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Due to the continuous and rapid evolution of telecommunication equipment, the demand for more efficient and noise-robust detection of dual-tone multi-frequency (DTMF) signals is most significant.

A novel machine learning-based approach to detect DTMF tones affected by noise, frequency and time variations by employing the k-nearest neighbour (KNN) algorithm is proposed. The features required for training the proposed KNN classifier are extracted using Goertzel's algorithm that estimates the absolute discrete Fourier transform (DFT) coefficient values for the fundamental DTMF frequencies with or without considering their second harmonic frequencies. The proposed KNN classifier model is configured in four different manners which differ in being trained with or without augmented data, as well as, with or without the inclusion of second harmonic frequency DFT coefficient values as features.

It is found that the model which is trained using the augmented data set and additionally includes the absolute DFT values of the second harmonic frequency values for the eight fundamental DTMF frequencies as the features, achieved the best performance with a macro classification F1 score of 0.980835, a five-fold stratified cross-validation accuracy of 98.47% and test data set detection accuracy of 98.1053%.

The generated DTMF signal has been classified and detected using the proposed KNN classifier which utilizes the DFT coefficient along with second harmonic frequencies for better classification. Additionally, the proposed KNN classifier has been compared with existing models to ascertain its superiority and proclaim its state-of-the-art performance.

This study aims to evaluate the suitability of Ferrock as a green construction material by analysing its engineering properties, environmental impact, economic viability and adoption challenges. It also aims to bridge knowledge gaps and provide guidance for integrating Ferrock into mainstream construction to support the decarbonisation of the built environment.

It presents a systematic and holistic review of existing literature on Ferrock, comprehensively analysing its mechanical properties, environmental and socio-economic impact and adoption challenges. The approach includes evaluating both quantitative and qualitative data to assess Ferrock’s potential in the construction sector.

Key findings highlight Ferrock’s superior mechanical properties, such as higher compressive and tensile strength, and enhanced durability compared to traditional Portland cement. Ferrock offers significant environmental benefits by capturing more CO₂ during curing than it emits, contributing to carbon sequestration and reducing energy consumption due to the absence of high-temperature processing. However, the material faces economic and technical challenges, including higher initial costs, scalability issues, lack of industry standards and variability in production quality.

This review provides a comprehensive and up-to-date analysis of Ferrock. Despite being discussed for a decade, Ferrock research has been overlooked, with existing studies often limited and published in poor-quality sources. By synthesising current research and identifying future study areas, the paper enhances understanding of Ferrock’s potential benefits and challenges. The originality lies in the holistic evaluation of Ferrock’s properties and its implications for the construction industry, offering insights that could drive collaborative research and policy support to facilitate its integration into mainstream use.

The purpose of this study investigate the antecedents the adoption of tour itineraries from smart travel apps. Travelers are progressively expanding their smart travel planning applications to organize their trip-related activities. With the help of these apps, users achieve their favorite tour itineraries and choose their preferred destinations.

This study aimed to examine the results of smart tour itineraries on travelers and elucidate the motivations for their continual use and why travel experts are increasingly using smart tour itineraries. Innovation resistance and experiential consumption theories were used in this study. SmartPLS 3.2.8 was used to consider 682 valid samples using structural equation modeling (SEM).

This analysis identified the following crucial factors: usage, value, risk and traditional barriers. Moreover, utilitarian and hedonic values significantly affected barriers. Finally, theoretical and practical suggestions are presented along with future research directions.

This study encompasses the tender of innovation resistance theory to travel itineraries by integrating experiential consumption theory in the context of smart tourism apps.

Employing the extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, this study examines the potential differences between two groups of hotel guests – business and leisure travelers – in terms of factors influencing their intention to purchase hotel products on Douyin (TikTok) in China.

Data gathered from 700 Chinese hotel guests was analyzed using partial least squares-structural equation modeling (PLS-SEM) and multigroup analysis (MGA).

The MGA results reveal that three newly added variables – personalization, perceived interactivity and perceived creativity – significantly influence the purchase intention of leisure travelers but not business travelers. Regarding the conventional UTAUT2 variables, leisure travelers are more influenced by hedonic motivation and price value in their purchasing decisions. In contrast, performance expectancy and effort expectancy have a greater impact on the decision-making process of business travelers than their leisure counterparts.

Theoretically, this paper is among the first to explore traveler types as moderators in the purchase of hotel products on Douyin. Practically, the findings offer valuable guidance for hotel marketers aiming to leverage Douyin to promote hotel products to these two different traveler segments.

