Safe delivery of goods and services with smart door locks: Unlocking potential use
Bibliographic record
Abstract
• Smart door locks make possible unattended delivery of goods and services. • Characteristics of potential users and non-users of smart door locks for goods and service delivery were studied to identify upscaling potential. • Results revealed that e-commerce innovation adoptions are affected by technological trust, social trust, and life management needs. • Results indicate that differentiated upscaling strategies is necessary to fully utilize smart door locks for service and goods delivery. • We propose an adopter typology which can be used to develop upscaling strategies for smart door locks for home delivery. The purpose of this paper is to identify the potential of using smart door locks in unattended home delivery of goods, and at home services (unattended and attended) by producing new knowledge on Potential adopters and Non-adopters. Survey data on Potential adopters and Non-adopters were statistically analysed to identify their 1) characteristics (sociodemographic, interpersonal trust and technological literacy), 2) stated demand for unattended home delivery of goods and 3) attitudes regarding in-home services using smart door-locks. Results suggest that potential users are resourceful and more sociable than non-adopters. Furthermore, they have a higher problem perception. Potential adopters are more positive to let in cleaners, craftsmen, healthcare personnel, service personnel, in-fridge delivery services and pet sitters into their home unattended using smart door locks. Regarding goods, they are more positive towards delivery of sports equipment and furniture and appliances. Due to the differentiated needs of Potential adopters and Non-adopters, we propose a typology based on three dimensions ( Technological trust, Social trust and Life management needs ). Increased understanding of potential users’ delivery preferences can be used in the smart door lock market development. The proposed typology can e.g. be used in the upscaling of smart door locks for home delivery of goods and services by diversifying strategies to meet varying adopter needs. A successful unattended delivery system behind closed door can reduce the number of failed deliveries, porch piracy, and unnecessary trips to let in service providers, and might enhance perceived flexibility and convenience of consumers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".