The Role of Kansei Engineering in Influencing Overall Satisfaction and Behavioral Intention in Service Encounters

Customers today concern themselves more on fulfilling their emotional needs rather than rationales and functionalities. In dealing with customer emotions in products/services, Kansei Engineering (KE) is applied. A comprehensive case study in luxury hotels was conducted. Eighty one Indonesian, 75 Singaporean, and 74 Japanese tourists participated in this survey. It aims to investigate the relationships among constructs during service encounter process. The finding shows that emotions (affective process) play a significant role as a complement to cognitive process in influencing customer satisfaction. Among 3 populations, Japanese was found to be more Kansei-oriented customer. Keywords: Kansei Engineering, emotional needs, customer satisfactio

Towards Knowledge-Based Personalized Product Description Generation in E-commerce

Quality product descriptions are critical for providing competitive customer experience in an e-commerce platform. An accurate and attractive description not only helps customers make an informed decision but also improves the likelihood of purchase. However, crafting a successful product description is tedious and highly time-consuming. Due to its importance, automating the product description generation has attracted considerable interests from both research and industrial communities. Existing methods mainly use templates or statistical methods, and their performance could be rather limited. In this paper, we explore a new way to generate the personalized product description by combining the power of neural networks and knowledge base. Specifically, we propose a KnOwledge Based pErsonalized (or KOBE) product description generation model in the context of e-commerce. In KOBE, we extend the encoder-decoder framework, the Transformer, to a sequence modeling formulation using self-attention. In order to make the description both informative and personalized, KOBE considers a variety of important factors during text generation, including product aspects, user categories, and knowledge base, etc. Experiments on real-world datasets demonstrate that the proposed method out-performs the baseline on various metrics. KOBE can achieve an improvement of 9.7% over state-of-the-arts in terms of BLEU. We also present several case studies as the anecdotal evidence to further prove the effectiveness of the proposed approach. The framework has been deployed in Taobao, the largest online e-commerce platform in China.Comment: KDD 2019 Camera-ready. Website: https://sites.google.com/view/kobe201

Context Effects as Customer Reaction on Delisting of Brands

The delisting of brands is frequently used by retailers to strengthen their negotiating position with the manufacturers and suppliers of their product assortment. However, retailers and manufacturers have to consider the risk of potential reactions when customers are faced with a reduced or modified assortment and thus, different choice. In this paper, two studies are presented which investigate customers` switching behavior if a (sub-)brand is unavailable and key determinants of the resulting behavior are discussed. Various conditions are tested by taking into account context theory. The results reveal that customer responses depend significantly on the context. A real-life quasi-experiment suggests that manufacturers may encounter substantially larger losses than retailers. Managerial implications for both parties can be derived and recommendations for further research are developed.Consumer decisions, delisting, context effects, switching behavior, retailing, logistic regression

Modeling toothpaste brand choice: An empirical comparison of artificial neural networks and multinomial probit model

Copyright @ 2010 Atlantis PressThe purpose of this study is to compare the performances of Artificial Neural Networks (ANN) and Multinomial Probit (MNP) approaches in modeling the choice decision within fast moving consumer goods sector. To do this, based on 2597 toothpaste purchases of a panel sample of 404 households, choice models are built and their performances are compared on the 861 purchases of a test sample of 135 households. Results show that ANN's predictions are better while MNP is useful in providing marketing insight

Function-Based Categorization of Online Product Information Types

Hardly any in-depth knowledge is currently available on how different types of product-relevant information influence online consumer trust and purchase decision. To address this research gap, we apply a generic function-based information typology to systematically classify the large variety of online product information and plan for a focused comparison of their functional roles and differential effects on online consumer decision making. The ultimate goal is to provide a theoretical basis for guiding and prioritizing online information organization and provision, which becomes increasingly important in the current context of information overload. The paper briefly reviews information research in e-commerce, discusses the conceptual basis of applying the generic function-based topical relevance typology to analyze online product information, and uses a variety of product examples from Amazon.com to demonstrate the process. The paper concludes with preliminary findings from this pilot study

