This paper focuses on the topic of servicerecovery and the importance of understanding justified forms in relation to scripted or discretionary behaviour of service employees. The research will delve into the social interaction between a service employee and customer and will take a look at the discretionary space a service provider employee has during servicerecovery processes. Processes of servicerecovery are rarely studied, and this is important because servicerecovery is seen as a powerful tool for value creation for customers, but it requires empowerment of service employees (Tax & Brown, 1998; Hart, Heskett & Earl Sasser, 1990). Servicerecovery is described as the actions taken by an organization in response to a service failure. The reasons for service failure are very diverse (Wilson, Zeithaml, Bitner, & Gremler, 2012). The effects of servicerecovery are quite positive. Research from Tax, Brown, & Chandraskekaran (1998) suggested that investments in complaint handling can improve evaluations of service quality, strengthen customer relationships and build customer commitment. So far, service literature has advocated to use scripted service protocols and emphasize efficiency (Bowen & Lawer, 1994). The focus on scripts and protocol is at the expense of the discretionary space of the service employee, but this discretionary space is a very powerful tool to enhance service performance (Hart et al., 1990). However this empowerment of employees is especially important in a service environment since servicerecovery pre-eminently covers exceptional situations which require creative solutions from a service employee (Hart et al., 1990; Wilson et al., 2012). Problems arise because customers most often do not want to get a standard ‘quick fix’ to their unique problem. If customers experience
Abstract:- The purpose of this research is to explore factors of ‘service quality’ and ‘service-recovery quality’ of online retailers in India; and to suggests measurement constructs for ‘service quality’ and ‘service-recovery quality’ from customer’s perspective. Exploratory factor analysis (EFA) of customer responses of a survey of consumer attitudes is used for data analysis. In the first stage, concepts and constructs of the ‘service quality’ and ‘service-recovery quality’ for online retailers are identified through extensive literature review. In the second stage, survey of attitude measurement questionnaire was administered to customers, —who have experienced online shopping over a period of time. A 7-point Likert scale is used for capturing customer responses based on quota sampling technique. EFA is conducted using oblique rotation considering factor dependence. Factors thus identified are further studied for literature support, analyzed for validity and reliability. Exploratory factor analysis using principal component method, identified five factor structure of ‘service quality’ of online retailers as; e-reliability, e-servicescape, e-technology dissatisfiers, e-security and e-delivery. Research also explored factors of ‘service-recovery quality’ of online retailers as; e- support and e-compensation. The proposed factors of ‘service quality’ and ‘servicerecovery quality’ of online retailers can be useful in improving service product offers. The designed research constructs can be operationalized for better online shopping consumer experience. Considering retail customer channel shift from offline retail shops to online retail, this research is a latest consumer perspective towards online buying. Identified factors is useful inputs to design online retail service quality by improving retail operations.
The study employed scenario-based experiments to test the proposed hypotheses. The sample of eWOM receivers’ responses is more representative by employing scenarios than by using recall-based designs in which subjects tend to report on experiences that are special or very important to them. Five scenarios were constructed to manipulate the servicerecovery strategies: S1 no recovery, S2 apology immediately at the scene, S3 compensation immediately at the scene, S4 apology after eWOM, and S5 compensation after eWOM. A fictitious brand name was used to eliminate the influence of brand familiarity, and the subjects were made aware of that. Examples of the scenarios are illustrated in the Appendix. Subjects were randomly assigned to one of the five experimental scenario groups. For each group, the subjects were instructed to play the role of a microblog user and were asked to read one written scenario. After reading the scenario, subjects were asked to fill in the questionnaire, as if they read the information from online microblog. The electronic characteristic of WOM was emphasized by highlighting the online context in the instructions. The format of the questionnaire used by three experimental groups was identical.
