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The Influence of Service Recovery Strategies on Word of Mouth

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IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 3, No 2, May 2012 ISSN (Online): 1694-0814


The Influence of Service Recovery Strategies on Word Of Mouth: Views of Mobile Phone Users
Samsudin Wahab and Nor Sabrina Norizan Center of Applied Management Studies Faculty of Business Management, Universiti Teknologi MARA 42300 Puncak Alam, Selangor

This study explores the relationship between perceived customer dimensions of justice and word of mouth among the selected university students in mobile phone usage. The respondent used for this study was 500 business students of Malaysian university students located in Kelang Valley. Out of 327 questionnaires distributed, there were 181 complainants. Dimensions of justice act as an independent variable consisted of procedural, interactional and distributional justice. In order to determine the relationship between dimensions of justice and customer satisfaction the researcher used multiple regressions. The result showed that distributional justice and interactional justice as a significant unique contribution to the prediction of customer word of mouth. Further research should be carried out to identify the other factors of service recovery strategies that will help in increasing the customer satisfaction towards the organization. As this research was conducted in the telecommunication sector, it would be appropriate if further research can investigate if customers from the other sectors can display similar behavior. It is because different sectors will come out with different outcomes, thus it can help the organization to know the differences between the sectors and then take appropriate actions. Keywords: Service Recovery Strategy, Word of Mouth, Mobile Phone Users

1. Introduction Throughout the last decade, service failure and recovery issues have been the focus of many researches. Even though many service failure recovery researches have been conducted, still there are many gaps found (Nibkin, Ismail, Marimuthu and Abu-Jarad, 2011) for example, most of the research found is only focusing on the company reputation in the aspect of service failure and service recovery without considering the effect of the company’s reputation on customer’s outcomes (Hess and Story, 2005). In

addition, according to Bhandari, Tsarenko and Polonsky (2007) there are only one or two outcomes in evaluating service encounters and recovery activities, and it was found that the outcomes do not measure the overall customer responses. This means that more researches need to be undertaken to examine how organizational and employee recovery actions cause impacts on a cross set of customer outcomes that vary. By changing one of the service recovery aspects, compensations may decrease and the customer intends to switch sides, for instance, however it will not help to reduce the negative word of mouth made by the customer. Here, organizations that focus on one outcome and single recovery activity will overlook the other important outcomes, or in other words, a recovery strategy that is considered to be successful using one outcome measure may be less successful or fail completely in terms of another outcome measure. Lapidus and Pinkerton (1995) have investigated the relationships between the equity theory and the behavioral intentions, but they are only focusing on one theory, which is the distributional theory and it was suggested that the current research should include the other two theories that are the procedural and the interactional theory (Ruyter & Wetzel, 2000). In addition, Nibkin et al., (2011) had conducted a research in the airline sector. They stated that it is good if future researchers can enlarge their research to the others sectors or countries

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because it would be better to investigate customers from the other services as consumer reactions to service failure and service recovery might differ because of the level of involvement, in a particular service. Finally, the researcher found that there are a few researches being conducted involving both the service recovery strategies and the customer satisfaction outcomes in the Malaysian telecommunications sector and it is clearly stated that there are gaps in the previous researches that need to be fulfilled and to be investigated. Based on the problems stated above, in order to assist the organizations to find the answers and solutions in solving those problems, this study was meant to achieve the following objective is to investigate the influence of service recovery strategies on customer’s wordof mouth.
2. Literature Review
Major headings are to be column centered in a bold font without underline. They need be numbered. "2. Headings and Footnotes" at the top of this paragraph is a major heading.

