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“Prosumers” (combining “producer” and “consumers”) describes consumers’ ability to openly share their product/service experiences and thereby drive sales and digital marketing. Understanding what motivates active prosumers to engage in electronic word-of-mouth (eWOM) and share or review their hotel experiences online can help organizations empathize with consumers and use their messages to co-create value. Identifying prosumers’ motivators can enable companies to properly target them as resources for review or consumer feedback studies. This paper aims to investigate the influence of motivators (intrinsic and extrinsic), service quality and age on consumers’ eWOM communication behaviors.

A panel of 204 travelers was surveyed regarding their hotel travel experiences, propensity to write online reviews, preferred review-writing platform, motivations for writing reviews and impressions of service quality. To test the hypotheses, a multivariate regression analysis was performed with eWOM as the dependent variable. Differences in eWOM as a function of preferred review platform were also tested using ANOVA, with a multiple comparison analysis that underlines the differences between prosumers who prefer different types of review platforms and their eWOM behaviors.

Both intrinsic and extrinsic motivators, as well as service reliability, had a significant influence on eWOM behavior, while service tangibility had a negative relationship. Additionally, prosumers’ engagement in eWOM about their hospitality experience differed according to their preferred review platform.

The findings of the analysis underline the importance of consumer motivations and of satisfaction with service quality in the context of digital review behavior. For marketing and hospitality research, this shows the benefits of including not only individual characteristics and demographics when analyzing review behavior but also elements such as perceptions of service quality. Given the differences in how the dimensions of service quality affect consumers’ engagement in online review behavior, this represents a very important topic for research and can be included in future studies that analyze the consumer review behavior model.

Regarding the implications for practitioners, this study highlights the important role played by consumer satisfaction with service in the hospitality industry and its effect on their involvement in online reviews. Managers should be focused constantly on offering great service to their guests, while, at the same time, offering them motivations to engage in posting positive reviews about their vacation. Moreover, as the results of this study imply that various dimensions of service quality have a different impact, managers should focus especially on the aspects that consumers consider important and constantly include in their reviews, such as the tangibles dimension. The results of this study also have the potential to provide to businesses more information to improve the social aspects of vacationing, which can not only improve perceptions about service quality but can also have a positive influence on consumers’ motivations.

This paper develops a better understanding of what motivates people to engage in the eWOM communication behavior of writing online hotel reviews, by showing the effect of consumer motivations and service quality variables on prosumers’ engagement in online review behavior.

Increasingly, marketing managers are asked to consider the financial implications, in terms of both book and market values, when making strategic decisions. The purpose of this paper is to investigate the role of marketing expenditures in explaining the variation in the aftermarket performance of a sample of firms conducting initial public offerings (IPOs).

Theories from marketing and finance – market-based assets (MBA) theory and signaling theory respectively – serve as the conceptual basis of this paper. The results of this study, based on a sample of 2,103 IPOs covering the 1996 to 2008 time period, suggest that increased marketing spending positively impacts aftermarket (i.e. stock price) performance.

The authors find that while short-run aftermarket performance is positively and significantly impacted by pre-IPO marketing spending, long-run firm performance measures do not appear to be impacted by pre-IPO marketing spending. Further, pre-IPO marketing spending does not incrementally reduce underpricing or improve long-run performance when the IPO takes place during extreme market conditions such as recessions or hot markets, and these results are important to the shareholders and potential investors in the firm.

Theoretically this paper advances the literature on the marketing-finance interface by extending the MBA and signaling theories. For practice, the results indicate that spending more money on marketing before the IPO and disclosing this information produces positive bottom-line results for the firm.

While Luo (2008) documents a significant relationship between the firms’ pre-IPO marketing spending and IPO underpricing, few studies explore the impact of marketing spending on stock price performance beyond the first day of trading. This paper makes three unique contributions. First, the authors extend Luo’s study by investigating the effect of marketing expenditures on underpricing during extreme market conditions. Second, the authors are the first to examine IPO performance in the long-run as well as the short-run. Finally, the authors assess how long-run performance is impacted by marketing spending during extreme market conditions. The findings of this study has implications for managers and shareholders of firms considering going public through a traditional IPO.

This study aims to investigate the relationship between Airbnb and long-term residential rents, using Santa Monica, California, as a case study. In 2015, Santa Monica adopted the home sharing ordinance (HSO), a stringent regulation aimed at restricting short-term rentals (STR). This research examines the implications of this ordinance on the local housing market.

The synthetic control method (SCM) is applied to a panel data set comprising Airbnb listings and residential rents from multiple cities in Los Angeles County. This approach is used to estimate the causal effects of Santa Monica’s HSO on two outcomes: Airbnb listings and residential rents.

The empirical results show a 60% reduction in Airbnb listings in Santa Monica within two years of implementing the ordinance. Despite this significant decrease, the effect of the regulation on rents was not significant. Suggestive evidence indicates that the ordinance’s ineffectiveness in increasing the number of houses allocated to long-term tenants may have contributed to its negligible impact on rental rates.

To the best of the author’s knowledge, this research is the first to use the SCM for evaluating the impact of STR regulations. It offers crucial insights to policymakers on regulating platforms like Airbnb. The study reveals a scenario where a marked decrease in Airbnb activity did not lower residential rents, highlighting the need for context-specific evaluations in understanding the housing market’s dynamics. Additionally, these findings are valuable for investors considering the implications of regulatory changes in the STR sector.

