing effect in bundle purchase decision-making by electrophysiological techniques. To attain this goal, two major price frames were created with the same total price for a bundle with two products, including a relatively expensive focal product and a relatively cheap tie-in product. In one price frame, both the focal and tie-in product were offered at a normal price (normal price condition, NP). In the second price frame, the tie-in product was offered at zero price while the total price of the bundle remained the same (zero price condition, ZP). Furthermore, a recent study reported an interesting finding that for price promotions offering product upgrades, it could be more effective when the upgrade was offered at a small token price (e.g., buy a Canon camera and upgrade its memory capacity from 16G to 32G for ¥0.1) rather than for free (Mao, 2016). We speculate that the tie-in product in a bundle might be treated as an “upgrade” in Mao's study. To test if Mao's findings could extend to a general bundling context, a third experimental condition was created such that the tie-in product was offered at a low token price (¥0.1, which was about equal to 0.016 US dollars at the time of experiment), whereas the focal product was offered at the same price as the focal product of ZP (low price condition, LP). Altogether, this study included three experimental condition (i.e., NP, ZP, and LP) with practically identical total prices (with a maximum difference of ¥0.1). During the experiment, participants were asked to view each bundle and determine if they would buy it or not while their scalp electroencephalogram (EEG) were recorded. According to prior literature on purchase decision making (Zhao et al., 2015; Goto et al., 2017), the late positive potential (LPP) is of particular interest to the current study.\nThe LPP is a positivity belonging to the P300 family, generally arises at about 400 ms after stimulus onset and lasts for several 100 ms (Schupp et al., 2000). The latencies of LPP vary across studies but tend to be predominant between 400 and 800 ms (Codispoti et al., 2012). LPP has a widespread scalp distribution from the frontal to the parietal sites with maxima over central-parietal sites. LPP is sensitive to motivationally relevant stimuli, and thought to reflect overt, post-perceptive deliberative processing related to stimulus significance (Olofsson et al., 2008). Emotionally significant stimuli (e.g., pleasant and unpleasant stimuli) has been found to trigger augmented LPP relative to neutral stimuli, suggesting enhanced activation of motivational system in the brain, increased resource allocation and sustained attentive processing for motivationally relevant stimuli (Schupp et al., 2004; Ferrari et al., 2011; Leite et al., 2012). Neuromarketing studies have revealed similar findings. Pozharliev et al. (2015), for instance, asked the participants to passively view pictures of luxury and basic branded products and noted increased LPP amplitude for luxury goods in the social context. Moreover, Goto et al. (2017) designed a virtual shopping task which revealed a positive relationship between LPP amplitude and subjective preferences of products. Consequently, LPP could reflect preferences based on more elaborative and conscious cognitive processes (Goto et al., 2017).\nIn the current study, three different price frames were created. Previous studies have demonstrated that options with no downside (no cost) could elicit more positive affect, which serves as an input for consumer decision making (Shampanier et al., 2007; Baumbach, 2016; Votinov et al., 2016). Thus, we hypothesize that the positive affect induced by a free component in a bundle could facilitate purchase decisions such that ZP will lead to higher purchase rate and enhanced LPP amplitude compared to NP and 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