Smart service efficiency: Evaluation of cultural trip planning service

2016 ◽  
Author(s):  
Kirill A. Kulakov ◽  
Oksana B. Petrina ◽  
Anastasiya A. Pavlova
Keyword(s):  
Efficiency Evaluation ◽  
Planning Service ◽  
Trip Planning ◽  
Service Efficiency ◽  
Smart Service

An Approach to Efficiency Evaluation of Services With Smart Attributes

2019 ◽  
pp. 1305-1326
Author(s):  
Kirill Kulakov
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Efficiency Evaluation ◽  
Trip Planning ◽  
Smart Services ◽  
Time Utilization ◽  
Smart Service ◽  
Services Implementation ◽  
Tourism Services

Nowadays amount of “smart” services in e-Tourism is growing rapidly. This is due to widespread use of mobile devices with new input methods and large amount of digitized data. In addition, Internet of Things and Big Data analytics has a major impact on development of e-Tourism services and cultural heritage services. At the same time the smart services implementation requires complex methods and high cost of their creation. Thereby there is an actual problem to estimate efficiency of smart services. This paper presents an approach to efficiency evaluation of services with smart attributes. The evaluation is based on service's work time utilization and required manual work. For each used attribute the execution scenario, ordinary (non-smart) service for comparison and used estimates are defined. Each estimate is calculated by taking into account the user's experience. Presented approach is relevant for smart services with big data analytics. The demonstration of the approach was carried out using Cultural trip planning service with possible ordinary services.

An Approach to Efficiency Evaluation of Services with Smart Attributes

2017 ◽  
Vol 8 (1) ◽  
pp. 64-83 ◽  
Author(s):  
Kirill Kulakov
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Efficiency Evaluation ◽  
Trip Planning ◽  
Actual Problem ◽  
Smart Services ◽  
Time Utilization ◽  
Smart Service ◽  
Services Implementation

Nowadays amount of “smart” services in e-Tourism is growing rapidly. This is due to widespread use of mobile devices with new input methods and large amount of digitized data. In addition, Internet of Things and Big Data analytics has a major impact on development of e-Tourism services and cultural heritage services. At the same time the smart services implementation requires complex methods and high cost of their creation. Thereby there is an actual problem to estimate efficiency of smart services. This paper presents an approach to efficiency evaluation of services with smart attributes. The evaluation is based on service's work time utilization and required manual work. For each used attribute the execution scenario, ordinary (non-smart) service for comparison and used estimates are defined. Each estimate is calculated by taking into account the user's experience. Presented approach is relevant for smart services with big data analytics. The demonstration of the approach was carried out using Cultural trip planning service with possible ordinary services.

A trip planning service acceptance model for young mainland Chinese tourists

2020 ◽  
Vol 11 (2) ◽  
pp. 327-342
Author(s):  
Vincent Ting Pong Cheng ◽  
Chen-Kuo Pai
Keyword(s):  
Social Influence ◽  
Partial Least Square ◽  
Least Square ◽  
Planning Service ◽  
Trip Planning ◽  
Content Type ◽  
Mainland Chinese ◽  
Chinese Tourists ◽  
Acceptance Model ◽  
Online Travel

Purpose Online travel agencies (OTAs) have been offering tourists trip planning services (TPS) for more than a decade. However, they are less popular than other online travel services such as metasearch with price comparison. This study aims to investigate why TPS on the internet, although important to tourists, are not well accepted by young mainland Chinese tourists. Design/methodology/approach A trip planning service acceptance model (TPSAM) was constructed and tested by inviting participants to take part in a trial using the TPS of a China OTA and then participants were asked to complete a questionnaire based on their user experience. Partial least square technique was used to perform a path analysis on the model. Findings Social influence and effort expectancy have significant direct influence on reuse intention. Social influence increases the trust level of the tourists on the TPS and effort expectancy’s strong influence on joy suggest that a joyful and effortless experience is critical for tourists to consider reusing the TPS. Practical implications The findings could provide some insight to the OTAs on improving their TPS. For instance, OTAs should let tourists feel that the TPS requires little effort and is fun to use and more promotion is needed through social media. Originality/value Although trip planning is essential for tourists in achieving a delightful travel experience, few studies have examined the adoption of Web-based TPS. This study contributes to the literature by establishing a TPSAM and extends previous work by showing that a causal relationship exists between social influence and trust in the service acceptance context.

scholarly journals Efficiency Evaluation of China’s Public Sports Services: A Three-Stage DEA Model

