Boundary Interaction Between Service Organizations and Their Publics: A Study of Teacher-Parent Relationships

Social Forces ◽  
1976 ◽  
Vol 55 (2) ◽  
pp. 471-492 ◽  
Author(s):  
R. G. Corwin ◽  
T. C. Wagenaar
2006 ◽  
Vol 58 (3) ◽  
pp. 303-316 ◽  
Author(s):  
Panayiotis Angelides ◽  
Louiza Theophanous ◽  
James Leigh

Author(s):  
S.U. Lyapina ◽  
◽  
V.N. Tarasova ◽  
V.B. Ruchkin ◽  
E.O. Koscheeva ◽  
...  

The quality issues of new services directly affect the competitiveness of service organizations. However, the introduction of new services to the market is often limited only to the construction of the logistics of business processes, and the design applies only to technological equipment and infrastructure, the quality of which ultimately does not always ensure the quality of the services provided. At the same time, quality management affects mainly operational aspects, that is, it covers the later stages of the service life cycle. In resource-intensive service industries (for example, transport, communications, etc.), the high cost of equipment and infrastructure reduces the possibility of changes in service delivery technologies to improve their quality, which leads to inefficiency and market failures due to the fact that the new service does not match the real needs of customers. Despite this, forecasting and planning the quality of a service at the stage «making a decision» to launch a new service on the market remains largely without sufficient attention. The authors prove the need to design the quality of services at the stage «making a decision» to bring new services to the market. The purpose of the article is to describe the approach developed by the authors to assessing the quality of projected services at the early stages of their life cycle, which makes it possible to integrate qualitative and quantitative indicators of the future service and take into account the forecast requests of customers. The proposed approach has two features: (1) forecasting customer requirements for the quality of services is based on the results of machine learning based on data on existing and potential customers, as well as on the basis of the accumulated knowledge base of customer experience and expert opinions; (2) multi-criteria optimization is used, while some of the optimized parameters are discrete and high-quality. In conclusion, the authors demonstrated the advantages of the developed model on the examples of transport and logistics business in the field of passenger and freight transportation in Russia.


2020 ◽  
Author(s):  
Nicolò Maria della Ventura ◽  
Szilvia Kalácska ◽  
Daniele Casari ◽  
Thomas Edward James Edwards ◽  
Johann Michler ◽  
...  

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