A customer-oriented organisational diagnostic model based on data mining of customer-complaint databases
Highlights
► We develop a customer-oriented organisational diagnostic model based on data mining of customer-complaint databases. ► The model includes four analytical stages. ► They are primary-diagnosis stage, advanced-diagnosis stage, review stage, and action stage.
Introduction
Customer satisfaction is recognised as one of the most important key performance indicators of success. However, it is always difficult to eliminate all causes of customer dissatisfaction and complaints. Customer satisfaction is influenced by such a variety of factors—including the attributes of a product or service, the individual needs of customers, and the service quality provided by front-line personnel—that even a fully ‘customer-focused’ service program cannot eliminate all product or service failures.
Most organisations are aware that service failures must be handled appropriately to avoid harm to the organisation’s goodwill and profits (Hart, Heskett, & Sasser, 1990). Service recovery has thus become an increasingly important issue to prevent the loss of customers (Kelley and Davis, 1994, McColl-Kennedy and Sparks, 2003, McColl-Kennedy et al., 2003, Sparks and McColl-Kennedy, 1998, Varela-Neira et al., 2008). The term ‘service recovery’ refers to remedial actions that are taken to re-establish the satisfaction of customers when product or service failure has occurred (Chaston, 1993, Zemke and Bell, 1990). Many studies have demonstrated that effective service recovery can transform negative evaluations into positive impressions, thus maintaining good relationships with customers (Hoffman et al., 1995, Karatepe, 2006, Kelley et al., 1993, Maxham Iii, 2001, Smith et al., 1999, Sparks and McColl-Kennedy, 1998, Spreng et al., 1995). Appropriate service recovery has also been shown to enhance the trust of customers and increase their willingness to re-purchase (Hung and Wong, 2007, Maxham Iii, 2001, Spreng et al., 1995, Tax and Brown, 1998, Tax and Brown, 2000, Yu and Dean, 2001). Conversely, ineffective service recovery is one of the main causes of switching behaviour (Keaveney, 1995).
Most studies of service recovery (Barlow and Moller, 1996, Boshoff, 1997, Boshoff and Leong, 1998, Johnston and Fern, 1999, Keaveney, 1995, Tax and Brown, 1998, Tax and Brown, 2000, Wirtz and Mattila, 2004) have focused on the effectiveness of specific remedial actions—such as exchanges of goods, apologies, or offers of compensation. Relatively few have studied the question of how to improve the service system by learning from the experiences of previous service failures and avoiding repetitions. It is the contention of the present study that the prevailing focus on remedial actions and compensation for a service failure is essentially a passive and reactive approach to the problem of service failure, whereas efforts to improve the existing service system represent a creative and proactive strategy.
To improve a service system and minimise service failures, it is necessary to collect and analyse customer-complaint data periodically and comprehensively. Although some studies have indicated that improvement actions should be based on customer complaints (Bosch and Enríquez, 2005, Gustafsson et al., 1999, Tax and Brown, 2000, Tax et al., 1998), these authors did not propose a comprehensive model to identify the sources of service failures. Chen et al., 2005, Chen et al., 2006, Chen et al., 2004, who have investigated the importance of service-system design and management, also emphasised the need to make better use of customer-complaint databases to diagnose failures in service systems.
Against this background, the present study seeks to establish a customer-oriented organisational diagnostic model of service failure based on customers’ complaints. The proposed ‘PARA’ model takes its name from the initial letters of the four stages of the model: (i) ‘primary diagnosis’; (ii) ‘advanced diagnosis’; (iii) ‘review’; and (iv) ‘action’. The diagnostic model provides a systematic analysis of service failures based on the customer complaint database. Data-mining techniques are then utilised to establish correlations between the identified categories of customer complaints. The model then develops a strategy of improvement actions for the service system. The model provides constructive customer-focused recommendations for improvements in service delivery through scientific analyses of service failures.
The remainder of this paper is organised as follows. The next section reviews the relevant literature on organisational diagnosis. The development of the proposed ‘PARA’ model is then presented. The practical efficacy of the proposed model is then demonstrated in an empirical case study of public-sector services in Taiwan. The paper concludes with a summary of the main advantages of the model and the implications for future research.
Section snippets
Literature review of organisational diagnosis
The term ‘organisational diagnosis’ is commonly used to refer to a process whereby an external consultant enters an organisation, collects valid data about human experiences within the organisation, and feeds that information back to the organisation to promote increased understanding of the organisation by its members (Alderfer, 1981). The purpose of organisational diagnosis is to establish a widely shared understanding of an organisation, and, based upon that understanding, to determine
The ‘PARA’ diagnostic model
As noted above, the present study contends that a proactive approach needs to be adopted in dealing with customer complaints and identifying the ‘voice of the customer’ (VOC). In accordance with this view, a customer-oriented organisational diagnostic model based on a comprehensive analysis of customer complaints is developed in this study.