facing some difficulties but when the organization use service recovery it will help them to prevent customers from making complaints before or after the problem has occurred. In a service failure perspective, service recovery can be considered as a second service encounter where the customers recognize a problem in relation to the service or service provider and hence if their expectations are not met, then another set of expectations – service recovery expectations – becomes active (Lewis & Spyrakopoulos, 2001). Therefore, one way in achieving customer loyalty in the organization is by having a good service recovery strategy (Andreassen, 2001; Tax & Brown, 2000) whereby it helps the organization to maintain its customers for a long time (Stauss & Friege, 1999). Successful recovery strategies are essential for customer retention resulting from a service failure (Strauss, 2002) and many researchers have clearly proven that by providing effective service recovery strategies it will help to enhance the dissatisfaction related with service failure and also to save the cost related to replace dissatisfied customers (Maxham, 2001; Bitner, Booms & Tetreault, 1990). However, most of the companies do not pay enough attention to manage customer complaints efficiently (Homburg & Fürst, 2005; Stauss & Schoeler, 2004). Furthermore, researches conducted by Lewis and McCann (2004), Naylor (2003), Andreassen (1999) and Tax and Brown (1998) show that the majority of customer complaints are those dissatisfied with the way the company handles their complaints. It seems that the matters of effective complaint handling are not sufficiently addressed by businesses. In the progressively service oriented world economy, companies might be shocked by this apparent disregard of customer complaints, especially when the seriousness of customer dissatisfaction in the short term and long terms are considered: negative word-of-mouth (Blodgett, Wakefield & Barnes, 1995; Sen and Lerman, 2007) and switching to competitors firms (Homburg & Fürst, 2005), companies will suffer from high costs of acquiring new customers (Hart, Heskett & Sasser, 1990) if the customers do not have loyal feelings towards the company (Colgate & Norris, 2001). It is suggested that when the organization deals with customer complaints, they should use a positive approach in order for them to maintain customer relationships and generate positive communication about the company (Boshoff & Allen, 2000; Stauss, 2002). Therefore, one of the service recovery benefits is the prevention of customer defection to other providers as it will lead to customer retention because to gain new customers is more costly than keeping existing ones (Power, 1992) and the customers will become more profitable if she or he keeps staying with the

2.1 Service Recovery
Service failure occurs when the organization cannot meet the customers’ expectations (Bell & Zemke, 1987) and when a service failure happens, the organizations need to use appropriate service recovery strategies in order to keep the customer with them and at the same time, to reduce the customer defection and negative word of mouth towards the organization. Therefore, it is important for the organization to have service recovery strategies which involve those actions that are designed to resolve the customer problem and to remove negative attitudes of dissatisfied consumers and at the same time to build a long term relationship between the customer and organization (Miller, Craighead & Karwan, 2000). Zemke and Bell (1990) defined service recovery as “a thought out, planned process for returning aggrieved customers to a state of satisfaction with the firm after a service or product has failed to live up to expectations.” Michel (2001) has differentiated between complain management and service recovery whereby he found the majority of dissatisfied customers are unwilling to complain even when they are

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IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 3, No 2, May 2012 ISSN (Online): 1694-0814


company (Reicheld & Sasser, 1990). Hence, Tax et al. (1998) have proposed a three dimensional concept of justice which are distributive justice, procedural justice and interactional justice.


Distributive Justice

Organizations need to develop effective service recovery strategies that can recognize the inconvenience that the service failure has created to its customer, hence conforming to notions of procedural justice and “outcome fairness” which is sometimes called as distributive justice (Tax et al. 1998; McColl-Kennedy & Sparks, 2003; Mattila & Patterson, 2004). Distributive justice can be referred to as customer perception of fairness in the complaint outcomes - notions of equity, equality and need consistency and it involves the perception of equality and fairness when the resources are exchanged among parties (Homburg & Furst, 2005). Different from Blodgett, Hill and Tax (1997); Homburg and Furst (2005) said that distributive justice refers to the customer’s perception of the equity towards the company resources allocation and the tangible outcomes of the service encounter which the company will offer to the customers in order to overcome the service failure. It was found that there were specific outcomes produced by distributive justice which the organizations and service providers did to recover what mistakes they have made to the customers (Greenberg, 1990 & Gilliand, 1993) and this outcomes included compensations which consist of discounts, coupons, refunds, free gifts and apologies (Mattila & Cranage, 2005). In order to know whether the customer receives the appropriate compensation, it can also be determined by looking at how the customers are being treated and how much loss that they have faced (Tax et al., 1998). Thus, by being given the same amount of recovery, customers in a high low quality relationship with the company will perceive lower fairness compared to those individuals in a low quality relationship and it is because of their exacerbated negative disconfirmation (Olson and Dover, 1979). It was also found that customers always expected that the organizations will treat them fairly otherwise they will become angry and skeptical towards the organization (Berry, 1995). According to the group-value Model of Justice Lind and Tyler (1988), if people value their relationships with organizations they will have lost more if the organizations’ actions are perceived to be unfair (Brockner, Tyler & Cooper-Schneider, 1992). Besides, if the organizations did not identify properly the cost in time and effort that the customer spends to seek compensation for inequity, it will lead to customer dissatisfaction (McCollough, Berry & Yadav, 2000; Smith, Bolton & Wagner, 1999). Each customer may expect that they will