Firm loyalty, product loyalty and customer satisfaction affects the intention to repurchase and whether or not the customer can be satisfied with the servicerecovery offered by the service provider. Intention to repurchase is a significant concept in marketing literature. The main reason for that is we look for ways to execute an effective strategy that will differentiate us from our competitors in the market. This can be done by implementing relationship marketing, where we build a relationship with our customers so that the relationship does not end after the first purchase. In building this relationship, marketers try their best to persuade the customers in coming back for returned purchases. Based on this logic, it is essential for marketers, to find effective strategies in bringing the customer back to the business. Based on the social status, age, education and other characteristics of the potential market, we need to find ways to attract customers back to the business. As stated above, from the emotional state of the customer to their cultural background, we want to develop commitment and loyalty towards the business by fitting the products and services offered to the liking of the customers. As a result we expect the customers to desire to maintain this valued relationship and in order for them to value; they must trust that the firm will deliver the high quality service expected by the customer. The most recent literature has investigated the impacts of delivering high quality service and perceived value to satisfaction, corporate image and behavioral intentions (Hu et. al., 2009). We can conclude that achieving high quality service and creating superior customer will ultimately bring in satisfaction and this will lead to retaining our customers (Hu et. al., 2009). Another recent study has revealed that, the quality of the service and the customer’s perceived value and image and influenced satisfaction is also a determinant of loyalty (Lai et al., 2009). Customer’s intention to repurchase is impacted by satisfaction and perceived value (Dongjin, et al., 2008). In strategy literature, we find that switching costs mediate the perceived value and satisfaction. That potential mediating affect is beyond the scope of this study so we propose;
the shortcomings existing in servicerecovery, servicerecovery could just make efficient performance. Second, the same servicerecovery procedure could result in different effects on customers’ satisfaction. If customers’ perception exceeds their SE, they will actually feel service provider’s concerns about them. As a result, their satisfaction could be restored to a high level. To other customers, this recovery procedure could be perceived lower than their will expectation, so there is little effect of servicerecovery on restoring customers’ satisfaction. Third, managers should not always provide excellent servicerecovery to maintain their service cost. For customers expectations (both will and should) will increase when they encounter service failure at next time if their perceived servicerecovery exceeds their expectations at the first time, managers have to deliver better servicerecovery to effectively restore customer’s satisfaction than what they provided at the first time, which will increase companies’ service cost dramatically. Maybe the wise way for managers to retain customers is to provide good recovery program and maintain their expectations at the same time.
The findings of this study demonstrate that service failure severity can enhance SRE in customers’ mind. Both SRE and SRP also influence service disconfirmation recovery significantly. So service provider should adopt different servicerecovery strategies depending upon the severity of the problem. They also have to first develop a system for tracking and identifying service failures and their level of severity. Firms should avoid solving customer complain by standard, low cost methods. Customer contact employees should be trained to recognize the varying severity of service failures from the customers’ perspective and to treat customers possessing varying degrees of negative emotions. Because they are the only one person who can fully express customers’ thoughts to service manager. From this source, service manager could understand more about customers’ real recovery expectation, and response that by the best recovery performance in the shortest time to promote the positive disconfirmation.
Divett, et al (2003) argue that satisfaction is the ultimate factor leading to strong probability of consumer loyalty. Satisfaction also requires sound communication channels underpinned by perceptions of equity and fairness. Servicerecovery must seek to fully satisfy consumers in terms of equity and fairness to influence loyalty levels by strengthening the relationship between company and consumer. Lin and Sun, (2009) emphasise that many factors influence consumer loyalty online, whilst highlighting the notion of social factors (equity and fairness) affects consumer expectations (Magnini and Ford, 2004; Komunda and Osarenkhoe, 2012) which must be resolved for companies to retain customers. The use of generic apologies and failure to remedy personal inconvenience can negatively influence a consumer’s repurchase decision. Personalisation is currently lacking when receiving service and support in the fashion sector due to the volume of consumers that shop online. Personalised communication strengthens and affects all aspects of company to consumer relationships, allowing individuals to feel they are not merely one of many consumers, particularly when recovering from service failure (Ball, et al 2004). Through personalisation, notions regarding equity, fairness and satisfaction are intensified.
The level of service quality can be measured by two dimensions; 1) the out- come or “what” the customer actually receives as part of the firm’s efforts to re- cover and 2) the process of recovery and “how” the recovery is accomplished (Duffy, Miller & Bexley, 2006). The outcome of SR is the customer’s main con- cern while the dimension of SR process is more internal and customer usually does not care about them (Duffy et al., 2006; Ringberg, Odekerken-Schröder & Christensen, 2007). Consequently, in order to provide appropriate response to unhappy customer, servicerecovery requires high level of interaction be- tween the service provider and its customer (Casado-Díaz & Nicolau-Gonzál- beza, 2009; Kau & Loh, 2006).
