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        <identifier>oai:figshare.com:article/33969085</identifier>
        <datestamp>2026-09-30T20:44:49Z</datestamp>
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          <dc:title>Liz Yingxue Zhao: Chatbots in Multi-Channel Information Elicitation</dc:title>
          <dc:creator>Yingxue Zhao (11445166)</dc:creator>
          <dc:subject>Marketing technology</dc:subject>
          <dc:subject>Chatbots</dc:subject>
          <dc:subject>Marketing</dc:subject>
          <dc:subject>Channels</dc:subject>
          <dc:subject>Information Elicitation</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;The image illustrates how chatbots can strengthen information elicitation in marketing across different communication channels. At the centre, the chatbot represents a conversational, interactive, and personalised interface that engages users across online and digital channels. This interaction facilitates the elicitation of richer information, reflected in key outcomes such as willingness to disclose, completeness, response quality, and engagement. These outcomes can, in turn, support more accurate customer insights, improved decision-making and personalisation, and higher response and completion rates. The image also highlights the theoretical foundations underpinning the research, such as Uncanny Valley Theory, etc. Overall, the visual captures the research focus on understanding how chatbot characteristics and channel contexts can shape users' responses and enhance the effectiveness of information collection in marketing.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-30T20:44:49Z</dc:date>
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