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While the links between customer word-of-mouth and desirable organizational outcomes have been widely studied, the possibility that customers might routinely exaggerate their consumption experience stories has been neglected. The paper aims to discuss this issue.

The first exploratory study examined exaggerated and unexaggerated word-of-mouth and the targets of such activities. The second exploratory study focussed on customer-exaggerated negative word-of-mouth and its drivers. The two experimental studies generated deeper insights into attributions of service failure and exaggerated negative word-of-mouth.

This research explicitly addresses customer exaggeration regarding service consumption and the reasons customers engaged in such behaviors. Study 1 focussed on the scope and targets of exaggerated word-of-mouth, and Study 2 concentrated on identifying the drivers of exaggerated negative word-of-mouth. Studies 3 and 4 experimentally elucidated the cognitive mechanisms leading to exaggeration.

Contributions include deeper understanding of the phenomenon of exaggerated negative word-of-mouth and developing and testing a model of the factors associated with consumers’ exaggerated negative word-of-mouth.

Implications include possible organizational and public policy actions to prevent Pinocchio customers from exaggerated negative word-of-mouth.

This paper explores the nature and scope of exaggerated customer word-of-mouth and contributes insights in four ways. First, this research explores the scope of consumer exaggeration during word-of-mouth storytelling and the intended targets of such communications. Second, this research focusses on exaggerated negative word-of-mouth and develops a conceptual model of the drivers of such activity. Third, the theory is tested and contributes empirical insights into exaggerated negative word-of-mouth. Fourth, through experiments, insights are gained into the cognitive mechanisms leading to exaggeration and the effects of attribution differences in personal vs service provider blame.

The purpose of this study was to investigate the effects of word-related factors (i.e. frequency, range, dispersion and cognateness) on first-language English (L1E) readers' (n = 20) and second-language English (L2E) readers' (n = 20) incidental acquisition of vocabulary through the reading of an authentic novel.

Participants read A Clockwork Orange by Anthony Burgess, a 58,686 token (word) English language novel containing Slovos, that is, words from Nadsat, a futuristic, foreignized teen talk invented by Burgess. Upon finishing the novel, the participants took two unexpected vocabulary tests, one for meaning recognition and the other for meaning recall.

The results of this study indicate that word-related factors significantly correlate with the word meaning recall test scores of both groups. However, the regression models of meaning recall for the two groups showed that dispersion was the most robust predictor, which implies that the participants recalled more word meanings when the novel had a more even distribution of the unknown target words. The meaning recognition test scores showed cognates were a significant predictor for the L1E readers but not for L2E readers.

This study marks the first attempt in the field to investigate the relative contribution of frequency, range and dispersion – a closely bound set of word-related factors – to both L1E and L2E readers' incidental acquisition of vocabulary through reading an authentic novel. Considering the important role of dispersion, the current study suggests that developers of graded readers and children's literature should more evenly distribute unknown target words in their books. Doing so will better facilitate both L1E and L2E readers' acquisition of those words. The study also addresses a fallacy of methodology regarding incidental vocabulary acquisition by examining the effect of the cognateness of the foreignized words embedded in A Clockwork Orange. The L1E readers' sensitivity to cognates implies that cognate-word awareness-raising activities are necessary to learning a foreign language, especially if that language has many cognates in common with English, such as Spanish.

Increasing reading achievement has become a nationwide priority resulting from the Elementary and Secondary Education Act of 2005 (Dole, 2004). Due to this emphasis, coupled with the fact that an elementary school’s success is generally not correlated with test scores in social studies, teachers of the elementary grades find limited time to teach the social studies curriculum. However, in effort to combat this tragedy, elementary educators should be taught and encouraged to integrate content area teaching with literacy strategies. Using the appropriate.

This paper illuminates the distinction between individual and organizational actors in business-to-business markets as well as the coexistence of formal and informal mechanisms of coordination in multinational corporations. The main questions addressed include the following. (1) What factors influence the occurrence of personal contacts of foreign subsidiary managers in industrial multinational corporations? (2) How such personal contacts enable coordination in industrial markets and within multinational firms? The theoretical context of the paper is based on: (1) the interaction approach to industrial markets, (2) the network approach to industrial markets, and (3) the process approach to multinational management. The unit of analysis is the foreign subsidiary manager as the focal actor of a contact network. The paper is empirically focused on Portuguese sales subsidiaries of Finnish multinational corporations, which are managed by either a parent country national (Finnish), a host country national (Portuguese) or a third country national. The paper suggests eight scenarios of individual dependence and uncertainty, which are determined by individual, organizational, and/or market factors. Such scenarios are, in turn, thought to require personal contacts with specific functions. The paper suggests eight interpersonal roles of foreign subsidiary managers, by which the functions of their personal contacts enable inter-firm coordination in industrial markets. In addition, the paper suggests eight propositions on how the functions of their personal contacts enable centralization, formalization, socialization and horizontal communication in multinational corporations.