Obsession with service delivery may not be a foolproof mechanism to prevent service failure (Migacz, Zou, & Petrick, 2018). Even in the face of uncontrollable circumstances, organizations must strive to make all efforts to mitigate the loss from failures and to salvage dissatisfied customers. Such efforts which are made by organizations as a response to service failure are broadly known as ServiceRecovery. Failures in service are critical incidents which definitely elicit a negative response from consumers. If left unchecked, failures may lead to situations where dissatisfied customers may switch to another provider. Apart from a loss in revenue, loss in goodwill may occur as disgruntled customers tend to spread unhealthy, damaging word of mouth. Some may even become activists by complaining to media, third parties, regulatory bodies etc. Quick resolution of customer complaints is essential in order to avoid potentially negative consequences for the organization. The servicerecovery paradox is one such path towards effective servicerecovery.
between customer determinants; accumulative trust, employee performance, service orientation of firm and digital commitment, and customer satisfaction and whether these relationships are direct or indirect. Third: the study examined the relationship between customer satisfaction and e-servicerecovery satisfaction, and whether implementing effective e-servicerecovery can generate satisfaction, that can ultimately lead to customer retention. The study also investigated the role of e-servicerecovery satisfaction as a mediator in the relationships between customer determinants and customer retention. The conceptualizing of the new constructs will be detailed in the following sections.
The study found out that respondents were satisfied with a discount as a compensation for service failure. Compensation was found to be the most powerful determinant of customer satisfaction and works better because it denotes seriousness on the part of the service providers towards valuing their clients and their eagerness to have them back as repeat customers. These findings agree with Wahab and Norizan (2012) study on the influence of servicerecovery strategies on word of mouth: views of mobile phone users who found that customers will spread positive word of mouth if they are satisfied with the outcome they received during the recovery effort. These findings are also supported by the social exchange theories which indicate that people feel fairly treated when they perceive their economic outcomes in proportion to their inputs (Adams, 1965 as cited in Namkung, Jang, Almanza & Ismail, 2009).
63 justice on satisfaction and the role of customer emotions in the service failure and recovery in tourism and hospitality services. Based on 32 interviews in Australia, the study proposed the following four categories for evaluating service failure issues: service issues (e.g. didn’t get business class seat overcooked/undercooked meal, cold meal, etc); service providers employee behaviour issues (i.e. jokes, rudeness, etc); outside the service provider’s control issues (e.g. wet weather power cut delayed flight, etc) and customer related issues (e.g. sick/heart attack too short for theme park ride guest injures himself/herself, etc). The results showed that when service providers did not appear to put effort into correcting perceived errors, servicerecovery had a significant direct influence on customer negative emotions. These results have also been reflected in the work of Rio-Lanza et al., (2009). Examining the impact of perceived justice on customer’s post-recovery perceptions in restaurant services, Mattila and Patterson (2004) used experimental methodology (scenarios) to examine 561 customer perceptions of restaurant service failure. The findings confirmed that perceived fairness in servicerecovery had a significant direct influence on post-recovery satisfaction.
The research findings imply that SCB should pay attention to the dimension of a fair fix for problems or added value compensation/ atonement. The findings showed the major importance of interpersonal skills of frontline employees who are directly facing and dealing with customer complaints. Although, the impact of an apology on recovery satisfaction is not as strong as the impacts of redress, attentiveness and explanations; However, Boshoff and Leong (1998) emphasized that an apology is the necessary first step in servicerecovery attempts. Davidow (2000) also reported that an apology, in particular, is important because it costs nothing yet significantly increases positive word-of-mouth activity. It implies that providing an apology to complainants should be given a high priority and be accompanied by other responses such as attentiveness, explanations or compensation. Finally, it is likely to state that customer complaints contain constructive information which can help the bank to recognize their problems, recover their service failures and maintain customers’ loyalty. Therefore, establishing clear complaint procedures can help customers to know how to complain and where to log complaints, should be highly considered.
A term that is synonymously used for a problem that a customer has with a service is “service failure” . Service failures are inevitable and occur in both the process and outcome of service delivery. In online business, just as the same as offline businesses, service delivery fails when it can not deliver services as promised. In these situations, there is a gap between customer’s expectations and performance of the system, which leads into dissatisfaction. Some authors [5,18] determined failure as a major cause of customer defection. To avoid such defections, literature suggests two kinds of strategies. First is to get things right the first time , by proactive planning, training and anticipating customer’s needs and possible service failure and eliminating the most likely areas of them. Yet, service failures are not completely avoidable. Thus, if they occur, the second type of strategy called servicerecovery should be activated in order to satisfy and retain the unhappy customer. Servicerecovery could be considered as a proactive process, which seeks out and deals with failure . However, most of the studies consider servicerecovery as a process, which should be invoked after the complaint is reported. Servicerecovery is of crucial importance, because if successfully implemented, it will lead into positive WOM (Word Of Mouth) and customer loyalty . Otherwise, poor implementation is a major cause of dissatisfaction [2,16] and results in customer defection  and / or his exit .
