Brick and mortar store vs. online shopping experience: a study

2017 ◽  
Vol 16 (2) ◽  
pp. 133
Author(s):  
Manya Jha ◽  
Pooja Misra ◽  
Sushil Baranwal
Keyword(s):  
Online Shopping ◽  
Shopping Experience ◽  
Brick And Mortar

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.

scholarly journals How the Covid-19 Pandemic Is Changing Online Food Shopping Human Behaviour in Italy

2020 ◽  
Vol 12 (22) ◽  
pp. 9594
Author(s):  
Leonardo Salvatore Alaimo ◽  
Mariantonietta Fiore ◽  
Antonino Galati
Keyword(s):  
Online Shopping ◽  
Grocery Shopping ◽  
Competitive Advantages ◽  
Web Based ◽  
Explanatory Variables ◽  
Food Shopping ◽  
Cumulative Logit Model ◽  
Level Of Satisfaction ◽  
Shopping Experience ◽  
On Line

The advent of the Internet has significantly changed consumption patterns and habits. Online grocery shopping is a way of purchasing food products using a web-based shopping service. The current COVID-19 pandemic is determining a rethinking of purchase choice elements and of consumers’ behavior. This work aims to investigate which characteristics can affect the decision of online food shopping during the pandemic emergency in Italy. In particular, the work aims to analyze the effects of a set of explanatory variables on the level of satisfaction for the food online shopping experience. For achieving this aim, the proportional odds version of the cumulative logit model is carried out. Data derive from an anonymous on-line questionnaire administrated during the first months of the pandemic and filled by 248 respondents. The results of this work highlight that people having familiarity with buying food online, that have a higher educational level and consider food online channels easy to use, appear more satisfied for the food online shopping experience. These findings can be crucial for the future green global challenges as online shopping may help to reach competitive advantages for company sustainability.

Online versus offline: preferred retail choice for premium brand purchase

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rituparna Basu ◽  
Neena Sondhi
Keyword(s):  
Predictive Model ◽  
Logit Analysis ◽  
Chi Square ◽  
Content Type ◽  
Sales Personnel ◽  
Study Results ◽  
Shopping Experience ◽  
Brick And Mortar ◽  
Chi Square Analysis ◽  
Retail Format

PurposeThis exploratory study aims to examine the prevalent triggers that motivate a premium brand purchase in an online vs offline retail format.Design/methodology/approachA binary logit analysis is used to build a predictive model to assess the likelihood of the premium brand consumer seeking an online or an offline platform. Demographic and usage-based profile of the two set of consumers is established through a chi-square analysis.FindingsThree hundred and forty six urban consumers of premium branded apparels residing in two Indian Metros were studied. A predictive model with 89.6% accuracy was validated for distinguishing premium brand buyers who shop at brick-and-mortar store or online platforms. Quality and finish were factors sought by the online buyer, whereas autotelic need, pleasurable shopping experience and social approval were important triggers for an in-store purchase.Research limitations/implicationsThe study posits divergent demographics and motivational drivers that led to an online vs offline purchase. Though interesting and directional, the study results need to be examined across geographies and categories for establishing the generalizability of the findings.Practical implicationsThe study findings indicate that premium brand manufacturers can devise an omni-channel strategy that is largely tilted toward the online platform, as the quality conscious and brand aware consumer is confident and thus open to an online purchase. The implication for the physical outlet on the other hand is to ensure exclusive store atmospherics and knowledgeable but non-intrusive sales personnel.Originality/valueThe study is unique as it successfully builds a predictive model to forecast online vs offline purchase decisions among urban millennials.

