New technology can be used at any stage of the marketing process, including during the segmentation, targeting or positioning sub-processes, to support or transform any of the marketing mix elements, thereby affecting consumer engagement with brands (Hollebeek et al., 2014). For example, product customization options (e.g. personalized Starbucks beverages) can alter the product offering, thereby enabling firms to more responsively cater to customers’ unique needs, wants or preferences (Keeling et al., 2019). Technology can also be used for promotional purposes (e.g. social media-based micro-targeting or virtual reality(VR)-based gamification to engage consumers; see Carlson et al., 2019). It can facilitate distribution (e.g. via additive manufacturing or 3 D printing) or influence consumers’ willingness to adopt or pay for focal offerings (e.g. via mobile or contactless payments; Kuppelwieser et al., 2014), thereby exerting potential effects on any of the marketing mix elements.
Inherent in the notion of evolving technology is its continuous innovative nature, whether radical or incremental. As such, firms need to prepare for and invest in their own adaptive capability within fast-changing business environments. To do so, knowledge or skill-based resources form an important foundation for customer engagement (CE; Vargo and Lusch, 2016; Hollebeek, 2017), which predominantly reside in human capital, including (internal) personnel or (external) customers who are prepared to exhibit high brand-related engagement (e.g. peer-to-peer user support in Apple Support Communities). Here, the latter group takes on the role of co-producers through their brand- and category-related activities (Xie et al., 2008). Based on these observations, the following key managerial question emerges: How can companies motivate customers to invest their scarce resources in interacting with their (vs competitors’) brands or competing activities? To foster insight into this question, companies require a deeper understanding of customers’ available resources and those they are willing to invest into particular brand- and category-related interactions and activities. This understanding can, in turn, be converted into marketing mix customization tools to optimally cater for specific customer needs, wants, or preferences (e.g. BMW’s Luxury Car Customizer; Hollebeek et al., 2019). Our specific interest is in the smart home, and how consumers work to customise ‘regular’ homes (i.e. the norm, with no in-built smart capability) into something more interactive (Gram-Hanssen and Darby, 2018). Although smart homes are now being built at an increasing rate these will remain the exception for many years (Harvey, et al., currently under review) and ‘smart’ will mostly emerge where consumers themselves look to customise their homes through individual creativity and access to recipe-based facilities now increasingly available on the web (e.g. www.IFTTT.com).
a) To what extent are regular customers motivated to ‘smarten’ their own homes?
b) What are the smart utilities or innovations that appeal most to do-it-yourself (DIY) smart home converters?
c) What resources do DIY smart home converters use/call upon to help them create their own smart environment?
d) How can organisations best exploit the opportunity to providing DIY smart home converters with the resources they really need and value most?
Method and Concepts
A mixed methods approach is recommended to investigate how companies can motivate customers to invest their scarce resources into customising/developing their ‘regular’ homes into smart/interactive environments. Both qualitative and quantitative methods will be necessary to capture the complex insights necessary to address the questions above. A range of theories may be deployed for the investigation and one of the successful candidates’ tasks will be to find the best conceptual focus for the work. Potentially useful theoretical lenses include service dominant logic (Vargo and Lusch, 2004); customer engagement theory (Brodie et al., 2011) and actor network theory (Latour, 2005)
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