receive different levels of compensation depending on how the service failure affects them for example an annoyed customer would expect a fair fix to the problem, while a customer who feels that he is a victim may expect some value-added atonement (Bell & Ridge, 1992). It is supported by Sparks and McColl-Kennedy (2001) whereby the researchers have proven that respondents were satisfied when a 50 percent refund was given to compensate for the service failure. Among to the three dimensions justice, Holloway et al., (2009) in the online shopping at a multichannel retailer website said that distributive justice is the most important dimension of the customers’ evaluation of a service recovery, largely due to the lack of human interactions in the online realm. Additionally, Chebat and Slusarczyk (2005) observed that distributive justice significantly influences customer loyalty through the mediator of such emotions and Kau and Loh (2006) in their research the in mobile phone industry confirmed that distributive justice is significantly related to customer satisfaction outcomes. Finally, Blodgett et al. (1997) found that in a retail setting, distributive justice had a significant influence on customer re-patronage and negative word-of-mouth.


Procedural Justice

Procedural justice is the customer’s perception regarding the equity of the policies and procedures used by an organization in the recovery process that led to the desired outcome (Blodgett et al., 1997; Maxham & Netemeyer, 2002b). According to Tax et al., 1998 procedural justice consists of timeliness and process control as the perceived fairness of customer complain handling process and different from Cropanzano and Greenberg (1997) which said that procedural justice refers to the fairness of the processes by which outcomes are determined. It is found that procedural justice will influence customer satisfaction and trust with an organization’s products or services (Teo & Lim, 2001; Sindhav, Holland, Rodie, Adidam & Pol, 2006; Guiltinan, 2006) and in the retail context, procedural justice (timeliness) did not have significant influence on customers’ re-patronage intentions and negative word of mouth (Blodgett et al., 1997) Leventhal and associates (Leventhal, 1976; Leventhal, 1980; Leventhal, Karuza & Fry, 1980) have identified several procedural justice rules, whereby they propose that, the greater that each of these rules are fulfilled, thus the fairer the procedure will be seen to be. For instance, ethical procedures generally are viewed more favorable than those that are not (Folger & Cropanzano, 1998) where there is a growing body of literature suggesting that participant fairness judgments are linked with their evaluations of both telecommunication procedures (Chen, Rose & Huang, 2007) and surveillance procedures in other contexts (Ambrose & Alder, 2000).

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IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 3, No 2, May 2012 ISSN (Online): 1694-0814


A different context on procedural justice suggests that people use procedural justice beliefs as a surrogate for determining whether they can trust the organization and accept its authority because procedural fairness beliefs act as a heuristic or mental shortcut for more complex trust judgment which the process called the procedural fairness heuristic (Lind, 2001). Therefore, in considering the customer’s needs, it is advisable that the service providers and front liner officers provide a timely response in managing the service failure situation (Bhandari, Tsarenko & Polonsky, 2007). It is said that procedural justice can help in determining the process of handling customer complaints (Blodgett et al., 1997), decision making, accessibility, timing or speed, process control and flexibility to be included in the service recovery (Tax et al. 1998). Most of the procedural justice aims to solve the conflict that appears between the company and the customer and even the outcomes will be unsuccessful (Tax et al., 1998; Bitner, Booms & Tetreault, 1990; Fisk & Coney, 1982). From customer complaint perspective, if a customer finds it difficult to engage in a process, prolonged time involvement or cost, a complaint can be classified as falling into procedural justice dimension. Previous research shows that most of the procedure-related complaints result in the company's timely responses and tend not to be related to monetary compensation such as refund (Smith, Bolton & Wagner, 1999). Another part of procedural justice is by providing a timely feedback about decisions, which is applicable to any service recovery situation. The delivery of timely feedback has been discussed in the management literature (Tyler & Bies, 1990; Sapienza & Lorsgaard, 1996) whose procedures allow individuals to feel that their interest is being protected (Lind & Tyler, 1998). Due to that, it is appropriate if the front-line employees who are empowered to manage a service failure situation can serve better in order to meet the customer’s wants and needs.

