Actor value formation in Airbnb: insight from multi-source data

Social media and review websites such as Trip Advisor are emerging as important platforms for restaurant reviews. The tendency of consumers to seek out electronic word of mouth before deciding where to dine has increased rapidly, with online content being shown to significantly impact purchasing decisions. Practitioners have indicated they are keenly aware of the importance of online reviews, but there is almost no research that looks at this phenomenon in the New Zealand context, and no research that compares traditional, print-based reviews with online content. In order to address this gap, a recent Auckland University of Technology master’s thesis applied content analysis to compare online and published restaurant reviews of restaurants in Auckland, New Zealand. Three hundred reviews from TripAdvisor website, Cuisine Magazine and the New Zealand Herald newspaper were analysed, and some results are presented here.
 Traditional print reviews (Cuisine and the Herald) tend towards a more ‘specialist’ approach, including detailed information about the chefs, the owners and the restaurants’ histories. They also use more ‘fancy’ language in their food descriptions, including very detailed menu ingredients. TripAdvisor reviews, by contrast, tend towards non-specialist, ‘plain language’ reviews, with simple menu descriptor words and little attention on ingredients. When discussing price, print reviews take an ‘objective’ stance, listing the price but rarely making a personal judgement about value; whereas the online reviews feature prominent personal judgements about value for money. In addition, online reviews emphasise the social aspects of dining (who they are dining with, the social nature of the event, e.g. birthday, interactions throughout the meal), often spending as much time discussing their companions as the products and service involved in the experience. By contrast, print reviews tend to focus more on the ‘physical’ aspects of dining (the wine, the food, the decor). Finally, both platforms strongly emphasise food and service as the main criteria for judgement, accounting for almost half the word counts in both styles of reviews.
 What can the practitioner take from this research? Firstly, the fact that food and service are the predominant criteria for both online and professional reviewers serves as a reminder for restaurant operators that, no matter how exquisite or stylish the restaurant is, well-cooked food and attentive service are significantly emphasised as the primary criteria by reviewers. Moreover, both review formats stress that the reliability of the booking system and efficiency of the service staff tended to enhance all reviewers’ satisfaction.
 However, there are clear differences in the review styles that represent the different audiences they are addressing. Each format attempts to recognise the perceived social identity of their audience, with the print reviews taking the ‘insider expert’ voice and appearing to speak to a more sophisticated upmarket, product-focussed audience. The print reviews also assume their readers are less sensitive to price, rarely discussing the perceived value of the meal. By contrast, the online reviews are more ‘plain language’, discuss value directly and are socially driven. By being aware of these differences in reviewing approaches, restaurant operators’ can finesse their marketing strategies. By reading and reflecting on the link between the contrasting review styles and the social identity of the respective readers, practitioners can consider how their offering ‘fits’ with their target markets. Finally, as online review platforms become increasingly important, practitioners should engage with the content they find there, ensuring they take time for reading, reflecting and responding.
 If you would like to read the original thesis this article is based on, please email: david.williamson@aut.ac.nz
 Corresponding author
 Ziye is an emerging researcher in the field of hospitality management. She received her bachelor’s degree from Beijing Union University in 2015 and her master’s degree from Auckland University of Technology in 2017, majoring in international hospitality management. Her research focusses on user-generated content in restaurant reviews, a relatively new data source for analysis in this area. Ziye also researches electronic word-of-mouth, online restaurant reviews and writers’ criteria for restaurant measurement.
 Ziye Zhang can be contacted at: ziye0927@outlook.com

Perceptions and Experiences of Vaping Among Youth and Young Adult E-Cigarette Users: Considering Age, Gender, and Tobacco Use

This study was conducted to understand customer experience and satisfaction through airline passengers’ online review. To achieve the purpose of this study, the semantic network analysis was conducted qualitatively by collecting reviews in top 10 airlines selected by Skytrax (airlinequality.com). In addition, this study quantitatively identified the relationship among six evaluation factors (seat comfort, staff, food and beverage (F&B), entertainment, ground service, and value for money), customer satisfaction and recommendation. This study collected 9632 reviews from the Skytrax. Through a CONCOR (CONvergence of iterated CORrelation) analysis, keywords were grouped into six clusters (seat comfort, staff, entertainment, ground service, value for money, and airline brand). Through the linear regression analysis, all evaluation factors except ‘entertainment’ factor significantly had impact on customer satisfaction and recommendation. These results showed that understanding online review can provide both academic implication and practical implication to develop sustainable strategy in the airline industry.