Impact of Visual Merchandising on University of New Hampshire Students

Visual merchandising is a marketing tool used by retail outlets in order to make their products attractive and engaging. It has the ability to sway consumers into buying a product, making visual merchandising a useful tool in today’s competitive market. This study examines the impact visual merchandising has on the students of the University of New Hampshire (UNH). To determine this, we researched both the students and their local retailers. Retailers in Durham, New Hampshire were interviewed to determine how important visual merchandising is to their business. The consensus was that visual merchandising is an important segment of their business; it is one of the most effective ways to market to students. To gain an understanding of students’ views, a survey was distributed to undergraduates to measure their shopping habits and perceptions of visual merchandising. It was found that students generally have a positive perception of visual merchandising. Overall, students find visual merchandising useful and valuable when shopping. Through the statements made by retailers and the data provided by students, it has been determined that students are largely impacted by visual merchandising at UNH

A Test-Retest Reliability Generalization Meta-Analysis of Judgments Via the Policy-Capturing Technique

Policy capturing is a widely used technique, but the temporal stability of policy-capturing judgments has long been a cause for concern. This article emphasizes the importance of reporting reliability, and in particular test-retest reliability, estimates in policy-capturing studies. We found that only 164 of 955 policy-capturing studies (i.e., 17.17%) reported a test-retest reliability estimate. We then conducted a reliability generalization meta-analysis on policy-capturing studies that did report test-retest reliability estimates—and we obtained an average reliability estimate of .78. We additionally examined 16 potential methodological and substantive antecedents to test-retest reliability (equivalent to moderators in validity generalization studies). We found that test-retest reliability was robust to variation in 14 of the 16 factors examined but that reliability was higher in paper-and-pencil studies than in web-based studies and was higher for behavioral intention judgments than for other (e.g., attitudinal and perceptual) judgments. We provide an agenda for future research. Finally, we provide several best-practice recommendations for researchers (and journal reviewers) with regard to (a) reporting test-retest reliability, (b) designing policy-capturing studies for appropriate reportage, and (c) properly interpreting test-retest reliability in policy-capturing studies

IMPULSE moment-by-moment test:An implicit measure of affective responses to audiovisual televised or digital advertisements

IMPULSE is a novel method for detecting affective responses to dynamic audiovisual content. It is an implicit reaction time test that is carried out while an audiovisual clip (e.g., a television commercial) plays in the background and measures feelings that are congruent or incongruent with the content of the clip. The results of three experiments illustrate the following four advantages of IMPULSE over self-reported and biometric methods: (1) being less susceptible to typical confounds associated with explicit measures, (2) being easier to measure deep-seated and often nonconscious emotions, (3) being better able to detect a broad range of emotions and feelings, and (4) being more efficient to implement as an online method.Published versio

Consumer Preferences for Imported Kona Coffee in South India: A Latent Class Analysis

Considering India as a potential export market for 100% Kona coffee, this study explores consumer preferences for imported, specialty, high-end Kona coffee in South India. Conjoint choice experiment with latent class analysis is used and results indicate that India offers an export market potential for Kona coffee, provided it caters to consumer preferences. Results show a significant preference for strong taste. The relative importance of price is lower than taste but majority are also adverse to higher prices. However,15% of the sample population does not care about price but does care about taste, indicating the possibility of a high-end niche market segment. Based on the results, marketing strategies and policy recommendations have been suggested.India, US Coffee Export, Kona Coffee, Conjoint Choice Experiment, Latent Class Analysis, Agribusiness, Q13,

The Effects of Customer-Centric Marketing and Revenue Management on Travelers’ Choices

This article examines how the simultaneous use of customer-centric marketing (CCM) and revenue management (RM) affects travelers’ perceptions of fairness and ultimately their purchasing choices. To address this issue, we propose and empirically test a choice model that incorporates reference-dependent fairness adjustments for both price and nonprice attributes within a random utility framework. The findings from two empirical studies using stated-preference choice experiments show that travelers engage in fairness-related reference point comparisons for price and other product attributes induced by RM and CCM. They offer additional evidence concerning the need to account comprehensively for attributes associated with both RM and CCM when predicting customer demand in travel and tourism firms. Accordingly, firms need to account not only for the effects of RM and CCM attributes but also for the corresponding reference-dependent fairness adjustments relating to those attributes