Understanding homophily of service failure within the hotel guest cycle: Applying NLP-aspect-based sentiment analysis to the hospitality industry

Online complaints have become increasingly influential on the purchasing behavior of customers in recent years. In an effort analyze large quantities of textual complaints and detail the various aspects of them, Aspect-Based Sentiment Analysis was looked to as an ideal framework to take on the task. This study set out to synthesize specific service failure items and categorize them into the groupings related to the hotel guest cycle and the corresponding operations, then compare the patterns of expression used by Asian and Non-Asian guests as the related their hotel experiences. A total of 390,236 online complaint terms posted about 353 hotels in the UK by hotel guests from 63 nations were manually derived from TripAdvisor for analysis. With consideration given to the homophily theory, we posited that Asian and non-Asian guests would exhibit similarities and differences with respect to the service failures they encountered when presented with various items of service. The results confirmed this as Asian guests were shown to encounter more service failures with respect to the engineering segment of operations (e.g. hotel room equipment issues), while non-Asian guests encountered more service failures on the housekeeping end of operations (e.g. toilets, public areas, cleanliness, and bedding). By organizing the failures according the four stages of the guest cycle, it was observed that approximately 80% of the service failures occurred during the occupancy period. This study contributes to the existing literature on hotel guest satisfaction both with respect to the methodology it uses and the new findings it presents on differences in perceptions of service failures members among different cultures.     

A comparison of the dominant meta programme patterns in accounting undergraduate students and accounting lecturers at a UK business school

Meta programmes are a means of describing the behavioural traits that a person exhibits when interacting with other people. An understanding of meta programmes can improve communication between individuals and this may have implications for teaching. The purposes of this study are first to identify the dominant meta programme patterns of first year accounting undergraduates at a UK business school. An earlier pilot study validated use of the Motivation Profile Questionnaire (MPQ) to elicit the dominant meta programmes of accounting lecturers at the same Business School (Brown, 2002). Secondly, the students' meta programmes are compared with those of their accounting teachers to identify whether there are any differences or similarities between the two groups. The matching of the meta programmes of the teachers and students would enhance communication whilst major differences in meta programmes would make communication more difficult. A sample of 62 first year accounting undergraduates and 20 accountancy teachers completed the MPQ. The results indicate that, on average, the accounting students have similar dominant meta programme patterns to their accounting teachers. The implications of the findings for improving communication and therefore teaching are discussed, along with the scope for further research.     

简快身心积极疗法的理论基础及其逻辑关系之剖析

简快身心积极疗法在发展过程中,不拘泥于学术学派的束缚,系统整合了当前国内外各种实用有效的治疗技术,因其简洁快速、实用有效的临床辅导效果而独树一帜。本文尝试系统梳理简快身心积极疗法的理论基础,挖掘其内在逻辑关系,剖析其简快有效的原因所在。     

Listening to the voice of the guest: A framework to improve decision-making processes with text data

The amount of texts available on the web is growing continuously and making sense of this unstructured data efficiently and effectively, therefore, poses a demanding challenge for organizations. Although computer science community has developed many techniques, there is ample room for improvement on organizational utilization of such text data, especially when referring to decision-making support. In this article, we propose and validate a framework towards an effective use of text data inside hotel industry, bringing tourism sector to this discussion. We combined three text mining techniques for text classification, sentiment analysis and topic modeling in a novelty way to allows managers to analyze guests’ comments and compares competitors in hospitality industry based on SERVQUAL. Our objective is to present an automatized process involving text data collection and analysis, improving decision-making process.     

Neuroeconomics and business psychology

To determine parameters of the frontal power of executive integration for application in business, this paper reviewed neuroeconomic neuroimaging research and discussion in relation to business psychology. The results are that limbic system （L） is a centre of primary consciousness based on a mesolimbic dopamine system serving the client in the brain stem with adaptive feedback as well as generating cognition and emotions towards Neocortex in a reciprocal autonomic balance. The power of concentration （C） is a tripartite executive integrating emotions and cognition： Prefrontal analysis by semantic recollection from temporal （R） lobe is based on episodic memories. Volition in the medial prefrontal cortex （c） controls both cognitive prediction （R＇c） and emotions （L/c） for a balanced integration as a neural root of economic reasoning. An intuitive visuospatial Parietal sketchpad （I） integrates hippocampal episodic memory mismatches complementary to the cognitive prediction function. Chronic stress limiting the capacity of C is indicated by baseline serum cortisol. The conclusion is that the neuroeconomic model enables （1） operation of the theorem of economic man as an economic-bio-educational complex. Other business applications comprise, （2） a neural foundation of transactional analysis （TA） to improve corporate collaboration and management, （3） a combined health promotion/human resource development program based on simple training techniques as physical exercise, medical meditation and neurolinguistic programming （NLP）, i.e., for weight regulation.     

