Characterization of the hotel sample.
\r\n\tThe discovery of Nylon by Wallace Hume Carothers, a Harvard-educated world-renowned organic chemist born in Burlington, IA in 1896, successfully crowned the attempts developed by E.I du Pont de Nemours & Company to investigate the structure of high molecular weight polymers and to synthesize the first synthetic polymeric fibre.
\r\n\tWhen it hit the market, it was in the form of stockings and all the women in the US wanted to get their hands on a pair. Despite the successful launch of Nylon on the synthetic fibre market and the high expectations created by its extraordinary features, the unexpected war events in 1941 diverted the production of the new synthetic fibre almost exclusively on military applications. Parachutes, ropes, bootlaces, fuel tanks, mosquito nets and hammocks absorbed the production of Nylon, which helped to determine the WWII events. When the war ended and production returned to pre-war levels, consumers rushed to the department stores in search of stockings, accessories and high-fashion garments.
\r\n\tEven if the world of high fashion now seems to more appreciate the use of natural fibres, Nylon is one of the most widely used polymers for the production of technical fibres and fabrics, automotive and micromechanical components. The global nylon 6 & 66 market is expected to reach USD 41.13 billion by 2025, by the following growth at 6.1% CAGR owing to the Increasing focus on fuel-efficient and less polluting vehicles.
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\r\n\tThe amazing success story of Nylon still continues. While its wide availability inspired the development of innovative applications, such as the additive manufacturing, on the other hand, proper disposal after use of high amounts of Nylon resin energised the development of efficient recycling methodology, including chemical recycling. Moreover, the production of Nylon precursors from biomass has become desirable due to the depletion of fossil hydrocarbons and to reduce greenhouse gas (GHG) emissions. This unique combination of technical and socio-economic driving forces is one that aims to further promote the development of Nylon as one of the most suitable ""best polymers"" with a low ecological footprint.
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\r\n\tThe aim of this publication is to unveil the relationships between the chemical structure and the outstanding properties of the broad family of polyamides and to describe the most recent use of Nylon in fostering new applications and promoting a culture aware of environmental sustainability.
Telomeres are specialized functional complexes that protect the ends of eukaryotic chromosomes. The telomeric DNA sequences are, in most species, tandem repeats of a short hexameric sequence unit [1]. Overall, telomere sizes range from about 15 to 20 kbp at birth to sometimes less than 5 kbp in chronic disease states. Telomeric repeats help maintain chromosomal integrity [2]. Evolutionary conservation of this repetitive DNA sequence family might indicate that sequence is essential to the cellular function [3]. Telomeric DNA sequences and structure are similar among otherwise widely divergent eukaryotes. The telomeric repeat unit is TTAGGG for humans as well as other vertebrates [4]. The ends of telomeres are protected and regulated by telomere binding proteins and form a t loop structure [2, 5]. Mainly, the inability of DNA polymerase to replicate the end of the chromosome during lagging strand synthesis results in the loss of telomeric repeats when cell divides. This phenomenon eventually results in a growth arrest and telomeres become critically shortened when multiple chromosome end fusions occur, resulting in a loss of cell viability [2]. Telomere shortening provides a barrier to cancer progression by preventing immortalization and the majority of the cancer cells depend on the activation of telomerase to gain proliferative immortality [2, 6]. But on the other hand, telomere shortening correlates with cellular aging. Stem and progenitor cells express low levels of telomerase [6].
Greider and Blackburn identified a specialized DNA polymerase in extracts from the Tetrahymena that extends the chromosome ends in eukaryotes [7]. Telomerase adds multiple copies of certain DNA unit to the terminal portion of one strand of the repeat tract [1, 4]. This process is required for genomic stability and cell viability. Telomerase is a specialized reverse transcriptase. Telomerase subunit TER identified in the late 1980s and catalytic subunit TERT in 1997. Subsequent studies showed that the TER and TERT together form a tight complex that is sufficient for telomeric DNA repeat synthesis in vitro [6]. TER contains RNA template for reverse transcription [8–10]. TERT contains discrete domains that carry out the mechanically complicated reaction of nucleic acid and nucleotide binding and selectivity in a coordinated manner during telomerase replication [8]. Despite only TERT and TER are required for telomerase catalytic activity in vitro, the physiologically functional holoenzyme is a multisubunit ribonucleoprotein (RNP). Tetrahymena telomerase holoenzyme contains eight subunits, each of which is essential for telomere length maintenance [10].
