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Factors Contributing and Curtailing Online Shopping Behavior: A Factor Analysis Approach


Affiliations
1 School of Management, SASTRA University, Thanjavur – 613401, Tamil Nadu, India
 

Objectives: To identify the factors those contribute and curtail people from online shopping and to verify whether the online shopping behaviors of rural people and urban people vary. Methods/Analysis: Descriptive research design was used; the primary data was collected from 320 samples from rural and urban areas of Trichy district using a structured questionnaire with the help of snow ball sampling method. The data was analyzed using descriptive statistics, one way Analysis of Variance and Factor analysis. Findings: Delivery on door steps was the top ranked and multitasking abilities was the lowest ranked contributing variable towards online shopping. The factors contributing towards online shopping were door delivery and frequent purchase loyalty bonus; purchase time saving and easy payment; easy cancellation and replacement guarantee services; exclusive new product launches; product comparison possibilities; return of goods; service quality and access to international products and product review option for users. Lack of real shopping experience was the top ranked and products are not boxed was the lowest ranked curtailing variable towards online shopping. The factors curtailing online shopping were absence of real shopping experience; delay in replacement and re-fund and lack of privacy; expired products and late product delivery; out of stock and inaccessible to illiterates; poor warranty service and pirated products; mismatch between ordered and received products and poor delivery and high shipping charges. Applications/Improvements: The uniqueness of the study is that it finds that the E-enabled people from rural and urban areas do not vary in their on line shopping behaviors.

Keywords

ANOVA, Descriptive Statistics, E-Commerce, Factor Analysis, Online Shopping.
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  • Factors Contributing and Curtailing Online Shopping Behavior: A Factor Analysis Approach

Abstract Views: 150  |  PDF Views: 0

Authors

S. C. Sivasundaram Anushan
School of Management, SASTRA University, Thanjavur – 613401, Tamil Nadu, India
S. Selvabaskar
School of Management, SASTRA University, Thanjavur – 613401, Tamil Nadu, India
R. Alamelu
School of Management, SASTRA University, Thanjavur – 613401, Tamil Nadu, India

Abstract


Objectives: To identify the factors those contribute and curtail people from online shopping and to verify whether the online shopping behaviors of rural people and urban people vary. Methods/Analysis: Descriptive research design was used; the primary data was collected from 320 samples from rural and urban areas of Trichy district using a structured questionnaire with the help of snow ball sampling method. The data was analyzed using descriptive statistics, one way Analysis of Variance and Factor analysis. Findings: Delivery on door steps was the top ranked and multitasking abilities was the lowest ranked contributing variable towards online shopping. The factors contributing towards online shopping were door delivery and frequent purchase loyalty bonus; purchase time saving and easy payment; easy cancellation and replacement guarantee services; exclusive new product launches; product comparison possibilities; return of goods; service quality and access to international products and product review option for users. Lack of real shopping experience was the top ranked and products are not boxed was the lowest ranked curtailing variable towards online shopping. The factors curtailing online shopping were absence of real shopping experience; delay in replacement and re-fund and lack of privacy; expired products and late product delivery; out of stock and inaccessible to illiterates; poor warranty service and pirated products; mismatch between ordered and received products and poor delivery and high shipping charges. Applications/Improvements: The uniqueness of the study is that it finds that the E-enabled people from rural and urban areas do not vary in their on line shopping behaviors.

Keywords


ANOVA, Descriptive Statistics, E-Commerce, Factor Analysis, Online Shopping.



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i27%2F135351