context, interactional justice refer to the method of service recovery process which is being operationalized and recovery outcomes presented. Blodgett et al. (1997) confirmed that interactional justice had a significantly large impact on word of mouth intentions as satisfaction with service recovery strategy would encourage positive word of mouth communication. Same goes to Kau and Loh (2006), who have found that higher levels of interactional justice will lead to more favorable re-patronage intentions and decreased likelihood of negative word of mouth. Furthermore, it is found there, that customers who complain will become more loyal with the service provider when only a partial refund, exchange, or discount is given, provided that they are treated with courtesy and respect (Blodgett et al. , 1997). In order to achieve a sense of interactional fairness it is necessary for the organization to include apology and empathy as it associated with customer perceptions so the customer will feel fairly treated (Wirtz & Matilla, 2004). Sources of unfair interactional perceptions include unjustified blame, violation of promises, failure to admit an error, and insults. The literature is inconsistent of the relative importance of each dimension, but it can be argued that they are all important in different situations and settings, and that they interact in predicting customer's reactions (Sparks & McColl-Kennedy, 2001; Tax & Brown, 2000). If the company shows a lack of concern to their customers during service recovery effort, the customer will suffer with negative emotion (McColl-Kennedy & Sparks, 2003).


Word of Mouth


Interactional Justice

Interactional justice is defined as dealing with interpersonal behavior in the enactment of procedures and the delivery of outcomes or in other words, it refers to how the recovery outcomes and process are being implemented and presented (Tex et al. 1998). Interactional justice is also related to the customer’s perception of the equity of the personal treatment that the customer receives from the company in terms of respect, honesty, education and dignity when they suffer from service failure (Maxham & Netemeyer, 2002; Smith et al., 1999). According to Tax et al. (1998), there are five elements of interactional justice which are explanations and causal accounts, honesty, politeness, effort and empathy and in a service recovery

Word of mouth can be defined as the message about an organization credibility, trustworthiness, how the company operating its business, communication between one person to another (Gronroos, 1990). In comparison to Anderson & Gerbing (1998), word of mouth is informal communication between private parties concerning evaluations of goods and services rather than formal complaints to firms. Word-of-mouth behaviour has been recognized as an important post purchase behaviour which according to Rosen (2000), customers frequently talks about products which are new, enjoyable, noticeable, personally experienced, complicated, and expensive products and services. Blodgett et al. (1997) confirmed that satisfaction with service recovery would encourage positive word of mouth communication between the customer and the organizations. Westbrook (1987) in the effects of service recovery on consumer satisfaction: a comparison between complainants and non-complainants journal, said word of mouth (WOM) can be referred to as informal

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communication between consumers about the characteristics of a business or a product. According to the previous research by Day (1980) about WOM, it is important for the customers’ post purchase behavior such as face to face communication, as it often provides information that is highly valuable that can help to influence others’ perceptions and beliefs about the other particular firm, and their intentions to purchase from the firm. Since word of mouth (WOM) regarding problem resolution can be either a positive or negative force in building a firm’s reputation and retaining customers, the reward for companies which resolve problems to the customer’s satisfaction appears to be very high (Hart et al., 1990). Moreover, when the customer received a fair treatment of service recovery, they will engage in positive WOM behavior, thus they will help to spread a goodwill on behalf of the service provider and it is found that positive word of mouth always happens with an effective recovery while negative word of mouth follows recovery failures (Blodgett, Granbois & Walters, 1993; Maxham, 2001).

(1970) model which had a population of 11,500, the sample size should have consisted of 373 respondents. Therefore, a total numbers of 500 questionnaires had been distributed.