\nTelomerase is a very important enzyme for the aging process and carcinogenesis. Primary human cells exhibit limited replicative potential but the cancer cell lines are immortal with passage in culture [11]. In embryonic stem cells telomerase is activated and maintains telomere length but the level of telomerase activity is low or absent in the majority of the stem cells. Thus, even in stem cells, except embryonic stem cells and cancer stem cells, telomere shortening occurs, possibly at a slower rate than that in normal somatic cells [12].
\nTo grow indefinitely, human cancer cells must compensate the progressive loss of telomeric DNA by cell division [13]. This immortality is mainly a result of telomerase activity. Telomerase is expressed in more than 85% of cancer cells [14–17], but in some cells, the telomere length could be maintained in the absence of telomerase. It has been deduced that one or more alternative telomerase-independent mechanisms exist in human cells [13].
Synthesis of DNA at chromosome ends by telomerase may be necessary for indefinite proliferation of human cells. According to results of Kim et al. in cultured cells representing 18 different human tissues, 98 of 100 were immortal and none of the 22 mortal populations were positive for telomerase. Similarly, 90 of 101 biopsies representing 12 human tumor types and none of the 50 normal somatic tissues were positive [14]. Tahara et al. observed that the positive telomerase activity in 28 hepatocellular carcinoma (HCC) tissues of 33. Interestingly, hepatitis B virus-positive patients were telomerase positive. Also, in 19 of 38 hepatitis tissues and 6 of 8 cirrhotic liver tissues, weak telomerase activity was detected. These results indicate that the expression of telomerase may play a crucial role in hepatocarcinogenesis [15]. Ferber et al. detected that the integrations of the hepatitis B virus and human papillomavirus into the hTERT gene in liver and cervical cancers [18]. Hiyama et al. showed that the 95% of the advanced stage breast cancer tissues have telomerase activity [16].
\nTelomerase is a molecular target since its discovery. The most important disadvantage of chemotherapy drugs used today is that they are not selective, they have effect on normal healthy cells together with cancer cells. Telomerase inhibition enables more specific ground because the telomerase is not detected in most normal tissues [2, 17]. Differences in telomerase expression, telomere length, and cell kinetics between normal and cancer tissues suggest that targeting telomerase for cancer therapy may be relatively safe [19]. Telomerase inhibitor effects on stem cells may thus be minor because these telomerase-competent cells only proliferate intermittently and typically have much longer telomeres than cancer cells [2].
\nExperimental and clinical studies for telomerase inhibition are currently carried out in many different ways, such as inhibition by nucleotides and nucleoside-type reverse transcriptase inhibitors; direct inhibition by nonnucleoside small molecules; oligonucleotide inhibitors of telomerase activity; gene therapy; telomerase-specific phosphorylation inhibitors; G quadruplex stabilizers; and TER directed hammer head ribozymes [2, 17, 20, 21].
\nIn recent studies, some of the synthetic telomerase inhibitors were tried to bone marrow, prostate, brain, breast cancer, and pancreas cancer cells and there was a decrease in the number of cancer cells [17]. Telomerase inhibitor imetelstat (GRN163L) is the first telomerase inhibitor to advance to the clinical development (www.geron.com/imetelstat). Some izothiazolone derivatives show telomerase inhibition properties [20]. 2-[(E)-3-naphtalen-2-yl-but-2-enoylamino]-benzoic acid was reported as a selective telomerase inhibitor [20, 22]. According to the results of our previous studies (unpublished), some of Imidazo[1, 2-a]pyrazine derivatives can be used for telomerase inhibition. There are some studies which draw attention to various enzyme inhibition and anticancer activities of İmidazo(1,2-a)pyrazine derivatives [23–28].
\nIn addition to synthetic compounds, various chemical compounds that occur naturally in plants like allicin, curcumin, and silbinin have been suggested as telomerase inhibitors (Figures 1 and 2) [29]. Allicin is organosulfur compound obtained from garlic that can inhibit telomerase activity and induce apoptosis of gastric cancer SGC-7901 cells [30]. Milk thistle’s silymarin and silibinin have also been investigated by some researchers in terms of telomerase inhibition and activation. The treatment of the K562 human leukemia cell line with silymarin resulted in a significant inhibition of telomerase activity [31]. In Yurtcu et al.’s study, combination of silymarin and doxorubicin and silymarin alone inhibited telomerase activity in HepG2 hepatocellular carcinoma cell line [32]. But silymarin may activate the telomerase in noncancerous cells according to the results of Parzonko et al. In this study, silymarin increased telomerase activity in endothelial progenitor cells [33]. Thelen et al. showed that inhibition of telomerase activity by silibinin in prostate cancer cells [34]. Silibinin can also inhibit hTERT gene expression in T47D breast cancer cells. Silibinin and curcumin combination could be more effective in the way of inhibition of telomerase [35]. Curcumin is a phenolic compound isolated from the rhizome of the Curcuma longa L. Curcumin has antitumor, antiangiogenic, and apoptotic properties. Chakraborty et al. suggested that telomerase inhibition is a main mechanism of curcumin-induced apoptosis in human leukemia cell line K-562 [36]. In Ramachandran et al.’s study, increasing concentrations of curcumin caused a steady decrease in the level of hTERT mRNA and inhibited telomerase activity in MCF-7 breast cancer cells [37].
