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Over time, the concept of word of mouth (WOM) has spread beyond marketing into other disciplines. This is because WOM is important in decision-making at both the individual and organisational levels. Also, people are more likely to trust recommendations from their peers than those from companies. Therefore, the purpose of this study is to investigate the perceived usefulness of WOM messages for small and medium-sized enterprise (SME) suppliers in participating in Tanzanian public procurement opportunities.

The study collected cross-sectional data from 214 SME suppliers who supply common use items to public procuring organisations in Dodoma City, Tanzania. Structural equation modelling was used to test the direct relationships between study variables, and Hayes' PROCESS macro was used to test for the indirect effect of WOM message delivery on WOM attributes and the perceived usefulness of WOM.

WOM attributes that include expertise differential, perceptual homophily, and trustworthiness are related to the perceived usefulness of WOM. Also, WOM message delivery mediates the relationship between the WOM attributes and the perceived usefulness of WOM in enhancing public procurement participation. Therefore, the study's findings revealed that WOM is applicable in the public procurement context, under which public buyers act as senders and suppliers act as receivers. The latter finds out about public procurement opportunities and responds to them, while the former gives suppliers whatever information they need to respond to public procurement tenders that have been advertised.

Because the study was cross-sectional, it was difficult to determine whether the opinions gathered over time remained consistent. Furthermore, only suppliers who are parties to framework contracts under Government Procurement Services Agency were included in the study. Therefore, the sample was limited to only suppliers supplying common use items to various public organisations in Dodoma City, Tanzania.

This paper integrates the concept of WOM from the marketing discipline and public procurement. As a result, the study adds to the understanding of the use of information transmission in terms of the contribution of WOM messages from public buyers to suppliers to enhance small and medium enterprises' participation in public procurement opportunities.

Grounded on the distributed theory and the social exchange theory, the current study investigates the determinants that positively influence job performance among educators within the realm of higher education in India. It particularly assesses the impact of perceived academic leadership on performance and explores the mediating and moderating effects of organizational citizenship behavior and informal institutional leadership.

Employing a descriptive research design, this study encompasses a broad cross-section of faculty members from various higher educational institutions across India. Data were gathered from 826 educators using a snowball sampling technique, with questionnaires administered online. Each variable was measured using prevalidated scales.

The findings from the moderated mediation model indicate a significant indirect relationship between perceived academic leadership and job performance, which is mediated by organizational citizenship behavior. Furthermore, informal institutional leadership demonstrates significant conditional indirect effects, enhancing the link between academic leadership and job performance up to a threshold, beyond which its influence diminishes.

This study pioneers the exploration of academic dynamics beyond mere titles and ranks in the Indian educational sector. It delineates both the direct and indirect roles these dynamics play in enhancing faculty performance, providing a novel insight into the complexities of academic leadership.

To enhance portfolio decision-making using a capital asset pricing model-based clustering analysis.

Capital asset pricing model (CAPM); K-means clustering; agglomerative clustering.

Employing clustering along with CAPM to identify varying levels of risk appetite among customers enables the customization of security recommendations, enhancing client satisfaction and portfolio performance.

By employing multi-factor models as the foundation for clustering, thereby integrating additional dimensions of risk and return.

This study aims to present recent trends in touchscreen research through scientometric analysis. Devices with touchscreen are powerful tools for performing specialized operations. The touch screens of tablets, smartphones, laptops and television play an important role in teaching, learning and research.

The data was collected from Web of Science database from 2011 to 2021 and analysed using MS-Excel and VOSviewer software. After analysing 389 research papers, the authors identified the high impact journals, collaboration of countries, institutions, authors and growth trend of publications. Analysing the most used keywords, country-wise distribution of publications and research collaboration between institutions will help interpret the research trends in the selected time span.

The publications show an increase in number over the years from 2011 to 2021. Among the countries, USA has the highest number of 127 articles published, followed by England (61) and Canada (30). The results showed that the multiple authorship pattern in touchscreen publication is high when compared to single authors. The institutional analysis indicated that the organizations publishing more than five documents in the area were mostly from United Kingdom, Australia, USA and Korea. Timeline visualizations identified prominent keywords like touchscreen, performance, operant platform, Alzheimer’s disease, etc. in the subject. Interdisciplinary research is dominant in the subject, as seen from the most preferred journals and keywords.

The analysis does not include a comprehensive coverage of the research output, as only Web of Science database from 2011 to 2021 in a 10-year period is included.

The study would benefit stakeholders, including manufacturers and researchers alike, to know the future of touchscreen research.

This study is pertinent to socio-psychological fields because touchscreen technology encourages social connection among older persons and may help foster early literacy skills.

This paper will provide an understanding of the global developments in touchscreen research with recommendations for future research.