3.2 Items and Measurement
The instrument for this study was a survey questionnaire. It was designed precisely by the researcher to answer research questions. The questionnaires were distributed by hand to each of the selected respondents involved in this study. The researcher had developed questionnaires that included the service recovery strategies which consist of distributive justice, procedural justice and interactional justice.
Table 3.2: Items for Questionnaires

DIMENSION Distributional Justice Procedural Justice Interactional Justice/ Explanation and Effort Empathy Politeness Word of Mouth and



3. Methodology 3.1 Population and Sampling
The population for this study was the business students from three universities located in Kelang Valley which are University of Malaya, MARA University of Technology and Putra Malaysia. The use of these students should be appropriate since students are real-life consumers of the services described in the scenarios and also the behaviors and responses of students and other market segments are likely to be more similar in every service recovery incidents (Miller et al., 2000). The total populations of the students at the three universities are 11,500 students. The sampling technique applied in this study was convenience sampling. Convenience sampling refers to the collection of information from members of the population who are conveniently available to provide it (Sekaran, 2000). Convenience sampling is most often used during the exploratory phase of a research project and is perhaps the best way of getting some basic information quickly and efficiently. The criterion set by the researcher was the respondents must have purchase a mobile phone before For the sample size, the sample was divided into two groups, one group comprising of respondents who had experienced service failure and had complained to the mobile service provider while the other group consisted of respondents who did not lodge any complaint with the service provider. In order to select the sample size, the researcher decided to refer to the Krejcie and Morgan

11 7 7

5 4

Clemmer (1988), Oliver and Swan (1989) Bitner et al. (1990), Taylor, (1994), Goodwin and Ross (1992) Blodgett et al. (1997), Parasuraman et al. (1998) Bies and Shapiro (1987) Blodgett et al. (1997), Walker and Harrison (2001)


4.1 Survey Return Rate
Out of 500 questionnaires distributed, it is only 350 set of questionnaires returned. Table 4.1 shows the response rate.

4.2 Reliability Analyses
In order to test whether the items grouped under a factor are internally consistent and stable, the reliability analysis is established. Consistency indicates how well the items measuring a concept hang together as a set. In general, reliabilities less than 0.6 are considered to be poor, those in the 0.7 range acceptable and those over 0.8 good (Sekaran, 2000). Different to George and Mallery (2003),

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in which the researchers provided the following rules of the thumb: “_ > .9 – Excellent, _ > .8 – Good, _ > .7 – Acceptable, _ > .6 – Questionable, _ > .5 – Poor and _ < .5 – Unacceptable”. Before the researcher runs the reliability analyses, the researcher had first recoded negatively worded scale items to ensure that the items were measured in the same direction. Therefore, the result of this analysis is presented in table 4.1. Thus, for this study the Cronbach’s for procedural justice, interactional justice, distributional justice, word of mouth, loyalty and trust, the range of the reliability was from .5 to .8 which is acceptable. Even though for the explanation and effort the Cronbach Alpha was .637 and word of mouth was .548 which it is considered lower limit of acceptability. But according to Fornell and Larcker (1981) even if the reliability is greater or equal to .5, it is considered lower but it is still acceptable. Table 4.1: Reliability Analyses Variables Procedural Justice Explanation and Effort Empathy and Politeness Distributional Justice Word of Mouth Number of items 11 7 5 5 4 Cronbach’s alpha .787 .637 .728 .764 .548

Table 4.2: Normality result: Skewness and Kurtosis values (n=181) Variables Procedural Justice Explanation and Effort Empathy and Politeness Distributional Justice Word of Mouth Customer Loyalty Trust Skewness .108 .133 -.006 .479 .446 .144 .406 Kurtosis -508 -0.61 -.634 -.031 .324 -.277 .342

4.4 Multiple Regressions Multiple regressions are one of the family techniques that can be used to explore the relationship between one continuous dependant variable and a number of independent variables or predictors (usually continuous). Besides, it is based on correlation, but allows a more sophisticated exploration of the interrelationship among a set of variables. The result of regression is an equation that represents the best prediction of a dependent variable from several independent variables. Thus, regression analysis is used when independent variables are correlated with one another and with the dependent variables. In this study, the researcher used multiple regression to identify the best predictor or most significant factors of service recovery strategies that influence customer satisfaction outcomes.

4.3 Normality Test The assumption of normality is a prerequisite for many inferential statistical techniques (Coakes, Steed & Ong, 2010). Normality is important in knowing the shape of distribution as the normality helps to predict dependent variables scores. To test the normality of the data, a number of statistics can be used which are KomogorovSminorv statistics, with a Lilliefors significance level and the Shapiro-Wilk statistics, skewness and kurtosis. For this study the researcher decided to use skewness and kurtosis in testing test normality. The range for skewness and kurtosis is considered acceptable if it is in range +/- 3 (Hair, Babin, Anderson, Tatham & Black, 2006). Table 4.14 shows the normality result for this study. The result shows the data was normally distributed since the value of kurtosis and skewness were in range.