Chemical formula of some natural telomerase inhibitors.
Various chemical compounds that occur naturally in garlic, turmeric, grape, and milk thistle are telomerase activity modifiers.
Antibiotics oflaxacin and levofloxacin inhibit the telomerase in cell extracts. Helenalin (a natural sesquiterpene lactone), polyunsaturated fatty acids with cis-double bond, also inhibit the telomerase [20]. However, some dietary polyphenols have been suggested as telomerase inhibitors [38]. Major tea catechin epigallocatechin gallate strongly and directly inhibits telomerase. It is suggested that telomerase inhibition could be one of the major mechanisms underlying the anticancer effects of tea [39]. Naasani et al. proposed that the inhibition of telomerase is a key mechanism in cancer inhibition by epigallocatechin gallate [40]. Besides, epigallocatechin gallate inhibits telomerase and induces apoptosis in drug resistant lung cancer and cervical cancer cells [41, 42]. Epigallocatechin gallate and sulforaphane combination treatment induce apoptosis in paclitaxel-resistant ovarian cancer cells through hTERT and Bcl-2 downregulation [43]. Sulforaphane (SFN) is a dietary isothiocyanate. SFN decreases viability and telomerase activity in hepatocellular carcinoma Hep3B cells. Moon et al. suggested that the reactive oxygen species (ROS) are essential for the suppression of SFN-mediated telomerase regulation [44]. According to Meeran et al.’s results, SFN causes epigenetic downregulation of hTERT expression in human breast cancer cell lines [45].
\nIt would suggest that telomerase inhibitors might be most effective in combinations with other conventional or experimental cancer treatments [2].
\nThere are alternative mechanisms for telomerase maintenance (ALT) and some rare telomerase negative human cancers. Unfortunately, telomerase inhibitors might result in the emergence of drug resistant telomerase-independent cancer cells [2].
\nTelomerase inhibitors can be useful for the treatment of some other diseases. Blackburn proposed that telomerase might be target for drugs against eukaryotic pathogenic or parasitic microorganisms, such as parasitic protozoans or pathogenic yeast [4]. Actually, some studies about telomerase activities of eucaryotic pathogenic microorganisms were achieved. Cano and colleagues identified telomerase activity in extracts of Trypanosoma brucei, Leishmania major, and Leishmania tarentolae and they proposed as a target the inhibition of telomerase activity [46].
\nThe catalytic subunit of telomerase (TERT) shows a striking similarity to retroviral reverse transcriptases (retroviral RTs) and viral RNA polymerase [8]. Rubomycin and some of its analogs were demonstrated to be potent inhibitors of retroviral RTs and also inhibitors of telomerase [20].
\nTelomerase inhibition is a good and specific target. Because the telomerase is not detected in most normal tissues [2, 17], differences in telomerase expression, telomere length, and cell kinetics between normal and cancer tissues suggest that targeting telomerase for cancer therapy may be relatively safe [19].
Proliferation of telomerase negative cells results in progressive telomere shortening. Cellular senescence is thought to serve as a protecting mechanism against cancer, but subsequent telomere dysfunction will be involved in tumorigenesis late in life [20]. Telomere shortening may cause aging and death. Some evidence suggests that the progressive loss of telomeric repeats of chromosomes may function as a molecular clock that triggers senescence [47–49]. Bodnar et al. analyzed two telomerase-negative normal human cell types. The cells were transfected with vectors encoding to human telomerase catalytic subunit. Telomerase expressing clones had elongated telomeres and showed reduced senescence signs [47]. Numerous epidemiological studies show that shorter telomeres in humans are associated with many age-related diseases [49, 50]. Humans with shorter than average telomere length are at risk of dying from heart disease, stroke, or infection. Individuals with chronic stress or infections have accelerated telomere shortening compared to age-matched counterparts [51].
