Shopping Experience Memory Scale

2020 ◽  
Author(s):  
Michaël Flacandji ◽  
Nina Krey
Keyword(s):  
Shopping Experience

India Goes Digital..Smartphone is the New Shopping Destination

2018 ◽  
Vol 6 (8) ◽  
pp. 289
Author(s):  
Shankar Chaudhary
Keyword(s):  
Online Shopping ◽  
Mobile Apps ◽  
Smart Phone ◽  
Mobile Commerce ◽  
Mobile App ◽  
Smart Phones ◽  
The Internet ◽  
The World ◽  
Shopping Experience ◽  
User Friendly

Despite being in nascent stage m-commerce is gaining momentum in India. The explosive growth of smart-phone users has made India much loved business destination for whole world. Indian internet user is becoming the second largest in the world next to China surpassing US, which throws open plenty of e-commerce opportunities, not only for Indian players, offshore players as well. Mobile commerce is likely to overtake e-commerce in the next few years, spurred by the continued uptrend in online shopping and increasing use of mobile apps.The optimism comes from the fact that people accessing the Internet through their mobiles had jumped 33 per cent in 2014 to 173 million and is expected to grow 21 per cent year-on-year till 2019 to touch 457 million. e-Commerce brands are eyeing on the mobile app segment by developing user-friendly and secure mobile apps offering a risk-free and easy shopping experience to its users. Budget 4G smart phones coupled with affordable plans, can very well drive 4G growth in India.

STORE ATMOSPHERIC FACTORS AT SELECT LARGE FORMAT RETAIL STORES IN HYDERABAD

2020 ◽  
pp. 1-4
Author(s):  
M Himabindu
Keyword(s):  
Sampling Technique ◽  
Retail Stores ◽  
Retail Sector ◽  
Large Format ◽  
Shopping Experience ◽  
Innovative Tool ◽  
Convenience Sampling ◽  
Atmospheric Factors ◽  
Number Of Customers ◽  
Structured Questionnaire

Store Atmospherics is an innovative tool that retailers use to attract a number of customers into the store and retain them for longer time in the store. The share of large format retail stores in organized retail sector is increasing significantly. This paper is an empirical study of factors of Store Atmospherics from customers’ viewpoint. Data was collected through structured questionnaire from 75 respondents following convenience sampling technique. Reliability test and factor analysis were done using SPSS. Results show that Store Music, Store Decorations, Store Fragrance, Store Brightness, In-store Promotions and Ambience are the important Store Atmospheric factors. Large format retailers should focus more on these so as to increase their appeal to the customers and give them a good shopping experience so that favourable shopping outcomes follow.

Impact of Chatbot in Transforming the Face of Retailing- An Empirical Model of Antecedents and Outcomes

2019 ◽  
Vol 12 ◽  
Author(s):  
Kumari Anshu ◽  
Loveleen Gaur ◽  
Arun Solanki
Keyword(s):  
Research Work ◽  
Shopping Behavior ◽  
Model Framework ◽  
Shopping Experience ◽  
The Face ◽  
Strongly Agree ◽  
Different Characteristics ◽  
Work Done ◽  
The Impact ◽  
Self Administered Questionnaire