THIS number will appear at the beginning of the Leeds Conference. Although there is no evidence that the attendance will surpass the record attendance registered at the Birmingham Conference, there is every reason to believe that the attendance at Leeds will be very large. The year is one of importance in the history of the city, for it has marked the 300th anniversary of its charter. We hope that some of the festival spirit will survive into the week of the Conference. As a contributor has suggested on another page, we hope that all librarians who attend will do so with the determination to make the Conference one of the friendliest possible character. It has occasionally been pointed out that as the Association grows older it is liable to become more stilted and formal; that institutions and people become standardized and less dynamic. This, if it were true, would be a great pity.

President Bill Clinton has had many opponents and enemies, most of whom come from the political right wing. Clinton supporters contend that these opponents, throughout the Clinton presidency, systematically have sought to undermine this president with the goal of bringing down his presidency and running him out of office; and that they have sought non‐electoral means to remove him from office, including Travelgate, the death of Deputy White House Counsel Vincent Foster, the Filegate controversy, and the Monica Lewinsky matter. This bibliography identifies these and other means by presenting citations about these individuals and organizations that have opposed Clinton. The bibliography is divided into five sections: General; “The conspiracy stream of conspiracy commerce”, a White House‐produced “report” presenting its view of a right‐wing conspiracy against the Clinton presidency; Funding; Conservative organizations; and Publishing/media. Many of the annotations note the links among these key players.

An abundance of techniques has been presented so forth for waste classification but, they deliver inefficient results with low accuracy. Their achievement on various repositories is different and also, there is insufficiency of high-scale databases for training. The purpose of the study is to provide high security.

In this research, optimization-assisted federated learning (FL) is introduced for thermoplastic waste segregation and classification. The deep learning (DL) network trained by Archimedes Henry gas solubility optimization (AHGSO) is used for the classification of plastic and resin types. The deep quantum neural networks (DQNN) is used for first-level classification and the deep max-out network (DMN) is employed for second-level classification. This developed AHGSO is obtained by blending the features of Archimedes optimization algorithm (AOA) and Henry gas solubility optimization (HGSO). The entities included in this approach are nodes and servers. Local training is carried out depending on local data and updations to the server are performed. Then, the model is aggregated at the server. Thereafter, each node downloads the global model and the update training is executed depending on the downloaded global and the local model till it achieves the satisfied condition. Finally, local update and aggregation at the server is altered based on the average method. The Data tag suite (DATS_2022) dataset is used for multilevel thermoplastic waste segregation and classification.

By using the DQNN in first-level classification the designed optimization-assisted FL has gained an accuracy of 0.930, mean average precision (MAP) of 0.933, false positive rate (FPR) of 0.213, loss function of 0.211, mean square error (MSE) of 0.328 and root mean square error (RMSE) of 0.572. In the second level classification, by using DMN the accuracy, MAP, FPR, loss function, MSE and RMSE are 0.932, 0.935, 0.093, 0.068, 0.303 and 0.551.

The multilevel thermoplastic waste segregation and classification using the proposed model is accurate and improves the effectiveness of the classification.

Cleanrooms are highly controlled enclosed rooms where air quality is monitored and ensured to have less contamination according to standard cleanliness level. Air filters are used to optimize indoor air quality and remove air pollutants. Filter media and filtering system are decided as per requirement. Depth filter media are mostly used in cleanroom filtrations. This paper aims to present a comprehensive review of the evolution of cleanroom filter media. It evaluates the advantages and disadvantages of air filter media. It is also studied which air filters have additional properties such as anti-microbial properties, anti-odour properties and chemical absorbent. Development and innovation of air filters and filtration techniques are necessary to improve the performance via the synergistic effect and it can be a possible avenue of future research.

This paper aims to drive the future of air filter research and development in achieving high-performance filtration with high filtration efficiency, low operational cost and high durability. Air pollutants are classified into three types: suspended particles, volatile organic pollutants and microorganisms. Technologies involved in purification are filtration, water washing purification, electrostatic precipitation and anion technology. They purify the air by running it through a filter medium that traps dust, hair, pet fur and debris. As air passes through the filter media, they function as a sieve, capturing particles. The fibres in the filter medium provide a winding path for airflow. There are different types of air filters such as the high-efficiency particulate air filter, fibreglass air filter and ultra-low particulate air filter.

Emerging filtration technologies and filters such as nanofibres, filters with polytetrafluoroethylene membrane are likely to become prevalent over the coming years globally. The introduction of indoor air filtration with thermal comfort can be a possible avenue of future research along with expanding indoor environment monitoring and improving air quality predictions. New air filters and filtration technologies having better performance with low cost and high durability must be developed which can restrict multiple types of pollutants at the same time.

The systematic literature review approach used in this paper highlights the emerging trends and issues in cleanroom filtration in a structured and thematic manner, enabling future work to progress as it will continue to develop and evolve.

This article proposes diffractive vignettes as a new analytical approach that can sensitize organizational communication research to extra/linguistic forces in the communicative constitution of major societal challenges such as the climate crisis. The critical feminist concept of diffraction examines how diverse forces interact, interfere and produce new patterns of meaning and difference through entangled, performative relations.

Diffraction as an analytical tool is illustrated based on fieldwork on organizing the climate crisis in the tourist destinations in the Tyrolean Alps and Venice. We analytically attune to how extra/linguistic forces move and resonate with us, how we read them through each other in a diffractive experiment and how they allow us to attend to materialization differently through crafting diffractive vignettes.

We account for how the analytical work required us to experiment with juxtaposing, weaving, dividing and melting data and theories together through non-representational, post-qualitative ways of analyzing. Through a diffractive vignette, we then unfold how the extra/linguistic forces became agentic for the constitution of the climate crisis.

Through diffractive vignettes, we extend a fast-developing body of work on materialization within organizational communication to analytically exploit communication’s performativity, including its extra/linguistic forces in a post-qualitative, non-representational sense. With diffraction, we expand the analytical potential of organizational communication scholarship with a sensitivity to difference in materialization.