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Impact of Voice Assistants on Brand Management

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Grade 1.3

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Master Thesis


Business Administration>Communication & Media




Master Thesis: Voice Assistant 2.4.1. Definition and VocabularyVoiceassistants are software agents that run on specific devices such as smart speakers and smartphones. The software listens for "wake-up words" to record the user's verbal request and send it to the server, where the request is processed and the command is interpreted. The server then sends information about the command back to the device, where it performs the appropriate task (Hoy, 2018, page 82). Although there are several different voice assistants available, common and similar and executable tasks are (Hoy, 2018, p. 83): • Send and read text messages, make calls, and send and read emails • Answer basic information inquiries ( "What time is it? What is the weather forecast? How many ounces are in the cup?") • Set timers, alarms, and calendar entries • Set reminders, make lists and perform basic mathematical calculations • Control media from connected services such as Amazon Play, Google Play, iTunes, Pandora, Netflix and Spotify•Control thermostats, lights, alarm clocks and locks and other IoT devices• Tell jokes and stories. The voice assistant can also make appointments and place orders on behalf of its users (Feng), 2017) . In addition, voice assistants can play skills, expand standard capabilities by accessing apps created such as "Alexa Skills" on Amazon's voice assistant (Hoy, 2018, p. 83), allowing more than 100,000 skills to be used globally. Currently, only 10,000 skills are available in Germany (Kinsella, 2019c). When the author mentions voice assistants, it should be noted that there are several synonyms, including "virtual assistant" (e.g. Dousay & Hall, 2018; Jones, 2018), "smart personal assistant" (e.g. Knote et al., 2018), " Intelligent personal assistants” (e.g. Silva et al., 2020; Chung, Iorga, Voas and Lee, 2017), “digital assistants” (e.g. Burton & Gaskin, 2019; Reis et al., 2018), and “voice-activated Personal assistants” (e.g. Coskun-Setirek and Mardikyan, 2017). 2.4.2. Technical background Regarding the more in-depth technical background of the voice assistance system, the system work based on voice recognition, text-to-speech and dialogue systems (Wielinga, 2018, pp. 6-7), explained in detail below: Voice recognition: voice recognition Refers to the translation of audio containing speech into a sentence that can be parsed by a computer. For this, it often uses machine learning (Wielinga, 2018, p. 6). Text to speech: Text to speech refers to the digital process of converting text into spoken language. Generally speaking, text-to-speech is supported by language analysis, signal processing, and machine learning technologies (Wielinga, 2018, pages 6-7). Dialogue systems: Dialogue systems use different technologies, including natural language processing, natural language understanding, and natural language generation to interact with individuals (Wielinga, 2018, p. 7). Thesis about Brand management 2.1.1. Defining brand is a widely discussed topic in academic literature, but according to the literature, there are several different definitions of the term brand, with various viewpoints that constitute the meaning of a brand (Maurya & Mishra, 2012, p.122) . One of the most cited definitions comes from the American Marketing Association, which defines a brand as: "A brand is a name, term, design, symbol, or any other characteristic that distinguishes a seller’s goods or services from those of other sellers Come on" (AMA, 2014). With this definition in mind, brand management is [...] the process of maintaining, improving and maintaining the brand so that the name is associated with positive results. [...] Brand management is based on marketing, but directly focuses on the brand and how the brand maintains its favor with consumers. (, 2019) 2.1.2. Background For decades, companies and researchers have tried to develop theories and how to develop a strong and attractive brand, because the brand is often considered the company’s most valuable asset (Keller & Lehmann, 2003, pp. 26-31). Adominantbrand is positively correlated with higher market share (Smith & Basu, 2002, p. 21), while strong brands are more resilient to product hazard crises (Dawar & Pillutla, 2000, p.224). In addition, brand loyalty makes users more likely to refute negative information about the brand (Ahluwalia, Burnkrant, & Rao, 2000, p. 10). Branding generates trust and emotional attachment, and therefore affects purchasing decisions (Erciş, Yildiz, &Türk, 2017, pages 11-12). As a result, thousands of publications deal with the topic of brand management and how companies can create strong and attractive brands. In all these publications, different explanations and theories are introduced. Heding, Knudtzen, and Bjerre (2009) conducted in-depth research on more than 300 journal articles and analyzed brand management theories from 1985 to 2008. As a result, the author discovered seven different brand management methods and how brand managers view the brand’s interaction with consumers. "These [...] methods complement each other rather than replace each other [...]". In addition, the author "[...] emphasizes that the birth of a method does not mean the end of the'previous' method" (Heding et al., 2009, p. 21). Seven different methods of brand management reflect the thinking that reflects the research period. However, many things similar to today can be drawn and valuable information can be extracted from them. In the following, these seven methods are structured in the order in which they appear. Read Less