Development of decision support matrix: determining the effectiveness of service recovery level in e-tailing

Service failures occur even in the best run service industry. These service failures tend to effect the satisfaction of the customers, which becomes one of the reasons for the customers to shift to another service provider. With that, an effective service recovery strategy plays a vital role in miti...

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Main Authors: Lim, Marvin Alexander S., Tan, Natasha Dominique G., Yeung, Clark Dustin T.
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Language:English
Published: Animo Repository 2015
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Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/7189
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-78332021-08-04T08:27:24Z Development of decision support matrix: determining the effectiveness of service recovery level in e-tailing Lim, Marvin Alexander S. Tan, Natasha Dominique G. Yeung, Clark Dustin T. Service failures occur even in the best run service industry. These service failures tend to effect the satisfaction of the customers, which becomes one of the reasons for the customers to shift to another service provider. With that, an effective service recovery strategy plays a vital role in mitigating the negative effects of service failures. However, characteristics of service failures vary across different industries. Existing literature have mainly focused on service industries (e.g. hotel, restaurants, and healthcare industries) that exhibit direct interactions with the customers. E-tailing, on the other hand, is a service industry that has limited interactions with the customer. Thus, poses unique characteristics of service failure that requires a different approach of service recovery. The empirical research of this study focused on establishing the relationships of the service recovery factors such as: taxonomy and severity of service failure and service recovery justices in order to better understand how these factors interact with post recovery satisfaction and repurchase intentions. Both the taxonomy of service failures and service recovery strategies were generated from the focus group discussion conducted with an e-commerce company in the Philippines that handles over 50 e-tailing industries nationwide. After which, the data gathered from the focus group discussion was transcribed into qualitative data through the use of survey questionnaires. These survey questionnaires were given to the e-tailing customers and were used as part of the explorative study confirming the taxonomy and severity of service failures initially generated from the focus group discussion. Scenarios for the final survey were then constructed based on the findings in the explorative study and the final survey proper were executed afterwards. E-tailing customers were asked to answer the experimental scenario survey, together with a video enactment of each scenario in order to better convey the emotions and help the responden Statistical software such as structural equation modeling, design expert 9, and Minitab were used to valuate and to establish the aforementioned relationships. After thorough analysis, it was found that the three service recovery justices have positive effect on both post recovery satisfaction and repurchase intention. However, it was found out that procedural service recovery justice is only significant for customer services problems and delivery problems. On the other hand, distributive and interactional service recovery justices have significant positive effects on the post recovery satisfaction and repurchase intention in all taxonomies of service failure. This suggests that taxonomy of service failures plays an important role in terms of the optimal setting in service recovery strategies to vary across different taxonomy of service failure, furthermore, it was discovered that severity of service failure negatively impacts the post recovery satisfaction and repurchase intention of the customers for all taxonomies of service failure except for security problem. The severity of security problems does not play a significant role because the recovery must always be of high setting as the customer's trust and safety are deemed to be very fragile needs. For the output of the study, a service recovery decision matrix was developed to serve as a guide for several e-tailing companies in terms of how they can effectively execute service recovery strategies that could yield to better post recovery satisfaction and repurchase intention. 2015-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/7189 Bachelor's Theses English Animo Repository Electronic commerce Service industries Industrial Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Electronic commerce
Service industries
Industrial Engineering
spellingShingle Electronic commerce
Service industries
Industrial Engineering
Lim, Marvin Alexander S.
Tan, Natasha Dominique G.
Yeung, Clark Dustin T.
Development of decision support matrix: determining the effectiveness of service recovery level in e-tailing
description Service failures occur even in the best run service industry. These service failures tend to effect the satisfaction of the customers, which becomes one of the reasons for the customers to shift to another service provider. With that, an effective service recovery strategy plays a vital role in mitigating the negative effects of service failures. However, characteristics of service failures vary across different industries. Existing literature have mainly focused on service industries (e.g. hotel, restaurants, and healthcare industries) that exhibit direct interactions with the customers. E-tailing, on the other hand, is a service industry that has limited interactions with the customer. Thus, poses unique characteristics of service failure that requires a different approach of service recovery. The empirical research of this study focused on establishing the relationships of the service recovery factors such as: taxonomy and severity of service failure and service recovery justices in order to better understand how these factors interact with post recovery satisfaction and repurchase intentions. Both the taxonomy of service failures and service recovery strategies were generated from the focus group discussion conducted with an e-commerce company in the Philippines that handles over 50 e-tailing industries nationwide. After which, the data gathered from the focus group discussion was transcribed into qualitative data through the use of survey questionnaires. These survey questionnaires were given to the e-tailing customers and were used as part of the explorative study confirming the taxonomy and severity of service failures initially generated from the focus group discussion. Scenarios for the final survey were then constructed based on the findings in the explorative study and the final survey proper were executed afterwards. E-tailing customers were asked to answer the experimental scenario survey, together with a video enactment of each scenario in order to better convey the emotions and help the responden Statistical software such as structural equation modeling, design expert 9, and Minitab were used to valuate and to establish the aforementioned relationships. After thorough analysis, it was found that the three service recovery justices have positive effect on both post recovery satisfaction and repurchase intention. However, it was found out that procedural service recovery justice is only significant for customer services problems and delivery problems. On the other hand, distributive and interactional service recovery justices have significant positive effects on the post recovery satisfaction and repurchase intention in all taxonomies of service failure. This suggests that taxonomy of service failures plays an important role in terms of the optimal setting in service recovery strategies to vary across different taxonomy of service failure, furthermore, it was discovered that severity of service failure negatively impacts the post recovery satisfaction and repurchase intention of the customers for all taxonomies of service failure except for security problem. The severity of security problems does not play a significant role because the recovery must always be of high setting as the customer's trust and safety are deemed to be very fragile needs. For the output of the study, a service recovery decision matrix was developed to serve as a guide for several e-tailing companies in terms of how they can effectively execute service recovery strategies that could yield to better post recovery satisfaction and repurchase intention.
format text
author Lim, Marvin Alexander S.
Tan, Natasha Dominique G.
Yeung, Clark Dustin T.
author_facet Lim, Marvin Alexander S.
Tan, Natasha Dominique G.
Yeung, Clark Dustin T.
author_sort Lim, Marvin Alexander S.
title Development of decision support matrix: determining the effectiveness of service recovery level in e-tailing
title_short Development of decision support matrix: determining the effectiveness of service recovery level in e-tailing
title_full Development of decision support matrix: determining the effectiveness of service recovery level in e-tailing
title_fullStr Development of decision support matrix: determining the effectiveness of service recovery level in e-tailing
title_full_unstemmed Development of decision support matrix: determining the effectiveness of service recovery level in e-tailing
title_sort development of decision support matrix: determining the effectiveness of service recovery level in e-tailing
publisher Animo Repository
publishDate 2015
url https://animorepository.dlsu.edu.ph/etd_bachelors/7189
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