Impact of Service Recovery on Customer Loyalty: A Study of E-Banking in Spain

The purposes of this study are twofold: (i) to propose and apply a scale to measure service recovery in the electronic banking (e-banking) sector; and (ii) to examine the relationship between service recovery and customer loyalty in the setting of e-banking services. An online questionnaire is used to survey 123 Spanish customers of e-banking services using a modified version of the E-RecS-QUAL scale. The data are analysed by exploratory factor analysis to: (i) test the applicability of the scale to the setting of online bank services: and (ii) generate a model including constructs for e-recovery and e-loyalty. The study reassures online banks that a modified version of the E-RecS-QUAL scale is an appropriate instrument for measuring service recovery. The study also provides empirical evidence that responsiveness to requests and complaints has a positive influence on e-loyalty. The study is the first to provide definitive empirical evidence of the presumed link between the recovery dimensions proposed in the E-RecS-QUAL scale and the construct of e-loyalty.recovery; electronic commerce; electronic service quality; E-RecS-QUAL.

Participation with online recovery specific groups - findings from the UK Life in Recovery survey 2015

As the concept of recovery has expanded, and become embedded in drug and alcohol policy, so too has the proliferation of online recovery support. This article explores data from the UK Life in Recovery survey, focusing on online recovery methods categorized as online groups, websites, and smartphone applications. Although 301 people (39.30%) reported involvement with at least one online recovery method, chi-squared tests reveal significant associations between people in stable recovery (5 years or more) and the use of recovery applications (Cramer’s V = .114), as well as between people in full-time employment and the use of online recovery websites or recovery applications. Having dependent children was not associated with use of any online recovery method, yet gender was (Cramer’s V = .088). This study extends the relatively limited literature and knowledge base of online recovery methods. Although the evidence points to higher engagement of recovery websites and apps for people in stable recovery, encouraging online recovery methods for individuals in early recovery may support recovery efforts when the risk of returning to substance misuse and active using social networks remains high. Further research should investigate the mechanisms of recovery change, with a focus on gender differences

Integrating computerized linguistic and social network analyses to capture addiction recovery capital in an online community

The article describes a new methodology designed with the aim of finding a comprehensive, unobtrusive, and accurate way of capturing social recovery capital development in online communities of recovery from alcohol and drug (AOD) addiction. Recovery capital was conceptualised as both engagement in the online recovery community and identification with the community. To measure recovery capital development, naturally occurring data were extracted from the social media page of a specific recovery program, with the page being set up as a resource for a face-to-face recovery program. To map engagement with the online community, social network analysis (SNA) capturing online social interaction was performed. Social interaction was measured through the linkages between the online contributors/members of the online community as represented by program clients, staff, and supporters from the broader community. To capture markers of social identification with the online community, computerised linguistic analysis of the textual data (content from posts and comments) was conducted. Recovery capital captured in this way was analysed against retention data (a proxy outcome indicator), as days spent in the (face-to-face) recovery program. The online data extracted was linked to participant data in regards to program retention to test prediction of a key recovery outcome. This approach allowed the examination of the role of online support communities and assessment of the association between recovery capital (developed via the online community of recovery) and recovery outcomes

Automated monitoring of recovered water quality

Laboratory prototype water quality monitoring system provides automatic system for online monitoring of chemical, physical, and bacteriological properties of recovered water and for signaling malfunction in water recovery system. Monitor incorporates whenever possible commercially available sensors suitably modified

Service Recovery in the Consumer Goods Industry: the Moderating Role of Online Versus Offline Environment

Service recovery is an important function for companies to maintain satisfied customers. In order to have successful service recovery, customers’ expectations should be recognized and met. This paper examines customers’ expectations towards service recovery in online versus offline environment. Due to the growth of Internet, online service recovery has become more popular than ever before. Thus, it is important to recognize the differences between online and offline customers’ expectations. This thesis includes an empirical study which reveals several following key findings. Complaining online is highly preferred over complaining offline and at the same time those who complain online have higher expectations towards service recovery. The biggest difference between online and offline customers is the expectations towards the quickness of the company’s response, since online customers are expecting quick response (1-2 days) significantly more than offline customers. Apology is the most expected factor in service recovery among both online and offline customers. Last finding is that a new product or a voucher that offers a new product are the most expected compensations in both online and offline customers. By these findings, this thesis fills the research gap of examining customer’s expectations towards service recovery in online and offline environment

Improving A*OMP: Theoretical and Empirical Analyses With a Novel Dynamic Cost Model

Best-first search has been recently utilized for compressed sensing (CS) by the A* orthogonal matching pursuit (A*OMP) algorithm. In this work, we concentrate on theoretical and empirical analyses of A*OMP. We present a restricted isometry property (RIP) based general condition for exact recovery of sparse signals via A*OMP. In addition, we develop online guarantees which promise improved recovery performance with the residue-based termination instead of the sparsity-based one. We demonstrate the recovery capabilities of A*OMP with extensive recovery simulations using the adaptive-multiplicative (AMul) cost model, which effectively compensates for the path length differences in the search tree. The presented results, involving phase transitions for different nonzero element distributions as well as recovery rates and average error, reveal not only the superior recovery accuracy of A*OMP, but also the improvements with the residue-based termination and the AMul cost model. Comparison of the run times indicate the speed up by the AMul cost model. We also demonstrate a hybrid of OMP and A?OMP to accelerate the search further. Finally, we run A*OMP on a sparse image to illustrate its recovery performance for more realistic coefcient distributions