Background In the context of booming e-commerce and associated logistics flows, there is a considerable challenge to support the future of volumes, specifically more towards home deliveries by logistics service providers (LSP). There are means of addressing this challenge by identifying the key factors that influence consumer behaviour and lead to better adoption by meeting their convenience through right self collection end points setups thus decreasing the logistics costs, meeting sustainability targets and also efficiencies for logistics service provider operations. Purpose The purpose of this study is to study and investigate the convenience factors of self-collection endpoints and associated levels that influence consumer preferences for logistics services to use self-collection last-mile endpoint in Sweden and also associate with observed behaviour across different demographic segments. Methods For research, quantitative research was done using conjoint analysis. Data was collected using a questionnaire sent in Google forms from volunteers, designed through an orthogonal designed based profile to rate the relevance and interest it generated. Results were based on 161 respondents' feedback on 16 such profiles (autogenerated in the SPSS platform). Analyses on existing historical parcel data of the logistics service provider along with the demographic data to build decision-tree models which supports determining the crucial attributes which influence home deliveries and also identify the potential site for trialability by LSP to support better decision-making aligned with the new Innovation diffusion into usage. Conclusions The research has shown that the collection distance is the most crucial convenience factor which can drive/steer consumers to use self-collection endpoints by being relevant in the context of convenience factors to be considered as an alternate to home delivery, followed by handling time. Respondents were willing to compromise on home deliveries if distance was within their expectations, such as <300m from the study conducted. During the thesis work, decision-tree models have also been developed, which has shown relationship/dependency between demographics to different delivery methods like home vs. service points across different geographies and factors influencing it. It has been further observed that different influencing attributes play a significant role across geographical type of delivery locations, such as urban, sub-urban volume data.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-455588 |
| Date | January 2021 |
| Creators | Kotty, Venkata Mukhyaprana Sree Hari Kiran |
| Publisher | Uppsala universitet, Industriell teknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | SAMINT-MILI ; 21055 |
Page generated in 0.0014 seconds