\nTelomerase-related gene mutations result in some diseases. The first disease-associated with mutations in human telomerase is dyskeratosis congenita (DKC) [20]. The X-linked form of the DKC is caused by mutations in the gene encoding dyskerin (DKC1). It has been suggested that DKC may be caused by a defect in rRNA processing. Dyskerin is associated also with human telomerase RNA [52]. Autosomal dominant form of DKC is closely associated with the mutations in the TER and defective telomere maintenance [53]. Mitchell et al. find that primary fibroblasts and lymphoblasts from DKC affected males have a lower level of telomerase RNA, produce lower levels of telomerase activity, and have shorter telomeres [52].
\nMore recently, telomerase mutations have been detected in the context of aplastic anemia, Hoyeraal-Hreidarsson syndrome, idiopaty pulmonary fibrosis, ataxia telangiectasia, Werner syndrome, Bloom syndrome, Nijmegen breakage syndrome, and ataxia telangiectasia-like disorder [20, 54]. The unifying molecular characteristics of these diseases are that patients harbor telomeres that are significantly shorter than the age-matched control subjects [54]. Not only the genetic modulation but also the epigenetic mechanisms may be responsible for the diverse expression status of telomerase in a tissue and cell-type dependent manner [55].
\nAlso, telomere erosion occurred by excessive T-cell proliferation in AIDS or X-linked Lymphoproliferative syndrome. However, cardiovascular diseases have been recently linked with telomere-dependent senescence [20].
\nBecause of that, telomerase activators are important for antiaging and telomerase-dependent disease treatments. Telomerase gene therapy in adult and old mice delays aging and increases longevity [56, 57]. TERT exhibits neuroprotective effects in experimental models of neurodegenerative disorders suggesting that inducing the telomerase activity in neurons may protect against age-related neurodegeneration and Alzheimer’s disease [58]. Geron Corp. and TA Therapeutics developed a single molecule telomerase activator, TAT2 (cycloastragenol) [29]. Cycloastragenol is an aglycone of astragaloside IV (Figure 3). It was first defined when screening Astragalus membranaceus extracts for antiaging properties and a potent telomerase activator in neuronal cells [59]. The extract of Astragalus membranaceus was licensed as a nutritional supplement called TA 65 (TA sciences, Geron Corp.). This extract could elongate short telomeres and increase health span of adult mice without increasing cancer incidence [60]. Also, this natural-based product can elongate short telomeres in human leukocytes [61].
Chemical formula of some natural telomerase activators.
Furthermore, certain phytochemicals like resveratrol and genistein have been shown to activate telomerase (Figure 3). Genistein is a natural isoflavone found in soybean products. Genistein inhibits the transcription of hTERT in breast MCF10AT benign cells and MCF7 cancer cells [62]. Genistein also decreases telomerase activity in prostate cancer cells [63, 64]. Ouchi et al. showed that the expression of hTERT and c-myc mRNA was downregulated by genistein in prostate cancer cells [63]. But, physiologically achievable concentrations of genistein enhance telomerase activity in prostate cancer cells [65]. Genistein may activate telomerase activity at low concentrations and inhibit telomerase activity at higher treatment concentrations [29].
\nThe trans-izomer of resveratrol is a natural phytoalexin present in a limited number of Spermatophyta, especially in grapes, fruits, and root extracts. It is synthesized in response to stress conditions. Resveratrol has a direct inhibitory effect on cell proliferation. Studies showed that resveratrol treatment downregulates the telomerase activity and levels of hTERT in MCF7 breast cancer cells [66]. Besides, relatively high concentrations of resveratrol were found to be able to downregulate telomerase activity in human colon cancer cells [67]. Several compounds like resveratrol have been shown to act as both inhibitors and activators of telomerase though this may be due to treatment concentration or cell type differences. Resveratrol has been shown to inhibit telomerase activity in cancer cells but activate telomerase in epithelial and endothelial progenitor cells [29, 68].
\nThere are few studies about the effects of Gingko biloba on telomerase activity. Dong et al. showed that Gingko biloba extract increases telomerase activity in endothelial progenitor cell [69].
\nAlso, HMG-CoA reductase inhibitor therapy and statin treatment are associated with delay of senescence and reduced cardiovascular diseases [29]. Moreover, in our study (unpublished) it was observed that dimetylsulfooxide (DMSO), which is used for solving chemical substances increases telomerase activity. In the study of Alfonso-De Matte et al., DMSO increased telomerase activity in some cell lines that is known to have no/low telomerase activity [70]. Also, in a study which was carried out about differentiation of embryonic stem cell on rats, TERT gene upregulated as a result of dimetylsulfooxide (DMSO) application on each individual and telomerase activity increased [71].