The proposed model, which is illustrated in Fig. 1, is designated the ‘PARA’ model from the initial letters of the four stages in the model’s diagnostic
Research setting
To demonstrate the efficacy of the proposed ‘PARA’ model, an empirical case study was conducted using the complaint database of public-sector service agencies in Tao-Yuan county, Taiwan. The aim of this exercise in organisational diagnosis was to utilise the complaints of citizens to ascertain the reasons for failures in the service systems of the Tao-Yuan county government agencies.
More than 80 government agencies provide a variety of services (including household registration, land
Conclusions
The ‘PARA’ (primary diagnosis, advanced diagnosis, review, action) model presented in this paper seeks to have the voice of customer (VOC) taken into account in the diagnosis of failures within a service system. Based on the data mining analysis of a customer complaint database, the model enables a comprehensive diagnosis of service failures and develops appropriate improvement actions.
The empirical case study reported in this paper has demonstrated the practical efficacy of the four stages of
Acknowledgements
This research is supported by National Science Council, Taiwan (NSC-97-2221-E-155-051-MY3). We also thank Miss. Hsiu-Chu Liang (Section leader in Tao-Yuan County Government, Taiwan) and colleagues for their assistance.
References (49)
- et al.
Course planning of extension education to meet market demand by using data mining techniques – An example of Chinkuo technology university in Taiwan
Expert Systems with Applications
(2008) - et al.
A typology of retail failures and recoveries
Journal of Retailing
(1993) - et al.
A model for diagnosing organizational behavior
Organizational Dynamics
(1980) The marketing orientation of OD
The Journal of Applied Behavioral Science
(1981)- et al.
The systems paradigm in organizational theory: Correcting the record and suggesting the future
Academy of Management Review
(1987) - et al.
A Complaint Is A Gift
(1996) The multiple cognitions and conflicts associated with second order organizational change
- et al.
Reframing Organizations: Artistry
(1991) - et al.
TQM and QFD: Exploiting a customer complaint management system
International Journal of Quality and Reliability Management
(2005) An experimental study of service recovery options
International Journal of Service Industry Management
(1997)
Empowerment, attribution and apologising as dimensions of service recovery. An experimental study
International Journal of Service Industry Management
Delivering customer satisfaction within SME client-banker relationship
The Service Industries Journal
An empirical analysis of customer-oriented service activities in the Taiwanese public sector
Total Quality Management and Business Excellence
ERA model: A customer-orientated organizational change model for the public service
Total Quality Management and Business Excellence
A customer-oriented service-enhancement system for the public sector
Managing Service Quality
The stakeholder theory of the corporation: Concepts, evidence, and implications
Academy of Management Review
Knowledge discovery in databases: An overview
Ai Magazine
Customer focused service development in practice: A case study at Scandinavian Airlines System (SAS)
International Journal of Service Industry Management
Organizations: Structures, Processes, and Outcomes
Principles of Data Mining
Diagnosing Organizations: Methods, Models, and Processes
Organizational Diagnosis and Assessment: Bridging Theory and Practice
The profitable art of service recovery
Harvard business review
Tracking service failures and employee recovery efforts
Journal of Services Marketing
Cited by (25)
Identifying individual expectations in service recovery through natural language processing and machine learning
2019, Expert Systems with ApplicationsCitation Excerpt :Some scholars have applied machine learning in complaints processing. For example, Chen, Shie, and Yu (2012) developed a customer-oriented organizational diagnostic model based on data mining of customer-complaint databases. Elmessiry et al. (2017) used machine learning methods to detect whether a patient complaint is associated with a physician or his/her medical practice.
Effects of Organizational Macroergonomic Compatibility Elements over Manufacturing Systems’ Performance
2015, Procedia ManufacturingImproving employment services management using IPA technique
2013, Expert Systems with ApplicationsCitation Excerpt :Most methods of service quality measurement can be traced back to the service industry. It is imperative that an organization properly handle every customer complaint stemming from poor services in order to avoid damages inflicted on its goodwill or profits (Chen, Shie, & Yu, 2012). The market value of an institution focused on customer services lies in the way it meets the target customers’ needs (Bronzo, de Oliverira, & McCormack, 2012).
Data mining of customer reviews to analyse the consumer experience in hospitals
2023, Research Square