Identifying the geography of online shopping adoption in Belgium

Beckers, Joris; Cárdenas, Iván; Verhetsel, Ann

doi:10.1016/j.jretconser.2018.08.006

Cited by 67 publications

(48 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However Lubis (2018), found that out of 200 respondents in the city of Medan, North Sumatra, men had a greater tendency to shop online. Similar results were also shown in the research conducted by Beckers et al (2018) The next factor is age. Online shoppers in America tend to be younger (Swinyard & Smith, 2003).…”

Section: Literature Reviewsupporting

confidence: 88%

“…International evidence also confirms such variety, either in America (Bellman, Lohse, & Johnson, 1999;Donthu & Garcia, 1999;Li, Kuo, & Rusell, 2006;Owens & Sarov, 2010;Swinyard & Smith, 2003;Yang & Lester, 2005), in India (Reddy & Srinivas, 2015;Richa, 2012), in Hong Kong and Taiwan (Chiu, Lin, & Tang, 2005;Sin & Tse, 2002), and other regions (Beckers et al, 2018;Bigné, Ruiz, & Sanz, 2005;Clarke, Thompson, & Birkin, 2015;Farag, Weltevreden, van Rietbergen, Dijst, & van Oort, 2006;Mahmood, Bagchi, & Ford, 2004;Rezai, Mohamed, Shamsudin, & Zahran, 2013;Zhou, Dai, & Zhang, 2007). In general, the existing literature investigates online shopping from the perspective of management and marketing studies.…”

Section: Introductionmentioning

confidence: 94%

“…Age and education factors do not significantly influence online shopping decisions. The variation in the results above indicates that online business developments between the regions are not uniform, and consumer behavior varies (Beckers, Cárdenas, & Verhetsel, 2018;Das et al, 2018).…”

Section: Introductionmentioning

confidence: 98%

See 2 more Smart Citations

Indonesian Demand for Online Shopping: Revisited

Yahya¹,

Sugiyanto

2020

J. Indones.Econ.Bus.

View full text Add to dashboard Cite

Introduction/Main Objectives: This study aims to analyze the factors that influence online shopping. Data are aggregated at the national, island, and regional levels. The regions are categorized based on their level of demand for online shopping. Background Problems: The rapid development of information and communications technology contributes to the transformation of the digital economy. By using 281,185 internet users from the National Households Survey (Survei Sosial Ekonomi-Susenas) 2017 data, we found that the percentage of online shopping in Indonesia is 7.59%. Online shopping is concentrated on the island of Java, especially in the Greater Jakarta area (Jakarta, Bogor, Depok, Tangerang, and Bekasi). Novelty: This study analyzes online shopping from the point of view of economic development studies, especially related to the development of information technology and the digital economy. Research Methods: We used a binary logistic regression analysis to assess the effect of demographic, socio-economic, and spatial factors on an individual’s decision to shop online. Finding/Results: The results indicate that individuals who have a greater tendency to shop online are those who have a high income, are women, can access the internet using mobile phones, they are the spouses of the heads of households, are 25 to30 years old, live in urban areas, have graduated from college (especially with a diploma), and work in the tertiary sector. The higher that the share of online shopping is in an area, the more intense the influence of individual characteristics will be on the tendency to shop online, according to the demographic and socio-economic factors, while the spatial factors will fade away. Conclusion: Income, gender, internet access, and the shopper’s position in the household are factors that significantly influence individuals to shop online.

show abstract

Section: Literature Reviewsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 94%

See 1 more Smart Citation

Indonesian Demand for Online Shopping: Revisited

Yahya¹,

Sugiyanto

2020

J. Indones.Econ.Bus.

View full text Add to dashboard Cite

show abstract

“…The scholars consider different approaches and methods to analyse CPDs systems (Song et al, 2009), for instance: environmental benefits (Edwards et al, 2010;Song et al, 2013;Liu et al, 2019), system dynamics models (Oliveira et al, 2010), scenario analysis of e-grocery distribution (Durand & Gonzalez-Feliu, 2012), modelling and simulation of e-commerce distribution (McLeod et al, 2006;González-Felíu et al, 2012), location analysis (Morganti et al, 2014a;Lemke et al, 2016), attitudes and behavioural analysis (Junjie & Min, 2013;Ducret, 2014;Xiao et al, 2018), e-consumers preferences (Moroz & Polkowski, 2016;Kedia et al, 2017;Oliveira et al, 2017;Beckers et al, 2018;Lachapelle et al, 2018;Yuen et al, 2018;Wang et al, 2018), and parcel locker facilities location problem (Deutsch & Golany, 2017).…”

Section: Theoretical Basismentioning

confidence: 99%

“…In order to identify the relationship between the location and socio-economic variables, we propose the indicator called InPop composed of the product of the average monthly household income and the population for each neighbourhood. Neighbourhood with a high combination of population and income are those with potential e-consumer demand (Oliveira et al, 2017;Beckers et al, 2018), referring to as high income-population areas.…”

Section: Research Approachmentioning

confidence: 99%

Analysis of accessibility from collection and delivery points: towards the sustainability of the e-commerce delivery

Oliveira

Sousa

et al. 2019

urbe, Rev. Bras. Gest. Urbana

View full text Add to dashboard Cite

The collection and delivery points (CDP) are an alternative to home deliveries and an important opportunity to reduce failed deliveries within urban areas. In this study, we propose to analyze the accessibility from CDPs located in commercial establishments (drugstores, gas stations, post offices, supermarkets, and malls) considered most attractive by e-consumers to receive this delivery solution. The methodological approach uses spatial analysis to identify the coverage area of the CDPs considering socioeconomic data and e-consumer preferences. Also, spatial tools to analyze the accessibility of CDPs were used, considering the transport infrastructure, the population location, and job opportunities location through different transport modes. The results indicated differences in levels of accessibility between the CDPs, highlighting the important associations among economic activities, land use patterns, and transport to plan for sustainable cities. The use of cluster analysis methods as a methodological approach is one contribution and can be replicated to support decision-making in other cities.

show abstract

Retail competition using free shopping shuttle bus strategies

Wang

Nie

2020

Manage Decis Econ

View full text Add to dashboard Cite

Free shopping shuttle bus (FSSB) is a common strategy in some industries such as super market and real estate. After illustrating the application conditions for FSSB, this study surveys competition effects of FSSB strategy on retailers by a duopoly spatial Bertrand model. The conclusions of this article show that the cost of FSSB and features of the market are two crucial factors to determine whether the FSSB is employed or not. When the demands are fixed, firms do not benefit from FSSB. But if the market is not fully covered, FSSB strategy has significant positive effects on market size improvement.

show abstract

Identifying the geography of online shopping adoption in Belgium

Cited by 67 publications

References 28 publications

Indonesian Demand for Online Shopping: Revisited

Indonesian Demand for Online Shopping: Revisited

Analysis of accessibility from collection and delivery points: towards the sustainability of the e-commerce delivery

Retail competition using free shopping shuttle bus strategies

Contact Info

Product

Resources

About