Fish processing by grilling can produce emissions that contain toxic compounds that can have short- and long-term effects on human health. Another study reported that exposure to air pollutants is hematotoxic. The purpose of this paper is to determine the effect of smoke exposure on fish grill results on hematological parameters.

The subjects of this study were 90 grilled fish sellers, with 32 processed food sellers who did not sell grill food as a control. The hematological analysis was performed using the Hematology Analyzers KX300 instrument.

The results showed that the mean value of hematological parameters in the test group was higher than the control group except for the number of lymphocytes and mixed cell parameters.

The content of harmful compounds contained in fish grill smoke can increase hematological value in the blood of exposed individuals, which has the potential for health problems and disease progression.

This study aims to deal with the paucity of studies in the stages of the development of loyalty behaviour of customers in the healthcare context by incorporating three crucial service quality dimensions (physical environment, personnel quality and technical quality) and also investigating trust and commitment as mediating factors.

Survey data were obtained from 420 respondents admitted to government hospitals in Kerala employing a convenience sampling method. The formulated hypotheses were tested using partial least square structural equation modelling.

Results indicate that patient satisfaction, trust and commitment can create favourable behavioural intentions amongst patients. When patients reveal higher trust, they are more inclined to value healthcare services and willing to commit to a long-term relationship, resulting in increased patient loyalty.

Organisational efforts should improve trust and commitment and build a good relationship between service providers and patients. Efforts should be taken to raise the standard of technical and personnel aspects, and a focus on physical infrastructure should also be considered to build a favourable behavioural intention to revisit and positive referrals.

This is the first empirical study to analyse technical quality, personnel quality and physical environment along with the mediating effect of trust, and commitment in a four-stage loyalty development model in the healthcare context of Kerala, India.

This paper explores the effect of perceived service quality, trust, perceived value and perceived cost on patient satisfaction and loyalty as well as exploring the moderating role of the sociodemographic factors.

The data were gathered from 462 patients via a structured questionnaire, while structural equation modeling was utilized for the analysis.

Results indicated that trust, perceived value and patient satisfaction have important roles in shaping the patient loyalty, while patient satisfaction was found to fully mediate the patient’s perceived service quality. Loyalty relationship was also found to partially mediate the trust–loyalty relationship. Nonetheless, the patient’s satisfaction–loyalty relationship was found to be only moderated by the age factor.

Implications are provided to the Egyptian private hospitals in order for them to formulate improvement plans as well as set higher standards of conduct.

This original research is the first one, up to the researcher knowledge, that explores the drivers of patient satisfaction in the private hospitals in Egypt.

The aim of this study is to investigate subject independent emotion recognition capabilities of EEG and peripheral physiological signals namely: electroocoulogram (EOG), electromyography (EMG), electrodermal activity (EDA), temperature, plethysmograph and respiration. The experiments are conducted on both modalities independently and in combination. This study arranges the physiological signals in order based on the prediction accuracy obtained on test data using time and frequency domain features.

DEAP dataset is used in this experiment. Time and frequency domain features of EEG and physiological signals are extracted, followed by correlation-based feature selection. Classifiers namely – Naïve Bayes, logistic regression, linear discriminant analysis, quadratic discriminant analysis, logit boost and stacking are trained on the selected features. Based on the performance of the classifiers on the test set, the best modality for each dimension of emotion is identified.

 The experimental results with EEG as one modality and all physiological signals as another modality indicate that EEG signals are better at arousal prediction compared to physiological signals by 7.18%, while physiological signals are better at valence prediction compared to EEG signals by 3.51%. The valence prediction accuracy of EOG is superior to zygomaticus electromyography (zEMG) and EDA by 1.75% at the cost of higher number of electrodes. This paper concludes that valence can be measured from the eyes (EOG) while arousal can be measured from the changes in blood volume (plethysmograph). The sorted order of physiological signals based on arousal prediction accuracy is plethysmograph, EOG (hEOG + vEOG), vEOG, hEOG, zEMG, tEMG, temperature, EMG (tEMG + zEMG), respiration, EDA, while based on valence prediction accuracy the sorted order is EOG (hEOG + vEOG), EDA, zEMG, hEOG, respiration, tEMG, vEOG, EMG (tEMG + zEMG), temperature and plethysmograph.

Many of the emotion recognition studies in literature are subject dependent and the limited subject independent emotion recognition studies in the literature report an average of leave one subject out (LOSO) validation result as accuracy. The work reported in this paper sets the baseline for subject independent emotion recognition using DEAP dataset by clearly specifying the subjects used in training and test set. In addition, this work specifies the cut-off score used to classify the scale as low or high in arousal and valence dimensions. Generally, statistical features are used for emotion recognition using physiological signals as a modality, whereas in this work, time and frequency domain features of physiological signals and EEG are used. This paper concludes that valence can be identified from EOG while arousal can be predicted from plethysmograph.