Person Service Items Fit Based on the Novel KNN Algorithm in Household Service Industry

2020 ◽  
Vol 09 (01) ◽  
pp. 55-60
Author(s):  
虹影 朱
Keyword(s):  
Service Industry ◽  
The Novel

scholarly journals Characterization and Design for Last Mile Logistics: A Review of the State of the Art and Future Directions

2021 ◽  
Vol 12 (1) ◽  
pp. 118
Author(s):  
Hyeong Suk Na ◽  
Sang Jin Kweon ◽  
Kijung Park
Keyword(s):  
Service Industry ◽  
Decision Makers ◽  
The Novel ◽  
Future Directions ◽  
Environmentally Sustainable ◽  
Market Risks ◽  
Last Mile ◽  
Delivery Technique ◽  
Depth Analysis ◽  
Delivery Services

One of the most challenging problems in last mile logistics (LML) has been the strategic delivery due to various market risks and opportunities. This paper provides a systematic review of LML-related studies to find current issues and future opportunities for the LML service industry. To that end, 169 works were selected as target studies for in-depth analysis of recent LML advances. First, text mining analysis was performed to effectively understand the underlying LML themes in the target studies. Then, the novel definition and typology of LML delivery services were suggested. Finally, this paper proposed the next generation of LML research through advanced delivery technique-based LML services, environmentally sustainable LML systems, improvement of LML operations in real industries, effective management of uncertainties in LML, and LML delivery services for decentralized manufacturing services. We believe that this systematic literature review can serve as a useful tool for LML decision makers and stakeholders.

scholarly journals Between comments and repeat visit: capturing repeat visitors with a hybrid approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jina Kim ◽  
Yeonju Jang ◽  
Kunwoo Bae ◽  
Soyoung Oh ◽  
Nam Jeong Jeong ◽  
...  
Keyword(s):  
Machine Learning ◽  
Service Industry ◽  
Hybrid Approach ◽  
Learning Approaches ◽  
The Novel ◽  
Content Type ◽  
Machine Learning Classifiers ◽  
Learning Classifiers ◽  
Novel Approach ◽  
Repeat Visit

PurposeUnderstanding customers' revisiting behavior is highlighted in the field of service industry and the emergence of online communities has enabled customers to express their prior experience. Thus, purpose of this study is to investigate customers' reviews on an online hotel reservation platform, and explores their postbehaviors from their reviews.Design/methodology/approachThe authors employ two different approaches and compare the accuracy of predicting customers' post behavior: (1) using several machine learning classifiers based on sentimental dimensions of customers' reviews and (2) conducting the experiment consisted of two subsections. In the experiment, the first subsection is designed for participants to predict whether customers who wrote reviews would visit the hotel again (referred to as Prediction), while the second subsection examines whether participants want to visit one of the particular hotels when they read other customers' reviews (dubbed as Decision).FindingsThe accuracy of the machine learning approaches (73.23%) is higher than that of the experimental approach (Prediction: 58.96% and Decision: 64.79%). The key reasons of users' predictions and decisions are identified through qualitative analyses.Originality/valueThe findings reveal that using machine learning approaches show the higher accuracy of predicting customers' repeat visits only based on employed sentimental features. With the novel approach of integrating customers' decision processes and machine learning classifiers, the authors provide valuable insights for researchers and providers of hospitality services.

The novel steroidal glycoside from the dried bulb of Allium Macrostemon Bunge inhibits platelet activation

2010 ◽  
Vol 34 (8) ◽  
pp. S33-S33
Author(s):  
Wenchao Ou ◽  
Haifeng Chen ◽  
Yun Zhong ◽  
Benrong Liu ◽  
Keji Chen
Keyword(s):  
Platelet Activation ◽  
The Novel ◽  
Steroidal Glycoside ◽  
Allium Macrostemon

The Involuntary Capture of Attention by Sound

2010 ◽  
Vol 57 (1) ◽  
pp. 68-76 ◽  
Author(s):  
Fabrice B. R. Parmentier ◽  
Pilar Andrés
Keyword(s):  
Older Adults ◽  
Mismatch Negativity ◽  
Visual Task ◽  
The Novel ◽  
Auditory Oddball ◽  
Current Trial ◽  
Electrophysiological Responses ◽  
Electrophysiological Studies ◽  
The Cross ◽  
Task Sets

The presentation of auditory oddball stimuli (novels) among otherwise repeated sounds (standards) triggers a well-identified chain of electrophysiological responses: The detection of acoustic change (mismatch negativity), the involuntary orientation of attention to (P3a) and its reorientation from the novel. Behaviorally, novels reduce performance in an unrelated visual task (novelty distraction). Past studies of the cross-modal capture of attention by acoustic novelty have typically discarded from their analysis the data from the standard trials immediately following a novel, despite some evidence in mono-modal oddball tasks of distraction extending beyond the presentation of deviants/novels (postnovelty distraction). The present study measured novelty and postnovelty distraction and examined the hypothesis that both types of distraction may be underpinned by common frontally-related processes by comparing young and older adults. Our data establish that novels delayed responses not only on the current trial and but also on the subsequent standard trial. Both of these effects increased with age. We argue that both types of distraction relate to the reconfiguration of task-sets and discuss this contention in relation to recent electrophysiological studies.

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