Chatbot has emerged as a significant resolution to the swiftly growing customer caredemands in recent times. Chatbot has emerged as one of the biggest technological disruption. Simply speaking, it is a software agent facilitating interaction between computers and humans in natural language. So basically, it is a simulated, intellectual dialogue agent functional in a range of consumer engagement circumstances. It is the easiest and simplest means enable interaction between the retailers and the customers. </p><p> • Purpose- Most of the research work done in this field is concerned with their technical aspects. The recent research on chatbot pay little attention to the impact it is creating on users’ experience. Through this work, author is making an effort to know the customer-oriented impact that the chatbot bear on the shoppers. The purpose of this study is to develop and empirically test a framework that identify the customer oriented attributes of chatbot and impact of these attributes on customers. </p><p> • Objectives- The study intends to bridge the gap between concepts and actual attributes and applications on the subject of Chatbot. The following research objectives can address the various aspects of Chatbot affecting the different characteristics of consumers shopping behaviors: a) Identify the various attributes of chatbot that bears an impression on consumer shopping behavior. b) Evaluate the impact of chatbot on consumer shopping behavior that leads to the development of chatbot usage and adoption among the customer. </p><p> • Design/Methodology/Approach – For the purpose of analysis, author has administered Factor analysis and Multiple regression using SPSS version 23 for identification of various attributes of Chatbot and knowing their impact on shoppers. A self-administered questionnaire from the review of literature is developed. Industry experts in the field of retailing and academician evaluate the questionnaire. Primary information from the respondents is gathered using this questionnaire. The questionnaire comprises of Likert scale on a scale of 1 to 5 where 1 stands for strongly disagree and 5 stands for strongly agree. Data is collected from 126 respondents, out of which 111 respondents were finally considered for study and analysis purpose. </p><p> • Findings – The empirical results show that the study identifies various attributes of chatbot like Trust, Usefulness, Satisfaction, Readiness to Use and Accessibility. It is also found that chatbot is really influencing the customers in providing them with shopping experience, which can be very helpful to the businesses for increasing the sales and creating repurchase intention among the customers. </p><p> • Originality/value – The recent research on chatbot pay little attention to the impact it is creating on customers who are actually interacting with it on regular basis. The research paper extends information for understanding and appreciating the customer oriented attributes of artificially intelligent Chatbot. In this regard, the author has developed a model framework and proposed the attributes identified. Through the work, author is also making an effort to test empirically the impact of the identified attributes on the shoppers.

The Impact of Demographic Factor on Consumer Buying Behaviour: A Study of Retail Sector in Delhi NCR

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Shamsher Singh ◽  
Ameet Sao
Keyword(s):  
Sampling Method ◽  
Primary Data ◽  
Survey Method ◽  
Retail Sector ◽  
Demographic Shift ◽  
Customer Perception ◽  
Shopping Experience ◽  
Buying Behaviour ◽  
The Impact ◽  
Structured Questionnaire

The retail sector is growing a faster pace in India due to demographic shift in population and growing middle class. It is an opportunity for both organized and unorganized sectors. The purpose of this article is to study the customer perception and shopping experience about organized and unorganized retailing with special reference to Delhi and NCR and find out whether the preferences for organized and unorganized retailing are dependent or independent demographic characteristics of consumers. The study has used the primary data collected from 200 respondents through survey method using structured questionnaire. Convenient sampling method was used during the

Constrained Dual-Level Bandit for Personalized Impression Regulation in Online Ranking Systems

2021 ◽  
Vol 16 (2) ◽  
pp. 1-23
Author(s):  
Zhao Li ◽  
Junshuai Song ◽  
Zehong Hu ◽  
Zhen Wang ◽  
Jun Gao
Keyword(s):  
Optimization Problem ◽  
Initial Conditions ◽  
Global Scale ◽  
Global Constraints ◽  
Economic Losses ◽  
Second Order Cone ◽  
Ranking Systems ◽  
Item Level ◽  
Shopping Experience ◽  
Regulation Method

Impression regulation plays an important role in various online ranking systems, e.g. , e-commerce ranking systems always need to achieve local commercial demands on some pre-labeled target items like fresh item cultivation and fraudulent item counteracting while maximizing its global revenue. However, local impression regulation may cause “butterfly effects” on the global scale, e.g. , in e-commerce, the price preference fluctuation in initial conditions (overpriced or underpriced items) may create a significantly different outcome, thus affecting shopping experience and bringing economic losses to platforms. To prevent “butterfly effects”, some researchers define their regulation objectives with global constraints, by using contextual bandit at the page-level that requires all items on one page sharing the same regulation action, which fails to conduct impression regulation on individual items. To address this problem, in this article, we propose a personalized impression regulation method that can directly makes regulation decisions for each user-item pair. Specifically, we model the regulation problem as a C onstrained D ual-level B andit (CDB) problem, where the local regulation action and reward signals are at the item-level while the global effect constraint on the platform impression can be calculated at the page-level only. To handle the asynchronous signals, we first expand the page-level constraint to the item-level and then derive the policy updating as a second-order cone optimization problem. Our CDB approaches the optimal policy by iteratively solving the optimization problem. Experiments are performed on both offline and online datasets, and the results, theoretically and empirically, demonstrate CDB outperforms state-of-the-art algorithms.