Table 4.3: Coefficient Model for Customer Word of Mouth


Unstandardi zed Coefficients B Std. Error .313 .086 .109

Standar dized Coeffici ents Beta



(Constant) Procedural Justice Explanatio n and Effort Compute Empathy and Politeness

2.7 19 .19 8 .01 8 .04 4

.153 -.012

8.68 9 2.28 5 .165

2.719 .198 -.018





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Distributio nal Justice

.02 7





Table 4.3 shows that the results of the analyses presented above allow the researcher to answer the question one of the study. The significant result for explanation and effort was (p=-0.18 < 0.05), empathy and politeness, (p=-0.44 < 0.05) and distributional justice, (p=-0.27 < 0.05) and this shows that the significance value is less than .05. It is found that the distributional justice and interactional justice is a significant unique contribution to the prediction of the DV. Thus, this result supports the researcher’s hypothesis one and hypothesis seven. Therefore, hypothesis four was rejected as the significance value is more than 0.05 due to the overlap with the other IV in the model.

4.Discussion, Recommendation



The result of the multiple regression analysis above showed that distributional justice and interactional justice as a significant unique contribution to the prediction of customer word of mouth. It is supported by Blodgett et al. (1997) that distributional and interactional justice has a significant effect on customer word of mouth. Moreover, according to Blodgett (1993) once a dissatisfied customer pursues redress, there will be positive or word of mouth and re-patronage intention during the complain process. In addition, Blodgett et al. (1997) in his retailing study confirmed that procedural justice did not have any significant effect on customer word of mouth. For the results stated, it is found that customers will spread positive or negative word of mouth if they are satisfied or dissatisfied with the outcome they received during the recovery effort. The outcome here refers to the compensation in term of coupons, refunds, free gift, replacement and apologies. If the customer found that the outcome they received is fair, they were likely to spread a positive of mouth to the other people, but if they received a bad outcome, it will cause them to spread the word to all the people. In addition, from the result above, it can be seen that interactional justice is also important in determining the customer word of mouth, as, if the customer perceived that they are treated well by the service provider they are likely to spread a positive of mouth. Service providers need to make sure they always include the explanations and efforts, and empathy and politeness during the interaction with their customers so that the customer will feel that they are being appreciated by the organization.

As for this study, it is revealed that distributional justice significantly influenced customer word of mouth. Thus, what the customers received during the service recovery effort will determine whether they will spread a positive or negative of mouth. Due to that that, the organization needs to makes sure they provide the right outcome during the service recovery effort. The outcome here refers to the compensation in term of refunds, coupon, free gifts or replacements that the customer will receive when they are having service failure. The organization needs to make sure the compensation given can replace the customer dissatisfaction experienced during the service failure. The study also revealed that interactional justice significantly influence customer word of mouth. Thus, the organization needs to make sure their employees use the explanation and effort, empathy and politeness aspect during handling dissatisfied customers. It is because the customers will spread a positive of mouth when they feel they are treated nicely and in a good manner. It will help to lower their dissatisfaction and will continue to spread a good of mouth about the company. The organization needs to make sure that their employees have all those aspects when dealing with the customers, as, the employees are the ones that communicate with the customers during the service failure. Further research should be carried out to identify the other factors of service recovery strategies that will help in increasing the customer satisfaction towards the organization. As this research was conducted in the telecommunication sector, it would be appropriate if further research can investigate if customers from the other sectors can display similar behaviour. It is because different sectors will come out with different outcomes, thus it can help the organization to know the differences between the sectors and then take appropriate actions.

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First Author a senior lecturer at Center of Applied Management Studies, Faculty of Business Management, MARA University Technology, Malaysia: hold a bachelor degree in Agribusiness (1989), MBA (2001) and PhD in Management (2010): Working as a teacher in 1995, Poly-technique lecturer in 2000 and MARA University lecturer in 2001: Achieved best paper awards from Postgraduate Colloquium in 2009 , Young Researcher Award in international symposium in service management in 2011: the authors for 16 management books between; current research interests is on e commerce, technology management; a members of Malaysian Qualitative Research Association and IACSIT. Second Author a young lecturer in MARA University of Technology, Terengganu Malaysia. Actively involved in international conference and journal writing. .

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