PurposeWith the growth of social media and online communications, consumers are becoming more informed about hotels' services than ever before. They are writing online review to share their experiences, as well as reading online review before making a hotel reservation. Hotel customers considered it as reliable source and it influences customers' hotel selection. Most of these reviews reside in unstructured format, scattered across in the Internet and inherently unorganized. The purpose of this study was to use predictive text analytics to identify sentiment drivers from unstructured online reviews.Design/methodology/approachThe research used sentiment classifications to analyze customers' reviews on hotels from TripAdvisor. In total, 9,286 written reviews by hotel customers were scrapped from 442 hotels in Malaysia. A detailed text analytic was conducted and was followed by a development of a theoretical framework based on the hybrid approach. AMOS was used to analyze the relationship between customer sentiments and overall review rating.FindingsWith the use of Structural Equation Modeling (SEM) and clustering technique, a list of sentiment drivers was detected, i.e. location, room, service, sleep, value for money and cleanliness. Among these variables, service quality and room facilities emerged as the most influential factors. Sentiment drivers obtained in this study provided the insights to hotel operators to improve the hotel conditions.Research limitations/implicationsAlthough this study extended the existing literature on sentiment analysis by providing valuable insights to hoteliers, it is not without its limitations. For instance, online hotel reviews collected for this study were limited to one specific online review platform. Despite the large sample size to support and justify the findings, the generalizability power was restricted. Thus, future research should also consider and expand to other type of online review channels. Therefore, a need to examine these data reside various social media applications, i.e. Facebook, Instagram and YouTube.Practical implicationsThis study highlights the significance of hybrid predictive model in analyzing the unstructured hotel reviews. Based on the hybrid predictive model we developed, six sentiment drivers emerged from the data analysis, i.e. location, service quality, value for money, sleep quality, room design and cleanliness. This consideration is critical due to the ever-increasing unstructured data resides in the online space. This explores the possibility of applying data analytic technique in a more efficient manner to obtain customer insights for hotel managerial consideration.Originality/valueThis study analyzed customer sentiments toward the hotel in Malaysia with the use of predictive text analytics technique. The main contribution was the list of sentiment drivers and the insights needed to improve the hotel conditions in Malaysia. In addition, the findings demonstrated motivating findings from different methodological perspective and provided hoteliers with the recommendation for improved review ratings.

How do consumers in the sharing economy value sharing? Evidence from online reviews

Four attitudinal components of customer loyalty were synthesised from the services literature and combined to produce a loyalty conceptualisation that excludes repurchase behaviour. This proposed conceptualisation of service loyalty was then modelled in two quantitative studies to determine the effects of potential predictors. The influence of consumers’ evaluative judgements was compared against the effects of relational outcomes. The three evaluative judgement measures were service encounter satisfaction, perceived core service quality and value for money while relational measures comprised social comfort, social regard and friendship. It was found that while personal friendship between customer and service employee was significantly associated with loyalty, service encounter satisfaction was the major predictor. It was also found that the relational factors of social comfort and social regard played indirect roles through their influence on customer’s evaluation of satisfaction and quality. Conversely, friendship was not related to the mediating variables of service encounter satisfaction and perceived core service quality.

PurposeThe paper aims to define and measure value for money (VFM) within the concept of private finance initiative (PFI), and investigate the principal factors in which opinions are formed.Design/methodology/approachLiterature review of texts, published papers, and reports are used to identify relevant parameters to the research. The sources support the arguments of opinion within the paper.FindingsPFI is still perceived by the government as the most cost effect means of procuring public infrastructure. The positive aspects of PFI are the competition generated by the concept, and improved risk management. Negative aspects include the lack of agreed formulae by all stakeholders by which to benchmark VFM, and an increasing sceptical electorate to the PFI concept of providing short and long term VFM.Research limitations/implicationsBy virtue of PFI being a dynamic, changing, and complex means of procurement, this research will be valid in its own right. However more up to date government policies must be consulted to take the determination of VFM in any further research.Practical implicationsThe research and conclusions will provide add to the current debate as to the viability of PFI, with VFM the main key point as to the ongoing success of the governments strategy this method of procurement.Originality/valueThe paper adds, to the “VFM” drivers that have been identified by identifying principle factors in creating VFM. This will be a sound basis for the justification of VFM in PFI.