In search of meaning: Lessons,resources and next steps for computational analysis of financial discourse

We critically assess mainstream accounting and finance research applying methods from computational linguistics (CL) to study financial discourse. We also review common themes and innovations in the literature and assess the incremental contributions of studies applying CL methods over manual content analysis. Key conclusions emerging from our analysis are: (a) accounting and finance research is behind the curve in terms of CL methods generally and word sense disambiguation in particular; (b) implementation issues mean the proposed benefits of CL are often less pronounced than proponents suggest; (c) structural issues limit practical relevance; and (d) CL methods and high quality manual analysis represent complementary approaches to analyzing financial discourse. We describe four CL tools that have yet to gain traction in mainstream AF research but which we believe offer promising ways to enhance the study of meaning in financial discourse. The four tools are named entity recognition (NER), summarization, semantics and corpus linguistics.     

Meta programme patterns in accounting educators at a UK business school

The purposes of this study are to compare the results of two alternative methods of eliciting meta programmes, the Motivation Profile Questionnaire (MPQ) and the Language and Behaviour (LAB) Profile semistructured interview, and to identify whether accounting educators exhibit any dominant meta programmes. An individual trained to use the LAB Profile interviewed a sample of 14 accounting educators who then completed the MPQ. The results of the MPQ and the LAB Profile identified three common patterns, indicating a good degree of correlation between the two methods. Identification of the key meta programmes of the accounting educators may have benefits in their teaching and is the precursor to a larger study of the meta programmes of accounting undergraduates, which can now be undertaken in a cost effective way using the MPQ.     

Ranking professional forecasters by the predictive power of their narratives

This article presents the first ever ranking of professional forecasters based on the predictive power of the narrative of their regular research reports. The ranking is generated by applying the fully automated four-step procedure – called NLP-ForRank – developed in this article. The four steps are data scraping from the internet; data preparation; application of the natural language processing (NLP) models; and evaluation of the predictive power of the NLP indexes with linear regression, Granger causality, vector autoregression (VAR), and random forest forecasting models. Applying this procedure to five large Polish banks and to many time series shows that including the constructed NLP indexes in the forecasting models lowers the forecast errors, and that the optimal model almost always contains the NLP index. The financial news agencies could consider publishing this type of ranking on a regular basis as it would foster accountability, transparency, and a more competitive environment in the professional forecasting industry.     

User generated content for exploring factors affecting intention to use travel and food delivery services

Customer reviews/comments on product-websites and on social-media pages can serve as great information sources for both customers and service-providers. For exploring the drivers of usage intention in context of Online-Food-Delivery services (OFDs) and Online-Travel-Agency services (OTAs), traditional-based (qualitative or quantitative or mixed-method) approaches may not be enough. This study utilizes a multi-method approach comprising of both traditional and Natural-Language-Processing (NLP)-based approaches. This study has captured the emic-perspectives using qualitative semi-structured-interviews and etic-perspectives using NLP-based analysis of extant literature. The conceptual model developed from the model of online-decision-making stance, was tested quantitatively using survey data and by NLP-based approach using online user reviews. The path-model was tested using Structural-Equation-Modeling (SEM). Results of this study reveal that price benefits and trust-in-service are major predictors of customer’s usage intention in OFD and OTA contexts. The study concludes with the various implications, limitations and future directions.     

基于大学生就业恐惧症的NLP简快心理疗法探究

本文在探讨就业恐惧症的形成、表现特征以及危害的基础上,借鉴美国学者理查德·班德勒和约翰·格林德创立发展而成的NLP简快心理疗法理论,对NLP基本特点与优势,以及该疗法基于就业恐惧症治疗的具体实施内容、技巧和操作方法,以及要注意的问题等,进行了系统的讨论,旨在造福于大学生就业恐惧症患者群体,造福于高校,造福于社会。