Instead of using “one-size-fits-all” strategies, hotel managers should design marketing strategies that address the diverse needs of business and leisure travelers on Douyin. By implementing this strategy, they can effectively attract target customers and, in turn, increase hotel revenue.

This study expands the UTAUT2 framework and contributes to the scarce knowledge about the differences between business and leisure travelers regarding the relative importance of factors that influence their purchase intention for hotel products on Douyin among business and leisure travelers.

This study aims to explore the factors affecting investment behaviour in cryptocurrencies among Jordanian investors. Specifically, it aims to assess how various motivational and behavioural drivers impact the intention to use cryptocurrencies, grounded in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework. The choice of Jordan as the research context is particularly relevant due to the lack of adequate regulations on cryptocurrency investment.

This study uses a quantitative research approach, using an online survey as the primary method for data collection. The final data set consists of 285 responses collected through a self-administered questionnaire to cryptocurrency users in Jordan. Next, structural equation modelling (SEM) was used to test the developed theoretical framework based on the UTAUT2 model.

The findings reveal that performance expectancy, trust, hedonic motivation and price value significantly enhance the intention to invest in cryptocurrencies, with performance expectancy acting as a mediator. Effort expectancy is not directly related to behavioural intention; however, it positively impacts performance expectancy, validating the mediation hypothesis. Trust affects both the intention to use and the performance expectancy, reinforcing its role as a mediator in cryptocurrency adoption. Hedonic motivation and price value also positively affect the intention to use cryptocurrency. In contrast, social influence and facilitating conditions do not significantly impact behavioural intention, suggesting that cryptocurrency adoption decisions are less influenced by external opinions or the availability of necessary conditions. The findings also show that the demographic profiles of the cryptocurrency users were young, educated males, which suggests a demographic skew in cryptocurrency usage in Jordan.

This study innovatively adapts the UTAUT2 model, focusing on the mediating role of performance expectancy between effort expectancy, trust, and behavioural intention. This study pioneers by examining the mediation effect of performance expectancy, showing how users' ease in using cryptocurrencies positively affects their belief in positive outcomes, subsequently influencing their behavioural intention to use cryptocurrencies. Moreover, this study sheds light on the factors driving cryptocurrency adoption in developing countries like Jordan. It also underscores the demographic trends in cryptocurrency use and proposes targeted recommendations for policymakers and cryptocurrency platforms to foster more inclusive and informed investment environments.

Three-dimensional (3D) food printers are revolutionizing food production with personalized, sustainable and efficient meal creation. This study aims to explore the factors driving consumer intentions to purchase three-dimensional (3D) food printers. These innovative devices are gaining popularity for their ability to produce intricate, customizable food designs with remarkable precision and convenience. By leveraging the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, the research examines key variables such as performance expectancy, effort expectancy, social influence, facilitating conditions (FCD), hedonic motivation and perceived product value. The aim is to understand how these factors shape consumer behavior and decision-making, providing insights into the adoption dynamics of 3D food printers for professional and domestic use.

This study collected 973 valid responses through an online survey. The data were analyzed using partial least squares structural equation modeling.

Performance expectancy, social influence and perceived product value significantly enhance consumers’ intention to purchase 3D food printers. In contrast, effort expectancy, FCD and hedonic motivation show no statistically significant impact on their usage intention.

Companies in the 3D food printing industry should prioritize improving product performance and leveraging social influencers to spark consumer interest. Educating the public about the benefits of 3D food printing is essential for building market acceptance and demand. Governments should contemplate implementing policies and regulations encouraging companies to invest in research and development in this field. This study acknowledges its limitations and recommends directions for future research.

This study establishes its originality by integrating hedonic motivation and perceived product value with the original UTAUT framework to investigate Chinese households’ intentions to use a 3D food printer.

This study aims to identify the significant factors that influence the continuation intention (CI) to use a digital wallet in the regions with low technology infrastructure and among the consumers possessing low levels of digital and financial literacy.

Data for the study were collected from the rural parts of South India with 295 digital wallet users. Co-variance-based structural equation modelling (SEM) (CB-SEM) using maximum likelihood estimation method and Bayesian SEM (BSEM) approaches were executed to test the influence of independent variables on the dependent variable and to ensure the validation of the proposed hypothetical model.

The results showed that trust, incentives, technology satisfaction (TS), facilitating condition, performance expectancy, effort expectancy, habit and hedonic motivation significantly influenced the CI to use a digital wallet. In addition, incentives positively impact habit for the CI to use a digital wallet.