2021 ◽  
Vol 18 (20) ◽  
pp. 10597
Author(s):  
Pengyu Ren ◽  
Zhaoxia Liu
Keyword(s):  
Technical Efficiency ◽  
Environmental Variables ◽  
Positive Impact ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Fitness Program ◽  
Dea Model ◽  
Service Efficiency ◽  
The Impact

Improving the level of public sports services enhances citizens’ physical fitness by implementing the national fitness program. A systematic and scientific efficiency evaluation is a prerequisite for optimizing and improving the level of public sports services in China. Based on data of the Chinese Statistic Yearbook, this study adopted the three-stage data envelopment analysis (DEA) model to measure and analyze the efficiency of public sports services in 31 provinces in China in 2016. To analyze the efficiency of public sports services, technical efficiency was decomposed into pure technical efficiency and scale efficiency. Simultaneously, environmental variables were added to improve accuracy. The results showed that scale efficiency was overestimated, and external technical efficiency was underestimated, before the elimination of external factors and environmental variables. Environmental factors significantly impacted the efficiency of public sports services. Regional gross domestic product (GDP) had a potentially positive impact, while population size partially restricted public sports service efficiency. After eliminating the impact of environmental and random factors, the comprehensive efficiency, pure technical efficiency, and scale efficiency of public sports services all showed improvement in varying degrees. The results provide beneficial insights for the formulation of rational improvement policies for public sports services.

Bus Trip Planning Service Based on Real Time Data

2011 ◽  
Author(s):  
Jiashun Liu ◽  
Yu Yuan ◽  
Feng Li ◽  
Wei Ding
Keyword(s):  
Real Time ◽  
Time Data ◽  
Planning Service ◽  
Trip Planning ◽  
Real Time Data

Research and Analysis of IT Customer Service System Structure

2014 ◽  
Vol 513-517 ◽  
pp. 2086-2089
Author(s):  
Qiang Chen ◽  
Xin Ming Xiang
Keyword(s):  
Customer Service ◽  
Service Management ◽  
Service System ◽  
System Structure ◽  
Standard Theory ◽  
Planning Service ◽  
Service Efficiency ◽  
Customer Service Management ◽  
Customer Services ◽  
The Cost

The core ideal of IT customer service management is that all business activities of the enterprise shall base on fulfilling with customers needs, and treat providing products or services tailored to customers needs as the enterprises obligation, and treat customers satisfaction as the enterprises objective. By referencing to international standard theory in ISO20000 and combining with the real work situation of IT customer service, this article analyses and gives the overall structure and main contents of IT customer service system, and aimed at planning service catalogues, service specifications, service procedures etc., so to ensure to provide safe, stable and high quality IT customer services to customers to meet mutual agreements, and to increase the cost efficiency of IT resource investment, and to improve service efficiency and customer satisfaction.

scholarly journals Novel Service Efficiency Evaluation and Management Model

2021 ◽  
Vol 11 (20) ◽  
pp. 9395
Author(s):  
Mingyuan Li ◽  
Lung-Yu Lin ◽  
Kuen-Suan Chen ◽  
Ting-Hsin Hsu
Keyword(s):  
Innovation Management ◽  
Operation Time ◽  
Management Model ◽  
Point Estimate ◽  
Efficiency Evaluation ◽  
Sampling Errors ◽  
Control Block ◽  
Operation Efficiency ◽  
Service Efficiency ◽  
Service Operation

Numerous scholars have invested in the research of service innovation management, hoping to find a more objective and scientific service efficiency evaluation and management model so as to stride forward towards the goal of smart innovation management. In the service operating system, the multi-workstation service operation is one of the common service operation models. Some studies have pointed out: apart from a good service attitude, the service operation time of each workstation is a key factor which measures the performance of the workstation’s service operation. Therefore, this paper proposed a standardized concept with a service operation efficiency evaluation index. This index is not only convenient and easy-to-use, but it also has a one-to-one mathematical relationship with the performance achievement rate. Next, the radar evaluation chart was employed to evaluate the service efficiency of each workstation. First, according to the upper confidence limit and the required value of the index, the minimum value (MV) of the index estimator was derived and marked on each radar line; at the same time, all MVs were connected to form a control block. When the point estimate of the index does not fall into the control block of the radar chart, it represents that the service operation efficiency of the workstation has not reached the required level, so it needs to be improved. Because this model can directly compare the point estimate of the index with the MV, it can judge whether the service operation efficiency reaches the required level. In this way, the advantage of simple and easy-to-use point estimate can be maintained, and the risk of misjudgment caused by sampling errors can be reduced as well, which is helpful for the service industry to move towards the goal of intelligent innovation management. This method is not only applied to the performance evaluation of the multi-workstation service operation process but also applicable to the performance evaluations of other service operations.

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