\nTelomere shortening correlates with cellular aging [6]. Telomerase-related gene mutations also result in some diseases [20]. Because of that, telomerase activators are important for antiaging and telomerase-dependent disease treatments.
I thank Dr. Ismail Kayagil for photographs.
Consumers increasingly use online means to share their experiences and perceptions about the quality of services they use. Every day overwhelming volumes of information are produced and published online, and these seem to exert a critical influence on service choices and purchase decisions. This context is very much facilitated by the dissemination of technologies that encourage the production and sharing of user crated content. Likewise, there is a growing familiarity of customers with Internet technologies that is fueling this trend. Service providers, by their turn are keeping the pace by implementing and adhering to online tools that offer efficient ways for users to make their ideas available to vast audiences in a fast manner [1]. The importance of such form of communication, known as electronic word-of-mouth (eWOM) or word-of-mouse, has been extensively acknowledged in the literature, often being referred as a more effective means to influence customers’ consumption decisions than other tools, such as personal sales or advertising, because it can be perceived by costumers as a rather reliable source of information. Whereas customer reviews are now a common feature in many company websites, and platforms, research is still necessary to gain knowledge about how to effectively use eWOM data as a valued adding tool to inform customer decision making, as well as to guide managerial actions towards service improvement and innovation. This study proposes a contribution in this direction.
The study describes the development of a methodology to support the analysis of eWOM, in order to facilitate the systematic analysis and visualization of insights from online reviews concerning service quality. The proposed methodology is useful to both academics and managers as it proposes a concise display of the data analysis results, allowing for a quick identification and debate about priorities and concerns for quality management, while building on a frame of reference for quality attributes that is derived from service management literature. The study was developed in the particular context of the hotel industry in Portugal, as a representative business sector for the volume and reach of online consumer reviews. The development of the proposed data analysis and display method was built on a selected sample of customer reviews extracted from a prevalent online service for hotel bookings. The hotel industry offers an adequate and rich context for the nature of this study for the fact that the travel and tourism industry is known for being a pioneer for the growing trends of promotion and distribution of services over the Internet [2].
The chapter offers an approach for making sense of customer reviews, by identifying relevant service quality dimensions embedded in the voices of hotel customers, while offering a concise tool for the visualization of the results. To this end, the study employed the principles of importance-performance analysis (IPA), a marketing research technique acknowledged for offering a concise graphical representation of results, to develop a framework for identifying salient hotel service attributes from the available and uncategorized information provided by customer reviews. The study offers a timely approach for assisting managers in the task of sense making from growing volumes of user generated information from a key source of information for the identification of priorities for service improvement and innovation.
Following this introduction, this chapter offers in Section 2 an overview of the conceptual background of the study, namely addressing on the topics of service quality and service quality assessment approaches while discussing some of the key challenges in measuring service results. In Section 3 is devoted to describe the application of the importance-performance analysis (IPA) approach to the context of eWOM in hotel services, and to presented and discuss some representative results of the application of this methodology to extract meaning from user generated context. The chapter closes with a presentation of key contributions and conclusions in the last section.
The understanding of service quality and the deployment of robust and replicable methods to conduct its assessment have been in the core of the agendas of service management scholars and practitioners for many years. Despite an early consensus about the relevance of service quality for customer satisfaction, loyalty and company’s profitability [3, 4], the operationalization of methods and tools to measure service quality and inform managerial practice and consumer decision making has generated extensive debate and challenges. Many of the results of service experiences lack tangibility and for this reason many approaches for service quality assessment rely on information from customers’ “perceived” experiences [5, 6].
Many of the prevalent approaches to capture consumers quality perceptions build on the development of survey methods for data collection, consisting of multi-item scales. Such multidimensionality is aligned with the conceptualization of services as experiences that enact perceptions about multiple attributes and dimensions that affect customer value such as service responsiveness, reliability, and even elements such as the characteristics of the tangible elements such as service facilities, equipment, etc., and the performance and empathy of service professionals. In service experiences customers receive a combination of outcomes including direct process results (e.g., availability of required items in a retail store, on-time arrival to a flight destination in transportation services, etc.) along with other results related to the process experience resulting from customers’ contact and involvement in the service process (e.g., store atmosphere in retail services, comfort in a flight, etc.). Service quality is therefore conceptualized as a construct, featuring distinct dimensions that correspond to the diverse benefits that a customer can derive from a service. These dimensions of service quality are present across the prevalent service quality models and mirrored in the generalized generic scales such as SERVQUAL, SERVPERF, along with other sector specific scales where items are adapted to business particularities, such as in retail, health or hospitality and tourism services. Prevalent models account for the recognized dual nature of service quality determinants, i.e. the quality of service outputs as well as the quality of the experience with the delivery processes [4].
