Wi-Suk Kwon

Online visual merchandising (VMD) of apparel web sites

Purpose – The purpose of this study was to examine visual merchandising (VMD) elements of apparel retail web sites, to describe the state of apparel online VMD and to develop a taxonomy of online VMD cues whose effects can be studied empirically.Design/methodology/approach – A total of 50 US and 50 Korean web sites were content analyzed in terms of environment, manner of presentation, and path finding.Findings – Results of the study revealed that many VMD features of offline stores have been implemented online. In addition, some VMD features of online apparel stores do not have a direct offline parallel. The taxonomy of VMD cues can be used by researchers to systematically study the effects of the cues following the SOR Model.Research limitations/implications – Because of the descriptive nature of the study important discussions about possible effects of various VMD elements on consumer behaviors cannot be addressed. Future research needs to investigate the effects of different VMD features introduced in ...

Exploration of Apparel Brand Knowledge Brand Awareness, Brand Association, and Brand Category Structure

Four phases of research were conducted to explore female college consumers’ apparel brand knowledge using students from a Southeastern university. First, results from a survey revealed a positive correlation between apparel brands’ recall and recognition performances (Phase 1). In Phase 2, through a brand-sorting task, four major apparel brand categories commonly perceived by female college consumers were identified. An online survey with a random sample of students (Phase 3) discovered that brands with higher levels of brand awareness were not necessarily linked to more favorable brand associations. Finally, an online experiment revealed that consumers’ cognitive structures of brand-category memberships were significantly affected by the model of categorization they were asked to use by the researchers (Phase 4). This study provided insight into the constructs of brand awareness, brand associations, and the three models of categorization which may aid consumers when identifying and classifying apparel brands in the market.

Virtual shopping agents

Purpose – The purpose of this study is to investigate whether the visual presence of a virtual agent on a retail Web site reveals positive outcomes for older users with respect to enhancing perceived interactivity, social support, trust and patronage intentions and alleviating user anxiety. Design/methodology/approach – A between-subjects laboratory experiment was conducted with 50 older users, which included an interaction experience of 30 minutes followed by a paper-based questionnaire. The visual presence of the agent was manipulated in a mock retail Web site through the presence or absence of a virtual agent image, while maintaining the same agent functionality. Findings – The contrasts of senior users’ shopping experiences between two agent-mediated Web sites (with or without agent image) support the direct “persona” effects of a virtual agent’s visual presence on enhancing perceived interactivity, social support, trust and patronage intentions in the retail Web site, while alleviating user anxiety. ...

Virtual Sales Associates for Mature Consumers Technical and Social Support in e-Retail Service Interactions

This study examines whether social presence through a virtual sales associate (VSA) affects mature consumers’ perceptions of technical and social supports from an apparel retail website and whether these perceptions influence consumers’ attitudes and patronage intentions toward the website. Sixty mature consumers participated in a laboratory experiment and completed a shopping task on a mock apparel website with or without a VSA. Results revealed that participants in the VSA (vs. no-VSA) condition perceived significantly greater social support; however, no significant difference existed in perceived technical support between the two conditions. This study also revealed that mature consumers’ perceived social support and ease of use of the retail website positively influenced their attitude toward the retail website, which in turn led to their website patronage intentions. Theoretical and managerial implications are discussed with respect to the potential of VSAs in enhancing the e-tail service quality for mature consumers.

Developing and Validating a Naturalistic Decision Model for Intelligent Language-Based Decision Aids