Customer Experience: Extracting Topics From Tweets

2021 ◽  
pp. 147078532110475
Author(s):  
Manit Mishra
Keyword(s):  
Social Media ◽  
Customer Service ◽  
Latent Dirichlet Allocation ◽  
Online Shopping ◽  
Customer Experience ◽  
Process Failure ◽  
Shopping Experience ◽  
Social Media Platforms ◽  
Media Platform ◽  
Moments Of Truth

The ubiquity of social media platforms facilitates free flow of online chatter related to customer experience. Twitter is a prominent social media platform for sharing experiences, and e-retail firms are rapidly emerging as the preferred shopping destination. This study explores customers’ online shopping experience tweets. Customers tweet about their online shopping experience based on moments of truth shaped by encounters across different touchpoints. We aggregate 25,173 such tweets related to six e-retailers tweeted over a 5-year period. Grounded on agency theory, we extract the topics underlying these customer experience tweets using unsupervised latent Dirichlet allocation. The output reveals five topics which manifest into customer experience tweets related to online shopping—ordering, customer service interaction, entertainment, service outcome failure, and service process failure. Topics extracted are validated through inter-rater agreement with human experts. The study, thus, derives topics from tweets about e-retail customer experience and thereby facilitates prioritization of decision-making pertaining to critical service encounter touchpoints.

An Investigation of Online Shopping Experience on Trust and Behavioral Intentions

2015 ◽  
Vol 14 (2) ◽  
pp. 233-254 ◽  
Author(s):  
Lee Hao Suan Samuel ◽  
M. S. Balaji ◽  
Khong Kok Wei
Keyword(s):  
Behavioral Intentions ◽  
Online Shopping ◽  
Shopping Experience

scholarly journals Electronic Ticketing System and Traveler Purchasing Intention

2013 ◽  
Vol 217 ◽  
pp. 129-146
Author(s):  
THẢO HOÀNG THỊ PHƯƠNG
Keyword(s):  
Regression Models ◽  
Online Shopping ◽  
Behavioral Control ◽  
Ease Of Use ◽  
Perceived Behavioral Control ◽  
Perceived Ease Of Use ◽  
Demographic Groups ◽  
Purchasing Intention ◽  
Shopping Experience ◽  
The Difference

This research aims to identify the importance of factors that influence customer intention of purchasing electronic air ticket (e-ticket). The research compares the difference in purchasing intentions based on e-ticketing between demographic groups of age, income, educational level, and online shopping experience. With the sample size of 295 travelers, the regression models and ANOVA tests are used to process and explain data. The research detects four components, namely, perceived system usefulness, perceived ease of use, perceived behavioral control, and security of transaction that influence the consumer intention to buy e-ticket. The paper then recommends managerial solutions to the development of an electronic ticketing system in particular and e-commerce in general.

scholarly journals South African generation-X online shopper satisfaction and their repurchase intentions

2016 ◽  
Vol 13 (3) ◽  
pp. 371-379 ◽  
Author(s):  
Jobo Dubihlela ◽  
Difference Chauke
Keyword(s):  
Customer Satisfaction ◽  
South African ◽  
Social Exchange ◽  
Generation X ◽  
Online Shopping ◽  
Target Population ◽  
Jel Classification ◽  
Future Research ◽  
Repurchase Intentions ◽  
Brick And Mortar

The growth of online shopping channels gradually forces brick and mortar retailers to explore the importance of online shopping trends and online customer behavior. While maintaining customer satisfaction has been recognized as one of the essential factors for business survival and growth, this has not been sufficiently explored for online shopping platforms. Understanding what online constructs appeal to generation-X consumers is critical for organization that would want to pursue virtual business platforms. From a brief literature review in this study, it could be said that online customer satisfaction and its influences on online repurchase intentions in the South African retailing environment remain sparsely researched. Therefore, this study seeks to analyze the dimensions of online customer satisfaction and regress the online satisfaction dimensions on repurchase intentions of generation-X consumers. An attempt is made to apply the theory of planned behavior and social exchange in the adapted conceptual of the study. These theories are deemed to provide an appropriate theoretical grounding to this study. The target population was South African generation-X online consumers in Gauteng. A total of 377 questionnaires were received for data analysis. Implications of the research findings are discussed and limitations and future research directions are provided. Keywords: online shoppers, online customer satisfaction, repurchase intentions, generation-X consumers, South Africa. JEL Classification: M1, M30, M31, L10

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