Improving Customer Experience throughout the Customer Journey in the Big Data Era

My PhD dissertation focuses on how firms should adapt their strategies to improve customer engagement throughout customer journey. My first paper examines firm-customer conversations on social media. Many firms struggle with how to craft their messages in conversations with customers on social media, and the lack of guidance for interacting with customers is among the top social media challenges reported by firms. The problem is compounded by the fact that these conversations take place in different, simultaneous threads, each of which potentially requiring a different approach. This paper studies how firms can adapt their responses in individual social media conversations such that these conversations become more favorable to the firm in terms of valence and arousal. Drawing on Speech Act Theory and based on an analysis of 1.6 million tweets capturing over 210,000 conversations involving the four major US banks across 10 years, the paper shows how firms, depending on the ongoing conversation, should adjust their firm-generated content (FGC) in terms of its valence, arousal, subjectivity, and topic. In my second paper I include all text communications recorded between a vacation rental firm and customers to realize how emotional content in firm messages can affect important customer outcomes. I conduct a thorough literature review to identify prior research on emotions in firm-customer communications. I suggest a novel deep learning tool in Natural Language Processing to extract and measure emotion in firm messages. To measure the outcomes of such emotional content in firm messages, I use repurchase as it is a critical indicator of loyalty

A method for improving the efficiency of DNA extraction from clotted blood samples

Funding information: This study was supported by a grant from the Research Council of the Mashhad University of Medical Sciences (Grant No: 931680). The authors would like to thank Dr. Hossein Eshghi at Department of Chemistry, Faculty of Science, the Ferdowsi University of Mashhad for his assistance in the experiment and Mohammad Sadegh Khorami who contributed to this study. We are also particularly grateful to the Research Council of the Mashhad University of Medical Sciences (MUMS) for the financial support of this studyPeer reviewedPublisher PD

Leishmania spp. proteome data sets: a comprehensive resource for vaccine development to target visceral leishmaniasis

Visceral leishmaniasis is a neglected infectious disease caused primarily by Leishmania donovani and Leishmania infantum protozoan parasites. A significant number of infections take a fatal course. Drug therapy is available but still costly and parasites resistant to first line drugs are observed. Despite many years of trial no commercial vaccine is available to date. However, development of a cost effective, needle-independent vaccine remains a high priority. Reverse vaccinology has attracted much attention since the term has been coined and the approach tested by Rappuoli and colleagues. This in silico selection of antigens from genomic and proteomic data sets was also adapted to aim at developing an anti-Leishmania vaccine. Here, an analysis of the efforts is attempted and the challenges to be overcome by these endeavors are discussed. Strategies that led to successful identification of antigens will be illustrated. Furthermore, these efforts are viewed in the context of anticipated modes of action of effective anti-Leishmania immune responses to highlight possible advantages and shortcomings

Recent updates and perspectives on approaches for the development of vaccines against visceral leishmaniasis

All rights reserved. Visceral leishmaniasis (VL) is one of the most important tropical diseases worldwide. Although chemotherapy has been widely used to treat this disease, problems related to the development of parasite resistance and side effects associated with the compounds used have been noted. Hence, alternative approaches for VL control are desirable. Some methods, such as vector control and culling of infected dogs, are insufficiently effective, with the latter not ethically recommended. The development of vaccines to prevent VL is a feasible and desirable measure for disease control, for example, some vaccines designed to protect dogs against VL have recently been brought to market. These vaccines are based on the combination of parasite fractions or recombinant proteins with adjuvants that are able to induce cellular immune responses, however, their partial efficacy and the absence of a vaccine to protect against human leishmaniasis underline the need for characterization of new vaccine candidates. This review presents recent advances in control measures for VL based on vaccine development, describing extensively studied antigens, as well as new antigenic proteins recently identified using immuno-proteomic techniquesThis work was supported by grants from Instituto Nacional de Ciência e Tecnologia em Nano-Biofarmacêutica, Rede Nanobiotec/Brasil-Universidade Federal de Uberlândia/CAPES, PRONEX-FAPEMIG (APQ-01019-09), FAPEMIG (CBB-APQ-00819-12 and CBB-APQ-01778-2014), and CNPq (APQ-482976/2012-8, APQ-488237/2013-0, and APQ-467640/2014-9). EAFC and LRG are recipients of the grant from CNPq. MACF is the recipient of grants from FAPEMIG/CAPE