This research is motivated by the development of technology in the field of information and communication which has an impact on the emergence of new innovations in terms of electronic payments. Non-cash money or electronic money (e-money) is a payment instrument that fulfills the elements, namely issued on the basis of the value of money deposited in advance by the holder to the issuer, the value of money is stored electronically in a medium such as a server or chip, used as a means of payment to merchants who are not the issuer of the electronic money and the value of electronic money deposited by the holder and managed by the issuer is not a deposit as referred to in the laws governing banking.The benefits and convenience offered by electronic money can influence the increase in users. When a product has benefits and convenience when used in everyday life, it is likely that the product will be used by the wider community. This study aims to explain the factors that influence trust and its consequences on continuous usage intention of e-money in Denpasar City in terms of perceived benefits, perceived convenience and perceived risk. Trust here acts as a mediating variable. The research sample was 100 people in Denpasar city. The research method used is quantitative method with PLS-based structural equation model analysis or SEM. This research shows that perceived benefits and perceived ease of use influence respondents confidence in using e-money continuously, while perceived risk does not show any influence on respondents confidence in their intention to use e-money continuously. Furthermore perceived benefits and perceived ese of use hav positive effect on the intention to continue using e-money, while perceived risk has no effect on the intention to use e-money continuously.

Kano analysis and importance-performance analysis (IPA) are widely used for needs analysis, product positioning, and strategic planning in product design. Previous research uses customer surveys and online reviews as the main data sources. However, these data carry inevitable subjective bias. In contrast, product maintenance records provide objective information on product quality issues and failure patterns, which can be cross-validated with customers’ personal experience from online reviews. In this paper, we propose a systematic approach for conducting Kano-IPA analysis from online reviews and product maintenance records synthetically. An attribute-keyword dictionary is first established using keyword extraction and clustering methods from online reviews and maintenance records. After that, semantic groups including product attributes and associated descriptions are extracted by dependency parsing analysis. The sentiment scores of identified attributes are calculated by a self-supervised representation learning approach (Sentiment Knowledge Enhanced Pre-training, SKEP) from the built semantic groups. Sentiment scores and occurrence frequencies of attributes in online reviews are utilized for Kano analysis. The importance of product attributes in IPA is estimated from the impact of sentiments of each product attribute on product ratings, while the performance is estimated from the sentiment scores of online reviews or the quality statistics from maintenance records. A case study of passenger vehicles shows that integrated data can provide more comprehensive results and richer insights. The proposed approach enables automatic data processing and can support companies to make efficient design decisions with broader perspectives from multi-source data.

Evidence that consumers in emerging economies are more tolerant of ineffective customer service (CS), instigated an investigation into controllable elements of the service offering in a specific context in South Africa, namely, appliances sales departments in retail stores. The research aimed to identify possible shortcomings in CS amidst evidence that consumers are exposed to sophisticated merchandise that they have limited experience and understanding of. The intention was to suggest initiatives to augment the service offering so that it becomes more conducive for informed, responsible buying decisions. Household appliances represent a category of complex, durable and expensive merchandise that require more extensive information search before concluding buying decisions.A survey was done in 2007 through a pre‐tested structured questionnaire. Several branches of five prominent department stores were involved through liaison with industry. A store intercept method was used to recruit respondents: 296 questionnaires were filled in on the spot under supervision. Three sections of the questionnaire are relevant for this report: (1) consumers' satisfaction with CS; (2) a product knowledge test; and (3) demographic information.Factor analysis revealed a reduction of the original five elements of CS in the scale to three distinct elements that were labelled Personnel, Processes and Value for Money, and Product Presentation. The simpler scale suggests a less intricate judgment of CS in the context of this research. Means indicated that consumers were generally satisfied with all elements of CS, i.e. the service offering coincided with their expectations. Analysis of variance indicated no significant differences in the interpretation of any of the elements of CS by gender. A significant inverse relationship between satisfaction with CS and years of experience occurred for respondents with more than 25 years of experience in terms of Personnel (Element 1) and Processes and Value for Money (Element 2).Findings of the product knowledge tests were meant to verify consumers' CS judgments. However, scores were disappointingly low for all appliances across all respondent categories. Consumers' product knowledge could therefore not have supported informed buying decisions, despite prior experience and the opportunity to acquire additional product information during the in‐store encounter. Consumers' positive CS judgments suggest that they not necessarily realize their lack of crucial product knowledge. In the interest of informed and responsible buying decisions that have consequences for proper use and maintenance of appliances in the long term, retail stores that serve a broad customer base are encouraged to attend to in‐store customer assistance during the pre‐purchase phase, notwithstanding positive CS judgments. Non‐formal consumer education by competent, well‐trained salespeople is recommended to encourage evaluative rational product judgments. It is also suggested that store displays are designed to encourage consumers to be more inquisitive during store visits.