People make mundane and critical consumption decisions every day using choice processes that are inherently constructive in nature, where preferences emerge ‘on the spot’ or ‘on the go’ using multiple strategies based on the task at hand (Bettman, Luce, & Payne, 1998; Sproule & Archer, 2000). This implies that applying a single, invariant algorithm will not solve decision problems that humans face (Tversky, Sattath, & Slovic, 1988). Instead, consumers need adaptive, multi-strategy decision aids since they shift between multiple strategies in a single decision as they acquire increasing information during the decision-making process (Bettman et al., 1998). This paper puts forth a cognitive computing approach to develop and validate a naturalistic decision model for designing language-based, mobile decision-aids (MoDA©) based on adaptive and intelligent information retrieval and multi-decision strategy use. The approach integrates established psychological theories, Elaboration Likelihood Model (ELM) and Construal Level Theory (CLT), to develop the scientific base for predicting decision-making under contingencies. ELM delineates whether human information processing is effortful or heuristic based on a person’s ability and motivation to engage in an object-relevant elaboration (Petty & Cacioppo, 1981). CLT determines whether the cognitive construal of the decision object is abstract or concrete based on psychological distance (Liberman, Trope, & Wakslak, 2007). Integrating the derivatives of these theories, the Human-Elaboration-Object-Construal (H-E-O-C) Contingency Decision Model’s central thesis is that the decision-making strategy employed by a decision-maker can be predicted by using natural language cues to infer the extent of human elaboration (low-high) on the decision and the type of knowledge (abstract-concrete) possessed on the decision object. Specifically, an extensive (vs. limited) decision strategy is likely to be employed when human elaboration revealed through natural language cues is high (vs. low). Further, an attribute-based (vs. alternative-based) strategy may be employed when the cognitive representation of the decision object is abstract (vs. concrete). Based on this theorizing, the H-E-O-C Contingency Decision Model can predict the use of four common decision strategies that systematically differ based on the amount (extensive vs. limited) and pattern (attribute- vs. alternative-based) of processing: Lexicographic or LEX (limited, attribute-based processing), Satisficing or SAT (limited, alternative-based processing), Elimination-by-Aspects or EBA (extensive, attribute-based processing), and Weighted Adding or WADD (extensive, alternative-based processing) (Bettman et al., 1998). To validate the H-E-O-C Contingency Decision Model, we conducted observational studies that simulated in-store purchase decision-making with real consumers. A total of 48 shopping sessions (n = 48) were held in a simulation home improvement retail store, and decision-making dialog between consumers and a customer service agent (trained research assistant) was recorded using wearable voice recorders. To ensure that there were fairly equal numbers of consumers who were either motivated or not to elaborate on their decisions, we created two shopping conditions – low risk (replacement AC filter purchase) and high risk (AC filter purchase to address allergy and asthma). The recorded decision dialogs were first transcribed verbatim, resulting 48 units of analysis, which were then analyzed using the grounded theory approach through open and axial coding processes (Corbin & Strauss, 1990). The open coding first identified the construal level, which was followed by axial coding to infer the decision strategy (LEX, EBA, SAT, or WADD) employed by the consumer at the initial and final stages of decision-making. This process was conducted by two coders with adequate inter-coder reliability. Two different coders coded the transcripts for the elaboration level (low vs. high) of the consumer based on specific definitions, with adequate inter-coder reliability. The H-E-O-C Contingency Decision Model proposes that high elaboration consumers will employ either WADD or EBA, whereas low elaboration consumers will employ either SAT or LEX. This proposition was supported in over 80% of the decision transcripts, offering an important validation of the framework. The main contribution of the H-E-O-C Contingency Decision Model is that it is derived from universal psychological constructs and predicts decision-making strategies that apply to many types of products and services related to healthcare, education, and finance that are characterized by attributes and alternatives. This ensures its broad applicability across a wide variety of disciplines and use cases.

Neural Correlates of Consumer Buying Motivations: A 7T functional Magnetic Resonance Imaging (fMRI) Study

Consumer buying motivations can be distinguished into three categories: functional, experiential, or symbolic motivations (Keller, 1993). Although prior neuroimaging studies have examined the neural substrates which enable these motivations, direct comparisons between these three types of consumer motivations have yet to be made. In the current study, we used 7 Tesla (7T) functional magnetic resonance imaging (fMRI) to assess the neural correlates of each motivation by instructing participants to view common consumer goods while emphasizing either functional, experiential, or symbolic values of these products. The results demonstrated mostly consistent activations between symbolic and experiential motivations. Although, these motivations differed in that symbolic motivation was associated with medial frontal gyrus (MFG) activation, whereas experiential motivation was associated with posterior cingulate cortex (PCC) activation. Functional motivation was associated with dorsolateral prefrontal cortex (DLPFC) activation, as compared to other motivations. These findings provide a neural basis for how symbolic and experiential motivations may be similar, yet different in subtle ways. Furthermore, the dissociation of functional motivation within the DLPFC supports the notion that this motivation relies on executive function processes relatively more than hedonic motivation. These findings provide a better understanding of the underlying neural functioning which may contribute to poor self-control choices.

Modeling Conversational Flows for In-Store Mobile Decision Aids

Based on the Human-Elaboration-Object-Construal (HEOC) Contingency Model, we propose design principles for modeling conversational flows between consumers and an in-store mobile decision aid (MoDA) with artificial intelligence, functioning as a virtual sales associate. Through an on-going assessment of the quantity, type, and specificity of the decision preferences from the user’s spoken input, MoDA is modeled to identify the user’s levels of decision elaboration and construal, which leads to its recognition of the user’s use of and shifts across four decision strategies commonly applied in consumer decision-making contexts. Upon identification of the user’s decision-making strategy, MoDA is modeled to (1) identify strategy-relevant assistive tasks, (2) generate or access strategy- and task-relevant intelligence, and (3) utter strategy-, task-, and intelligence-relevant speech to naturally support the user’s decision making strategy. The proposed design principles further map the types and examples of the agent tasks, intelligence, and speech required across the four consumer decision making strategies.

Inferring a User’s Propensity for Elaborative Thinking Based on Natural Language

Natural language-based aids (e.g., intelligent cognitive assistants) that assist humans with various tasks and decisions, often need to recognize the user’s propensity (low-high) to elaborate on the task or decision, to ensure that the information provided matches the user’s thinking level. We conducted two qualitative studies of natural language usage in customers’ written product reviews (Study 1) and conversational transcripts of customer-store associate interactions (Study 2) to generate (Study 1) and validate (Study 2) four rules that can be employed to infer a user’s propensity for elaborative thinking. These include: consideration of multiple (2+) attributes/alternatives; detailed description (word count) about a single attribute/alternative; demonstration of specific knowledge (use of specific terms) about an attribute/alternative; and consideration of pros and cons about an attribute/alternative. Implications for natural language-based, intelligent cognitive assistants emerge as a result of this work.

Locus of control in conversational agent design: effects on older users’ interactivity and social presence

This study examines the impact of locus of control in conversational agent design on the interaction experience of 61 older users (65+ years old) through a laboratory experiment. Results reveal that for older users, agent control facilitates greater interactivity and social presence than user control.