After-sales services and aftermarket support: a systematic review, theory and future research directions

Durugbo, Christopher

doi:10.1080/00207543.2019.1693655

Cited by 61 publications

(26 citation statements)

References 272 publications

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“…Simultaneously, Kaura et al, (2015); Durugbo (2019) evaluated the effect of service quality, fair price, and convenience of service on customer loyalty and customer satisfaction variable in Indian retail banking. The results of this study exhibited that service quality, reasonable price, and convenience of service affect customer loyalty.…”

Section: Introductionmentioning

confidence: 99%

Determining the increased numerical value of customer satisfaction, which has been impacted by latent and observed factors in after-sales service in the automotive industry, based on System Dynamics Method. (A Case study in car manufacturer)

Soltani

Sobhani

Najafi

2021

JER is an international, peer-reviewed journal that publishes f

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Contextualized in the field of customer satisfaction in after-sales service in the automotive industry, the authors contribute to increasing customer satisfaction in three fundamental ways. First, by offering a new conceptual framework that integrates prior studies and Delphi methodology to survey the automotive industry's experts to identify essential and influential variables on customer satisfaction. Second, by developing a system dynamics and modeling method to evaluate the effect of these variables on each other, and unlimitedly investigate these variables' impact on customer satisfaction. Third, by offering an improvement scenario, we indicated what combination of observed and latent variables leads to a numerical increase in the customer satisfaction index. The survey's analytical results suggest that the cost of services and repair time is reduced by 30%, and the time of car acceptance in the repair shop is reduced by 20%. At the same time, the satisfaction with repair order description is increased by 30%, resulting in a 5% increase in numerical satisfaction with the overall service. Heretofore did not use a dynamic system model to determine the numerical amount of increasing customer satisfaction with after-sales service in the automotive industry. Therefore, the results of this study can be used as a basis for developing new policies in customer relationship management in automotive companies to increase customer satisfaction. This fact can lead to an increase in sales and ultimately the company's profitability. The article contributes to future research by quantitatively determining the number of changes in the significant factors to increase customer satisfaction.

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Section: Introductionmentioning

confidence: 99%

Determining the increased numerical value of customer satisfaction, which has been impacted by latent and observed factors in after-sales service in the automotive industry, based on System Dynamics Method. (A Case study in car manufacturer)

Soltani

Sobhani

Najafi

2021

JER is an international, peer-reviewed journal that publishes f

View full text Add to dashboard Cite

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“…For management priorities, the review applies clustering to capture themes that underscore focal points for management and interventions to enhance institutional innovation. Applying conceptual and thematic analysis is consistent with the systematic review methodology (Khan et al 2003 ; Durugbo 2020 ) and enables the review to present the findings in a form suitable for dissemination. The next section reports the findings of the synthesis of articles.…”

Section: Methodsmentioning

confidence: 90%

Systematic review of institutional innovation literature: towards a multi-level management model

AlMalki

Durugbo

2022

Manag Rev Q

Self Cite

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Institutional innovation creates smart institutions that idiosyncratically thrive in a world of exponential change. Through policy-driven interventions and experiential learning, managers of institutions become adept at delivering praxis- and crisis-driven innovations required for survival and success. Similarly, the management of institutional innovation remains an interest in research due to links of this form of innovation to economic growth, and the demands of on-going major socioeconomic transformations due to technological advances, increased occurrences of major crises, and emerging socioeconomic challenges. Accordingly, a key question arising from the literature concerns the range of determinants and priorities that influence institutional innovation for delivering society value. Thus, the onus is on scholarship to capture and advance knowledge for harnessing the potency of institutional innovation. The purpose of this article is to analyse the current state of research on institutional innovation. Using the systematic review methodology, we identify and critically appraise 485 peer-reviewed scientific publications between 1969 and 2021. The review finds key determinants and management priorities with a view to developing a multi-level management model of institutional innovation. Guided by insights from the review, the article sets a research agenda for future management studies of institutional innovation.

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“…a temporal contractual assignment of the original equipment manufacturers (OEM) to offer uphold for an equipment. Figure 1 presents the main after sales activities such as the "provision of field technical assistance, spare parts distribution, and customer care and accessories sale" (Durugbo, 2020).…”

Section: Related Work Home Appliance After Sales Servicesmentioning

confidence: 99%

Data Mining Approach Improving Decision-Making Competency along the Business Digital Transformation Journey: A Case Study – Home Appliances after Sales Service

Mydyti

2021

SEEU Review

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Data mining, as an essential part of artificial intelligence, is a powerful digital technology, which makes businesses predict future trends and alleviate the process of decision-making and enhancing customer experience along their digital transformation journey. This research provides a practical implication – a case study - to provide guidance on analyzing information and predicting repairs in home appliances after sales services business. The main benefit of this practical comparative study of various classification algorithms, by using the Weka tool, is the analysis of information and the prediction of repairs in the home appliances after sales services business. The comparison of algorithms is performed considering different parameters, such as the mean absolute error, root mean square error, relative absolute error and root relative squared error, receiver operating characteristic area, accuracy, Matthews’s correlation coefficient, precision-recall curve, precision, F-measure, recall and statistical criteria. Five classification algorithms such as the Naive Bayes, J48, random forest, K-Nearest Neighbor, and logistic regression were implemented in the dataset. J48 has proved to provide the best accuracy and the lowest error among the other examined algorithms applied to a home appliances after sales services dataset to predict repairs based on product guarantee period. The extracted information and results of an after sales services business by using data mining techniques prove to alleviate the process of streamlining decision-making and provide reliable predictions, especially for the customers, as well as increase businesses’ efficiency along their digital transformation journey.

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After-sales services and aftermarket support: a systematic review, theory and future research directions

Cited by 61 publications

References 272 publications

Determining the increased numerical value of customer satisfaction, which has been impacted by latent and observed factors in after-sales service in the automotive industry, based on System Dynamics Method. (A Case study in car manufacturer)

Determining the increased numerical value of customer satisfaction, which has been impacted by latent and observed factors in after-sales service in the automotive industry, based on System Dynamics Method. (A Case study in car manufacturer)

Systematic review of institutional innovation literature: towards a multi-level management model

Data Mining Approach Improving Decision-Making Competency along the Business Digital Transformation Journey: A Case Study – Home Appliances after Sales Service

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