Hallmarks and potential pitfalls of customer‐ and consumer engagement scales: A systematic review

Abstract

Multiple scales measuring a customer's, or consumer's, engagement (CE) with a brand or specific brand elements (e.g., advertising/social media content) have been proposed in the literature, offering researchers different options to gauge CE. However, the myriad proposed operationalizations can yield confusion among scholars regarding how to best capture CE, exposing a growing issue for CE research. Addressing this issue, we take stock of major scales measuring a CE with a brand or specific brand elements. To achieve this objective, we performed a systematic review of major CE scale development articles (2005 to January 2023) using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) approach. We systematically evaluated these scales in terms of their respective CE conceptualization, dimensionality, itemization, and underlying theoretical perspective. We also identify potential scale-related risks, or pitfalls, exposing important insight for CE researchers.Overall, the results suggest the existence of theoretical contamination in specific CE measures (e.g., through the inclusion of related concepts in the proposed CE definition), compromising their theoretical rigor and raising a need for scholars to verify the theoretical underpinnings of their adopted CE scales.

Engaging consumers through artificially intelligent technologies: Systematic review, conceptual model, and further research

“…We, then, developed a protocol specifying the inclusion criteria for our articles (Hollebeek et al, 2023). Specifically, relevant articles addressing AI‐based CE that were published in English, peer‐reviewed Scopus‐indexed journals with an impact factor of ≥3 were considered eligible for inclusion in our review (Giang Barrera & Shah, 2023; Rehman et al, 2020).…”

“…To guide our analysis, we adopted the widely‐used PRISMA protocol (e.g., Hollebeek et al, 2023; Moher, 2009), which comprises three main phases, including Identification, Screening, and Inclusion (Page et al, 2021). First, in the Identification phase, we searched the titles, abstracts, and keywords of eligible Scopus‐indexed journals for the following keywords (Shobhit et al, 2023): (engagement AND (“artificial intelligence” OR AI OR “machine learning” OR “deep learning” OR automated OR automation OR self‐driving OR autonomous OR chatbot* OR “voice assistant*” OR robot* OR “digital assistant*” OR “virtual assistant*” OR “recommender system*” OR “recommendation agent*” OR “supervised learning” OR “unsupervised learning” OR smart)).…”

“…First, CE is an interactive concept that centers on the consumer's interactions with a brand or (a) specific brand‐related object(s) (e.g., brand‐related AI technologies; Hollebeek et al, 2023; Perez‐Vega et al, 2021). Here, interaction reflects “mutual or reciprocal action or influence” (Vargo & Lusch, 2016, p. 9) between the engagement subject (e.g., consumer) and the engagement object (e.g., an AI technology; Hoffman & Novak, 2018; Hollebeek, 2011; Sung et al, 2021).…”

“…Second, CE is, typically, modeled as a multidimensional construct comprising cognitive, emotional, and behavioral dimensions (Hollebeek et al, 2023; Vivek et al, 2014). While cognitive engagement reflects the consumer's cognitive resource investment in their brand interactions (Schaarschmidt & Dose, 2023), emotional engagement denotes a consumer's emotion (e.g., passion) invested in their brand interactions (Herrando et al, 2017).…”

“…Third, scholars have adopted manifold theories to explore CE, including S‐D logic (Brodie et al, 2011), relationship marketing (Vivek et al, 2014), and congruity theory (Islam et al, 2018), among others, revealing the concept's theoretical versatility (Hollebeek et al, 2023). CE has also been explored in online (digital), offline, and hybrid (phygital) contexts (Mele & Russo‐Spena, 2022).…”