Overall service quality models, and the derived methods for its assessment, analysis and interpretation are built on customers’ perceptions about the performance of service delivery, rather than on objective assessments of quality items [7, 8]. Perceived service quality is defined as the customer’s evaluation of the overall excellence of a service and has been persistently distinguished from objective quality measurements, which were typically associated to the quality assessment of manufacturing products. The use of perceived service quality models is motivated by the specific nature of service outputs, which involves both tangible and intangible components and, as such, are often hard to assess and can result into very heterogeneous evaluations across customers.
Despite of the popularity of the [quantitative] multi-attribute type of measurement that has prevailed in the service quality domain along the years, several debates have highlighted the limits of such instruments. Among these are the difficulties of interpreting and using the standardized results of multi-attribute measurements. Data collected in this form offers only limited information about the richness, and the details, that contextualize customer perceptions about a service. More importantly, survey data fails from capture information about contradictions in service experiences as the respondents are forced to aggregate their quality experiences into ratings for a limited number of items. Any comprehensive listing of all quality aspects would result into lengthy questionnaires that would exceed customer’s willingness to answer and therefore hurt the validity of the information collected. A customer of an accommodation service of asked to evaluate the friendliness contact employees is forced to choose a single point on a scale despite the number of contacts and different staff met whose behavior and friendliness might vary considerably.
Overall the standard attribute-based quality and satisfaction surveys are not perfect when it comes to capturing all relevant managerial information, and for this reason other complementary approaches have been advanced, such as focus groups studies, analysis of critical incidents, among others, in order to capture richer consumer insights. In this context, word-of-mouth, i.e. the expressions about the service experiences as expressed in the words of the consumers have always been acknowledged as an important source of information, and a key determinant for consumer choice. Generally, it is referred to as an informal and personal form of communication [9] that has been acknowledged by its influence for customers ‘decisions [10], being source of trusted information [11].
In recent years, the advent of electronic-word of-mouth (eWOM) has created a rich field of data for deepening the understating about consumer experiences. Differently from traditional WOM, the its electronic version eWOM offers the advantage of being preserved, and accessible, over time in a written format that can be revisited and analyzed in detail, with distinct lenses.
The volume and reach of eWOM content have expended enormously, and are increasingly calling for the development of methods and tools that can assist consumers and managers to filter and make sense, in a timely manner of such large and rich amount of information. Consumers are expressing their opinions using multiple sources that include blogs, online reviews, and social networking websites, while interacting virtually to share information about their experiences with all sorts of goods, services, and brands [12]. eWOM has been defined as “any positive or negative statement made by potential, actual or former customers about a product or company, that is made available to a multitude of people and institutions via the internet” ([1], p. 39).
The tourism sector is a prominent example of a setting where eWOM has grown in volume and popularity, notably by means of online reviews that are the concrete examples of electronic versions of traditional WOM and result in a volume of comments from travelers about their experiences, the products, and the services they find along their journeys [13]. eWOM is available for other tourist to read and revisit, as well as for service managers to learn about their experiences. In fact many of the tourism service providers actively encourage their consumers to post reviews on their sites, social media platforms and other sources of reference [14]. The growth in eWOM is motivating increased research attention in several fronts, such as the investigation of the impacts of eWOM on sales, on consumer behavior. In tourism industry the results support that eWOM is considered credible [15], reducing consumers resistance to booking [16] and affects the sales of hotel rooms [17] and the motivations to visit some specific destinations [18]. Despite the growing number of studies that cover, the field is still far from being fully covered, and is still very much concentrated in exploring the behavioral implications of eWOM on travelers [19]. In this study we take a different approach aimed at developing approaches to make sense of the rich information contained in the reviews’ texts with the purpose of advancing in the creation of tools to support data analysis and visualization that can assist managers and consumers in extracting valuable information from eWOM sources.
Importance-performance analysis is a popular approach for interpreting customer satisfaction and for setting up priorities for upgrading service quality proposed by [20]. IPA builds on customers’ assessments concerning the importance and the performance of quality attributes in order to diagnose areas for improvement—typically using data collected by means of questionnaires employing service scales. IPA offers a plot representation for the measurements for importance-performance, declared by customers, consisting of a four quadrants matrix. The IPA matrix plots these values against two axes: a vertical axis—for the values of performance of service attributes; and an horizontal axis—for the values of attribute importance (see Figure 1).