The present study is based on the samples from the regions with low technology infrastructure and among the consumers possessing low levels of digital and financial literacy in the rural parts of South India, which limits the generalisation of results.

The results provide impetus to the government, digital wallet marketers and users regarding how the CI to use a digital wallet can be encouraged among the low-adoption regions.

This study remains unique as the assessment of CI to use a digital wallet was conducted in low-adoption regions (rural parts of India) in extending Unified theory of acceptance and use of technology 2 with TS. A comparison of results arrived from CB-SEM with those of the BSEM ensures that the validation of the hypothetical model is found to be another major methodological contribution towards the consumer behaviour literature.

The authors aim to study a conceptual model based on behavioural theories (UTAUT-3 model) to evaluate the adoption, usage and recommendation for neobanking services in India.

The authors propose this model based on the UTAUT-3 integrated with perceived risk constructs. Hypotheses were developed to determine the relationships and empirically validated using the PLSs-SEM method. Using the survey method, 680 Delhi NCR respondents participated in the survey.

Empirical results suggested that behavioural intention (BI) to usage, adoption and recommendation affects neobanking adoption positively. The research observed that performance expectancy (PE), effort expectancy (EE), perceived privacy risk (PYR) and perceived performance risk (PPR) are the essential constructs influencing the adoption of neobanking services.

Limited by geographic and Covid-19 constraints, a cross-sectional study was conducted. It highlights the BI of neobanking users tested using the UTAUT-3 model during the Covid-19 period.

The study's outcome offers valuable insights into Indian Neobanking services that researchers have not studied earlier. These insights will help bank managers, risk professionals, IT Developers, regulators, financial intermediaries and Fintech companies planning to invest or develop similar neobanking services. Additionally, this research provides significant insight into how perceived risk determinants may impact adoption independently for the neobanking service.

This study aims to deal with the case adaptation problem associated with continuous data by providing a non-zero base solution for knowledge users in solving a given situation.

Firstly, the neighbourhood transformation of the initial case base and the view similarity between the problem and the existing cases will be examined. Multiple cases with perspective similarity or above a predefined threshold will be used as the adaption cases. Secondly, on the decision rule set of the decision space, the deterministic decision model of the corresponding distance between the problem and the set of lower approximate objects under each choice class of the adaptation set is applied to extract the decision rule set of the case condition space. Finally, the solution elements of the problem will be reconstructed using the rule set and the values of the problem's conditional elements.

The findings suggest that the classic knowledge matching approach reveals the user with the most similar knowledge/cases but relatively low satisfaction. This also revealed a non-zero adaptation based on human–computer interaction, which has the difficulties of solid subjectivity and low adaptation efficiency.

In this study the multi-case inductive adaptation of the problem to be solved is carried out by analyzing and extracting the law of the effect of the centralized conditions on the decision-making of the adaptation. The adaption process is more rigorous with less subjective influence better reliability and higher application value. The approach described in this research can directly change the original data set which is more beneficial to enhancing problem-solving accuracy while broadening the application area of the adaptation mechanism.

The examination of the calculation cases confirms the innovation of this study in comparison to the traditional method of matching cases with tacit knowledge extrapolation.

The algorithm models established in this study develop theoretical directions for a multi-case induction adaptation study of tacit knowledge.

This study designs a multi-case induction adaptation scheme by combining NRS and CBR for implicitly knowledgeable exogenous cases. A game-theoretic combinatorial assignment method is applied to calculate the case view and the view similarity based on the threshold screening.

Kerala, being the most literate state in India, has at least one newspaper being subscribed to every household and thus the Print industry in Kerala is doing a commendable job. Labour welfare as a part of industrial relation is assuming greater significance with the growth of industrialization. An industry today is a co-operative undertaking with both the capital and the labour as equal partners. The workers in the modern context are not simply a marketable commodity to be purchased by the owners, but human beings with their own needs, emotions and aspirations who invest their labour in making the industry a success. It is normally believed that the model employer maintains harmonious relation with the employees. Considering the conflicts are usually natural, the employer always tries to minimize the disputes by offering the right mix of labour welfare measures and ensure the loss of man days and the loss of production to the lowest possible extent. This article delineates the industrial relations in Kerala newspaper industry. The data were analyzed related to age, occupation, region of working, education and experience on the leaders' attitude on various factors related to labour welfare. The primary data collected from the trade union leaders were analyzed using the statistical computer package SPSS. Appropriate tests were used for analysis. It can be seen that the leaders were not at all satisfied with any of the facilities except for safety practices for the employees and the grievance handling process since they were directly involved.