This study aims to investigate the content of hotel brands’ mission statements (MSs) and their relationship with selected attributes of hotel brands.

Content analysis of hotel brands’ MSs was used to detect the MSs’ key words, which were further processed by methods of social network analysis, complemented by clustering techniques and correspondence analysis on the generalized aggregated lexical tables, a special type of correspondence analysis.

Hotel brands operating in luxurious markets more often emphasize experiences than those in midscale markets. Furthermore, hotel brands with longer traditions and those with a large number of controlled rooms communicate words in their MSs that represent a rather traditional approach to hospitality. Younger hotel brands with fewer controlled rooms chose words that indicate a more commercially oriented approach. Finally, cluster analysis revealed four dimensions of hotel brands’ MSs, instead of the nine most typically used in mission statement component models.

Understanding the frequencies and networks of keywords, and their relationship with hotel brand attributes, will help create more focussed MSs. This will strengthen hotel brands, raise their revenues and subsequently increase company performance.

The analysis provides valuable insight into MSs in the specific tourism context of hotel brands. The authors have achieved this with the use of a wide range of advanced network analytic methods. These insights can guide hotel brands to better position themselves in the competitive tourism accommodation market.

This paper aims to map the evolution of research in business ethics from 1991 to 2018. It aims to identify the major themes and how they have evolved. It also aims to identify gaps in the literature for recommending future research agenda.

This study uses co-word network analysis. Co-word network analysis is a bibliometric technique used to objectively identify research themes via article keywords. The study examines articles from 1991 to 2018, which is a span encompassing a greater number of articles than previous bibliometric studies in business ethics. This time span was split into four periods and major research themes were identified for each period to map the changes in research agendas in the business ethics discipline over time.

The findings point to increasing maturation of the discipline, a slight decline in ethical decision-making research, a rise in research at the intersection of leadership and ethics and exponential growth in studies on corporate social responsibility. Ethical issues in business-to-business contexts are understudied. Research in environmental disclosures and leadership is expected to grow in the future.

This is the first study in business ethics to use keywords for analyzing the evolution of a discipline. This study encompasses more articles than any other study in business ethics. Finally, this is the only study to use co-word network analysis to study business ethics literature.

One of the chief purposes of bibliometric analysis is to reveal the intellectual structure of a knowledge domain. Yet due to the magnitude and the heterogeneous nature of bibliometric networks, some sorts of filtering procedures are often required to make the resulting network interpretable. A co-word analysis of more than 135,000 scholarly publications on Buddhism was conducted to compare the intellectual structure of Buddhist studies in three language communities, Chinese, English and Japanese, over two periods (1957–1986 and 1987–2016). Six co-word similarity networks were created so social network analysis-based community-detection algorithm can be identified to compare major research themes in different languages and eras. The paper aims to discuss this issue.

A series of filtering procedures was performed to exclude less discriminatory keywords and spurious relationships of a large, cross-language co-word network in Buddhist studies. Chief among the filtering heuristics was a percolation-transition based method to determine the similarity threshold that involves observing the relative decrease of nodes in the giant component with the increasing similarity threshold.

It was found that the topical patterns in the Chinese and Japanese scholarship of Buddhism are alike and observably distinct from that of the English scholarship. Furthermore, a far more drastic changes of research themes were observed in the English literature relative to the Chinese and Japanese literature.

The filtering procedures were shown to greatly enhance the modularity values and limited the number of modularity classes; thus, domain expert interpretation is feasible.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

This chapter presents “what we know” about the application of technology to instruction for students with learning and behavioral disabilities. Information is presented on research-based effective practices in technological interventions for teaching specific academic skills, delivering content at the secondary level and using technology as a tool for assessment. The chapter concludes with a discussion on Universal Design for Learning and the promises this paradigm holds for educating not only students with special needs, but all learners. The chapter begins where parents and teachers typically begin: the consideration of technology.