Quad chart illustrating the breakdown of traditional importance-performance analysis approach. Desirable re-allocation of resources would go from the lower right quadrant to the upper left quadrant. Source: Adapted from Martilla and James [20].
Such concise display enables the quick visual identification of what elements demand for managerial improvement actions (i.e. attributes ranked in the quadrant for high importance vs. low performance) as well as others where the providers efforts are potentially misplaced (i.e. attributes ranked in the quadrant for low (customer) importance vs. high (provider) performance).
Subsequent studies have proposed modified approaches building on the principles of the IPA framework, extending its scope of application. For example CIPA, that stands for “Competitive Importance Performance Analysis”, is focused on the gaps of the performance of a given service company and that of its competitors, offering a tool to diagnose which competitive attributes demand for improvement. In this adaptation the horizontal axis represents the differences between a company’s performance towards the other market players.
Other formulations of IPA aim to address criticisms about its assumptions, namely the independence between the importance and performance measures and the linear relationship between the attributes and the performance. The so-called IPA with the three factor theory employs also a matrix representation for the measurements but takes into account the fact that not all service attributes are equally important for customer satisfaction [21, 22, 23]. This approach distinguishes three types of factors: (i) basic factors, i.e. minimum requirements that cause dissatisfaction if not fulfilled while not leading to customer satisfaction if fulfilled; (ii) performance factors, i.e. elements that cause satisfaction or dissatisfaction, depending on their performance level and (iii) excitement factors that can increase customer satisfaction if delivered but do not cause dissatisfaction if not delivered [24]. The modified IPA approach employs this three factor theory [25] and uses estimations of the relative importance of the quality attributes, instead of using customer declared information. The importance-performance lens of analysis therefore offers a versatile methodology for approaching the prioritization of service attributes.
This study builds on prevalent approaches of extending the applications of IPA by developing a modified version of IPA for identifying areas for service improvement building on qualitative data in the context of hotel experiences.
The main purpose of this work is to develop a flexible and concise methodology to make sense for the ever growing online customer reviews that are available for a wide diversity of service business, in an abundant and unstructured manner. Despite the volume and richness of data available, the ability of both customers and providers to summarize and interpret customer generated content is still very limited and often done ad hoc by managers, therefore hurting its utility and value for customer decision and company improvements. Yet recent research results confirm that such sources of information are increasingly accessed by customers to support purchase decisions [26]. To this end, the study focuses on customer online reviews in the context of the hotel industry for several reasons. Tourism and hospitality services are experiential in nature which makes pre-purchase quality assessments rather difficult, leading customers to search for various clues and information to support their choices. In this context the opinions of other customers assume a critical role. In addition this service industry has a pioneering record in the utilization of online means for customer service interactions (e.g. travel reservations), and for the abundance of eWOM behavior.
The study addresses a sample of customer reviews for a selected number of hotels in a medium sized tourist destination city in Portugal available in the online reservation website
Hotel | Star rating | Rooms | Location* | Available services | Average price** |
---|---|---|---|---|---|
Moliceiro | 4 | 49 | 0 | 16 | € 99 |
Aveiro palace | 4 | 49 | 0 | 13 | € 62 |
Melia Ria | 4 | 128 | 10 min | 22 | € 94 |
Américas | 4 | 70 | 5 | 16 | € 79 |
Imperial | 3 | 107 | 0 | 8 | € 63 |
Jardim | 3 | 48 | 0 | 11 | € 56 |
Afonso V | 3 | 78 | 5 | 6 | € 49 |
Veneza | 3 | 49 | 0 | 7 | € 68 |
Aveiro center | 2 | 24 | 0 | 8 | € 58 |
J. Estevão | 2 | 12 | 1 | 6 | € 57 |
Salinas | 2 | 18 | 0 | 7 | € 58 |
Characterization of the hotel sample.
Walking time to the city center (minutes).
Standard double room, average.
The first column contains the hotel name, the second column the official star rating at the time of the study, the third contains the number of rooms and the fourth the estimated walking time to the city center. The fifth and sixth columns present the number of services available at the hotel and the average price per night, respectively.
The chosen hotel reservation Website exhibits written online customer reviews, organized into groups—positive and negative reviews—as well as a rating obtained from customer scoring. In order to guarantee reliability, i.e. that the reviews resort from individual experiences, the Website only allows for reviews from customer who have effectively made a reservation.