72 Ha and Jang’s study (2009), examined whether the customer’s response of perceived justice regarding future behavioural intentions differs across customers’ relationship quality levels. Theirs’ study outcome showed that high recovery efforts were high appraised steadily in terms of perceived justice when that was compared to low recovery efforts irrespective of the level of the relationship quality. Moreover perceived justice through the servicerecovery efforts has a positive weight on the customer’s future behavioural intentions. Finally through hierarchical regression analysis it was suggested that relationship quality has a moderating role among perceived justice and behavioural intentions in the distributive and procedural justice dimensions. The appliance of justice theory in servicerecovery in tourism and hospitality services is in its infancy phase (Becker, 2000; Collie et al., 2000). Particularly in the airline industry there is a gap as far as concerning the servicerecovery and justice theory with the majority of similar studies focusing in the hospitality industry -hotels and restaurants mainly- leaving outside the airline industry. (DeWitt et al., 2008; Kim et al., 2009; Sparks and Fredline, 2007; Yuksel et al., 2006; Karatepe, 2006).
An important element of servicerecovery is compensation, hence this research addresses the key question of how much should a business compensate consumers for a service failure in order to maximize recovery performance? Existing evidence is inconsistent. Some studies report that high recovery is more effective in amending consumer dissatisfaction and emotion resulting from service failure (Bradley & Sparks, 2012; Choi & Choi, 2014; Maxham, 2001). Others find that overcompensating can be counterproductive, with Boshoff (2012) reporting that overcompensation produces lower satisfaction than a more moderate recovery and Noone (2012) revealing that low and high recovery cash offers induce similar perceptions of fairness. These contradictory and inconclusive findings suggest that more nuanced influences are at play. Thus, research revealing boundary conditions of recovery magnitude effects is worthwhile not only for theory development but also to provide practical insights as inconsistent findings are unhelpful in attempting to predict consumer response to recovery.
There are some limitations to this study. Fluctuating numbers of participants and feedback in the 2015 and 2016 data do not allow for straight-up comparison. Misunderstanding in the term “informal carer fully involved” may have produced ambiguous results. The 3-month period for the analysis of IRPs was randomly selected and may not be a representative sample. Despite the admission of 45 consumers during the assessed 3 months, only 12 rated their progress. According to PARC staff, the 3-month period was particularly out of character compared with the over- all response rates throughout the lifetime of the service. Future analysis might be more accurate if data of IRPs were equally spread out over a 12-month period as, for example, for 1 month every quarter of the year. Moreover, the low response rate did raise the question as to why the number of completed ratings was that small. In consultation with PARC staff, it became apparent that some consumers found it at times too hard to focus on the questions, let alone providing an answer or a score. In such cases, a feasible strategy to overcome this issue may be the employment of people with lived experience, to aid in the data collection.
Cloud Computing is a technology that provides services to the users and access to the resources regardless of geophysical location. It consists of several service models for different types of organizations. These services may consist of private or global services. Cloud computing consists of three major services namely Infrastructure as a Service, Platform as a Service and finally Software as a Service. These services are scalable on consumer demand that can be priced on a pay-per-use basis (Bohm et al., 2010). However, cloud services are demanded in enterprise organization for the last several years (Sriram and Khajeh- Hosseini, 2010). Nevertheless, cloud may consist of several data centers or individual data centers that are dependent on the size of organization. Cloud often leverages massive scale, homogeneity, virtualization, resilient computing, low cost software, geographic distribution, service orientation, and advanced security technologies. The last aspect is composed of four deployment models in cloud computing including Private, Community, Public, and Hybrid Clouds.
ABSTRACT: With the rapid popularity of cloud computing paradigm, disaster recovery using cloud resources becomes an attractive approach. This paper presents a practical multi-cloud based disaster recoveryservice model: DR- Cloud. With DR-Cloud, resources of multiple cloud service providers can be utilized cooperatively by the disaster recoveryservice provider. A simple and unified interface is exposed to the customers of DR-Cloud to adapt the heterogeneity of cloud service providers involved in the disaster recoveryservice, and the internal processes between clouds are invisible to the customers. DR-Cloud proposes multiple optimization scheduling strategies to balance the disaster recovery objectives, such as high data reliability, low backup cost, and short recovery time, which are also transparent to the customers. Different data scheduling strategies based on DR-Cloud are suitable for different kinds of data disaster recovery scenarios.Experimental results show that the DR-Cloud model can cooperate with cloud service providers with various parameters effectively, while its data scheduling strategies can achieve their optimization objectives efficiently and are widely applicable.