Quality of patient-provider communication regarding tobacco use may encourage cessation that could lead to improved health outcomes for mothers and children. However, currently there are no validated measures of frequency and quality of patient-provider communication about cigarettes and e-cigarettes. The objective of this study was to adapt and validate measures of frequency and quality of patient-provider communication about smoking and e-cigarette use among a sample of pregnant mothers who currently smoked. An online sample of US pregnant women who reported past 30-day smoking were recruited to complete a cross-sectional, online survey (n=267). An exploratory factor analysis examined the factor structure of four measures of frequency and quality of patient-provider communication about cigarettes and e-cigarettes among those who reported prior communication with their provider about cigarettes and e-cigarettes (n=170). Relationships between measures were explored, and a logistic regression explored each measure's association with intention to switch from cigarettes to e-cigarettes. Items measuring the frequency of communication loaded onto one factor for both cigarettes and e-cigarettes (α=0.88). Quality of communication loaded onto two factors for both cigarettes and e-cigarettes, termed active communication and internalized perception. Internalized perceptions of communication quality about cigarettes (β= -0.32, p<0.002), active communication (β=0.46, p<0.02), and internalized perceptions of communication about e-cigarettes (β= -0.36, p<0.001) were related to intention to switch, in separated models. Quality conversations between healthcare providers and pregnant patients is likely more important for behavioral decision-making than the frequency of communication.

Importance-performance analysis (IPA) is widely used for needs analysis, product positioning, and strategic planning in product design. Previous research on IPA often employs single-source data such as customer surveys or online reviews with unavoidable subjective bias. In contrast, product maintenance records provide objective information on product quality and failure patterns, which can be cross-validated with customers’ personal experiences from surveys or online reviews. In this paper, we propose an integrated framework for conducting IPA from online reviews and product maintenance records jointly. An attribute-keyword dictionary is first established using keyword extraction and clustering methods. Then, semantic groups, including product attributes and associated descriptions, are extracted using dependency parsing analysis. The sentiment scores of identified product attributes are determined by a voting mechanism using two pre-trained sentiment analysis models. The importance of product attributes in IPA is estimated from the impact of sentiments of each product attribute on product ratings with the extreme gradient boosting (XGBoost) model, while the performance is estimated from the sentiment scores of online reviews or the quality statistics from product maintenance records. In addition, we propose two methods to validate the IPA results, in which the IPA results are compared with the actual product improvements on the market or compared with the analysis of customer reviews from different time periods, respectively. The validated IPA results from online reviews and maintenance records are then integrated to obtain a more comprehensive understanding of customer needs. A case study of passenger vehicles is used to demonstrate the framework. The proposed framework enables automatic data processing and can support companies in making efficient design decisions with more comprehensive perspectives from multisource data.

Use of tele-nursing in primary care: A qualitative study on its negative and positive aspects

This contribution aims to expand the study of experiences at work by (a) analyzing a theoretical perspective concerning experiences at work which emphasizes both positive aspects as well as negative aspects, (b) exploring the relation of both negative (Bullshit job perceptions; BJP) and positive aspects (Meaningful Work perceptions; MWP) experienced at work to negative work-related behavior (Counterproductive Work Behavior [CWB] and Cyberloafing), (c) investigating the (moderating) role of work ethic, and (d) examining the robustness of these relations when considering additional contextual factors (organizational work values and tightness–looseness reflecting social norms). Three studies were conducted, including two samples of German employees (N = 247 and N = 240), and another one of employees in the USA (N = 253). Our findings reveal that negative experiences at work (BJP) are the main predictor of problematic workplace behavior (CWB and Cyberloafing). Furthermore, their relation was contingent on individuals’ endorsement of work ethic. BJP and CWB (or Cyberloafing) were more closely associated for individuals strongly endorsing work ethic. In contrast, the relation of positive experiences (MWP) to problematic behavior at work was not significantly qualified by work ethic. The observed relations were robust when additional contextual factors were controlled for. The results emphasize the importance and complexity of work experiences including and differentiating positive and negative aspects. They also highlight the significance of work ethic and related beliefs of employees in shaping problematic behavior in work settings.

GeoAI in terrain analysis: Enabling multi-source deep learning and data fusion for natural feature detection