On the impact of analyzing customer information and prioritizing in a service system

Dobson, Gregory; Sainathan, Arvind

doi:10.1016/j.dss.2011.02.006

Cited by 22 publications

(11 citation statements)

References 15 publications

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“…This requires the inclusion of a triage (or "sorting") step, which may result in a reduction of work at the treatment step. As such, it may impact the service rate of the treatment step, and opens up the opportunity to use different waiting time targets for different priority classes ( [5]). In addition, we plan to introduce shift constraints in the model, to further increase its practical relevance.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Controlling excessive waiting times in small service systems with time-varying demand: An extension of the ISA algorithm

Defraeye

Nieuwenhuyse

2013

Decision Support Systems

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In many service systems, the arrival pattern is not constant throughout the day. This raises the question how staffing decisions should be adapted in view of controlling customer's waiting times. Assuming a single-stage queueing system with general abandonment and service times and time-varying demand for service, we suggest a method inspired by the simulation-based Iterative Staffing Algorithm (ISA) proposed by Feldman et al. (2008). The main advantage of our extension is that it enables to control the probability of experiencing an excessive waiting time, in particular in small systems.

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Section: Conclusion and Future Researchmentioning

confidence: 99%

Controlling excessive waiting times in small service systems with time-varying demand: An extension of the ISA algorithm

Defraeye

Nieuwenhuyse

2013

Decision Support Systems

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“…In Dobson and Sainathan (2011), the authors examine prioritization in the service system and analyse whether prioritization can improve system performance where there are two different classes of customers for service time: first, customers who require urgent services have a high waiting cost, and second, customers who require non-urgent service have a low waiting cost.…”

mentioning

confidence: 99%

An empirical study of a novel managing customer power model and business performance in the mobile service industry

Alotaibi

Liu

2014

Business Process Management Journal

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Purpose – The purpose of this paper is to investigate the impact of dividing the companies’ customers into different priority groups to be served according to their payment history and feedback on the business performance areas: service quality (SQ), business process time (BPT), business process cost (BPC) and customer satisfaction (CS). Design/methodology/approach – A new numerical model to improve CS service waiting time according to their priority queue class, particularly customers in the high priority queue class will be proposed. To validate the proposed numerical model, a call centre at the selected telecommunication company is used as a case study. An empirical analysis based on data from 130 business and IT managers is used to evaluate and investigate if it has an impact on business process (BP) performance. Bivariate correlation analysis was used to test four hypotheses. The results were subjected to reliability and validity analyses. Findings – The results show that managing customer power is positively associated with BP performance. Furthermore, the results indicate that by using the proposed numerical model, the customers’ satisfaction can be improved. Research limitations/implications – The paper has some limitations as it is only tested on one real business organizations and one BP service. Furthermore, the study was conducted only in telecommunication companies. The questionnaires were answered only by IT and business managers in Saudi Arabian telecommunication companies. Therefore, the results cannot be used as a standard and might not be directly transferrable to any sized firm and any other country. Moreover, the results may be affected by common method variance as the authors collected the data from participants by using the same survey and at the same time. Social implications – The results of this research provide important evidence for business managers and business analysts that managing customers power can enhance the business performance. Originality/value – To date, there is only a few researches have been conducted in the area of separating customers into different priority groups to provide services according to their required delivery time, payment history and feedback. However, most of them have not been evaluated in the business environment. Moreover, no previous study has attempted to empirically demonstrate the relationship between creating a BP model which can manage customer power, SQ, BPT, BPC and CS.

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“…While they discuss prioritization or diagnostics in a more general service system, they both mention that their analysis may also be relevant for ED triage. While most studies on prioritization assume that sorting is free and instantaneous, Dobson & Sainathan (2011) state that prioritization has both benefits and costs. The benefits are that more urgent patients are treated faster and that some information about the patient may already be obtained so that the following processes go more smoothly.…”

Section: Triagementioning

confidence: 99%

Improving Patient Flow in Emergency Departments with OR Techniques: A Literature Overview

Carmen

Nieuwenhuyse

2014

SSRN Journal

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On the impact of analyzing customer information and prioritizing in a service system

Cited by 22 publications

References 15 publications

Controlling excessive waiting times in small service systems with time-varying demand: An extension of the ISA algorithm

Controlling excessive waiting times in small service systems with time-varying demand: An extension of the ISA algorithm

An empirical study of a novel managing customer power model and business performance in the mobile service industry

Improving Patient Flow in Emergency Departments with OR Techniques: A Literature Overview

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