scholarly journals Does CSR Help to Retain Customers in a Service Company?

2020 ◽  
Vol 13 (1) ◽  
pp. 300
Author(s):  
Juan Carlos Fandos-Roig ◽  
Javier Sánchez-García ◽  
Sandra Tena-Monferrer ◽  
Luis José Callarisa-Fiol
Keyword(s):  
Financial Services ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Special Importance ◽  
Csr Strategies ◽  
Shopping Experience ◽  
Managerial Implications ◽  
Customer's Loyalty ◽  
High Level ◽  
Customer Trust

The main aim of this paper is to analyze the influence of service companies’ corporate social responsibility (CSR) actions on final customer’s loyalty. A theoretical model of loyalty formation based on CSR was proposed and a sample of 1125 final customers of financial services in Spain was studied. Structural equation models were used to verify the hypothesized relationships. Based on the CSR theory oriented to stakeholders, this work justifies the direct and positive relationship between the perception of CSR actions in the shopping experience and customer trust. We also verified a positive indirect influence on loyalty. The services industry was chosen to conduct this research due to its own particularities (intangibility, inseparability, heterogeneity and perishability). As it is impossible to evaluate a service before its consumption, a high level of trust in the supplier will be necessary to motivate the purchase decision. We conclude that CSR becomes a key strategic asset for determining trust and loyalty among consumers. As major findings, we have verified the special importance of CSR in the services market. CSR improves customer trust in the service provider. Thus, this paper has significant managerial implications. Through CSR strategies, both the perception of the customer’s purchasing experience and trust can be enhanced, resulting in more loyal customers. As a limitation, this research was carried out among financial services. Further research should test the model across different industries and countries in order to determine the generalizability and consistency of the findings of this study.

scholarly journals Recognition of Customers’ Impulsivity from Behavioral Patterns in Virtual Reality

2021 ◽  
Vol 11 (10) ◽  
pp. 4399
Author(s):  
Masoud Moghaddasi ◽  
Javier Marín-Morales ◽  
Jaikishan Khatri ◽  
Jaime Guixeres ◽  
Irene Alice Chicchi Giglioli ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Sensation Seeking ◽  
Support Vector Machine Classifier ◽  
Support Vector ◽  
Behavioral Patterns ◽  
Consumer Experience ◽  
Shopping Experience ◽  
Temporal And Spatial ◽  
Informative Signals ◽  
Exploration Task

Virtual reality (VR) in retailing (V-commerce) has been proven to enhance the consumer experience. Thus, this technology is beneficial to study behavioral patterns by offering the opportunity to infer customers’ personality traits based on their behavior. This study aims to recognize impulsivity using behavioral patterns. For this goal, 60 subjects performed three tasks—one exploration task and two planned tasks—in a virtual market. Four noninvasive signals (eye-tracking, navigation, posture, and interactions), which are available in commercial VR devices, were recorded, and a set of features were extracted and categorized into zonal, general, kinematic, temporal, and spatial types. They were input into a support vector machine classifier to recognize the impulsivity of the subjects based on the I-8 questionnaire, achieving an accuracy of 87%. The results suggest that, while the exploration task can reveal general impulsivity, other subscales such as perseverance and sensation-seeking are more related to planned tasks. The results also show that posture and interaction are the most informative signals. Our findings validate the recognition of customer impulsivity using sensors incorporated into commercial VR devices. Such information can provide a personalized shopping experience in future virtual shops.

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