The IPA addresses the data from the sample of extracted customer reviews. The first step in the analysis involves the identification of the most frequent terms and expressions about the hotel experience as stated by customers, for which text mining tools were employed, including a preliminary cleaning of symbols and words with no relevant meaning, and the standardization of terms, whenever synonyms are used to refer to a same hotel service element. The terms and expressions with higher frequency were retained for inclusion in the IPA analysis. A second step involves the identification of dimensions of affinity for the service quality attributes present in customers’ statements. This process leads to the identification of three dominant service quality elements, motivating the expression of (positive or negative) customer opinions: room, location and staff. Whereas a more detailed list if attributes can be retained the choice is for the use of a more aggregated level of analysis given the exploratory nature of the study.
The IPA matrix for the 11 hotels is displayed in Figure 2, where the data points for importance-performance for the three salient attributes, room, location and staff are, respectively ●, ▲ and *. In the traditional IPA the horizontal and vertical axis represent the coordinates for the values of importance, and the performance as perceived by the customers, usually resulting from structured questionnaire answers, using ordinal scales (e.g. 1–7), where customers sate their expectations (i.e. interpreted as importance) and service perceptions (i.e. experienced performance). In the current study, and given the qualitative nature of the available data—the reviews—the values for the matrix coordinates are obtained as follows.
Modified IPA graph for the hotel sample in the study.
For each service attribute (room, location and staff) the total frequency (considering all the terms and expressions associated to a given service attribute) is employed as a proxy for the importance of the attribute, therefore assuming, that customers express more opinions for items that are more relevant for their experience. As for performance, the analysis employs the ratio of the number of positive reviews towards the sum of positive and negative comments, for a given service attribute. According to this logic a hotel for which the proportion of positive comments is higher than the negatives corresponds to a positive performance. This proxy measurement for performance therefore varies between 0 (when all comments are negative) and 1 (when all comments are positive). Also, the traditional IPA usually employs a central tendency measure (e.g. mean, median) to split each axis and identify the four quadrants. In the current study the value of the mean is employed to split the plot area.
The interpretation of the IPA graph offers a number of interesting insights. Overall, for each hotel unit, the three service attributes considered in the analysis are closely positioned next to each other. This suggests that when hotel customers are pleased with a hotel, or with the particular performance of one service attribute and they engage in offering positive comments, they tend to be positive about the remaining attributes. Whereas there’s some natural dispersion in the points exhibited in Figure 2 most service attributes, for the diverse hotels, is positioned in the quadrants II and IV pointing towards urgent action and resource underutilization, respectively.
Overall the service attributes for the various hotel units are positioned very closely in the IPA map. A look at the positioning of the service attributes (room, location and staff) the one with stronger consistency in customers’ opinions is staff, as in 90% of cases appears as the most important attribute. An opposed pattern is shown for the attribute room, for which customers seem to hold more heterogeneous opinions about its importance. Overall the data suggests some inconsistency in customers’ perceptions about the importance of the service attributes. Of particular interest is the observation that there is a great variability in what regards the number of positive or negative comments. Most of the hotels exhibit a value for the performance measure (i.e. positive comments divided by the sum of positive and negative comments) not very distant from 0.5, therefore suggesting the existence of some level of service inconsistency across customers, a characteristic that is rather undesirable in service settings. The proposed analysis is susceptible of being conducted at a more fine grained level, i.e. in this case, for each hotel (see for example Figure 3).
Modified IPA displaying in detail the positioning of the three salient attributes [room, location and staff] for a single hotel unit (Hotel Afonso V).
This study, although exploratory and restricted to a small sample of service providers, from a specific service context—hotels—offers an illustrative insight of how existing managerial analytical tools can be adapted to help making sense of large volume of customer generated content. Whereas the study was applied in the context of hotel services, it is clear that the principles of the tool are applicable to any service industry, given that there is some kind of customer content to work with. Customer reviews are proliferating across service websites, platforms and social media contexts, therefore providing an ample and rich field for the development of new approaches to develop knowledge about service quality. The study illustrates that is possible to apply tools to offer a concise and structured view of the content generated by customers in their service reviews, and therefore to extract value from this abundant source of information. The extracted service attributes (room, location and staff) are particular to this study, its context and the limitations of sample selection, not meaning that they are the overall more important in the hotel industry. In order to do so, the study would have to be extended to a wider sample, and account for any conditioning variables (e.g. seasonality, weather, customer experience, etc.). As such this work suggested that there is a vast array of models and tools for assessing service quality that can be called to help make sense of the overwhelming volume of eWOM.
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