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Using a combination of the geographical information system (GIS) and the Canadian water quality index (WQI), the current study sought to provide a long-term general assessment of the water quality of the Shatt Al-Arab River (SAAR), focusing on its suitability for living organisms. Likewise, SPSS statistics was used to develop a nonlinear WQI regression model for the study area.

The study required four decades of data collection on some environmental characteristics of river water. After that, calculate the WQI and conduct the spatial analysis. Eight variables in total, including water temperature, dissolved oxygen, potential hydrogen ions, electrical conductivity (EC), biological oxygen demand, turbidity, nitrate and phosphate, were chosen to calculate the WQI.

Throughout the study periods, the WQI values varied from 55.2 to 79.83, falling into the categories of four (marginal) and three (fair), with the sixth period (2007–2008) showing the most decline. The present research demonstrated that the high concentration of phosphates, the high EC values, and minor changes in the other environmental factors are the major causes of the decline in water quality. The variations in ecological variables' overlap are a senior contributor to changes in water quality in general. Notably, using GIS in conjunction with the WQI has shown to be very effective in reducing the time and effort spent on investigating water quality while obtaining precise findings and information at the lowest possible expense. Calibration and validation of the developed model showed that this model had a perfect estimate of the WQI value. Due to its flexibility and impartiality, this study recommends using the proposed model to estimate and predict the WQI in the study area.

Even though the water quality of the SAAR has been the subject of numerous studies, this is the only long-term investigation that has been done to evaluate and predict its water quality.

Sports advertisements such as the Super Bowl showcase products and brands that have invested increasingly large sums financially to gain viewers’ attention. However, how audio features in advertisements impact viewers' behavior remains unexplored.

Using the lens of signaling theory, this research uses advanced data analytics of voice and music audio in Super Bowl advertisements to examine its impacts on viewers.

Results show that advertisement viewers prefer more voiced frames and have a greater liking behavior of voiced frames with a low intensity (less loud) and a higher F1 frequency, which is typically associated with male vocal tracts. A fast music tempo works better for longer advertisements. The model controls for various types of ad appeals. The research underlines the importance of voice and music in signaling successful brand features that are likely to increase the ad-liking behavior of consumers (positive effect).

The current research implies that brands advertising through sports ads must carefully select voice actors and music in order to provide the most positive signals for a brand to have the most significant effect and, thus, a greater return on the high sums invested in the ads.

First, this research contributes in terms of a new research process for using audio analytics in advertising. The detailed research process outlined can be used for future research examining audio and music from advertisements. Second, our findings provide additional support to the important role of voice features (e.g. intensity and frequency) as signals in inducing responses from consumers (Biswas et al., 2019; Hagtvedt and Brasel, 2016). Third, the study surfaces a new theoretical association: the effect of tempo in moderating the relationship between duration and propensity to like an ad.

Evidence suggests supported living can improve functioning and reduce need. However, its lack of a clear definition has presented significant challenges to establishing a definitive evaluation of its efficacy. This study aims to evaluate the efficacy of a defined model of supported living using in terms of reductions made to aspects of clinical and social recovery.

A naturalistic, non-controlled assessment was conducting using using the Camberwell Assessment of Need Clinical Scale with a sample of adults with severe and enduring mental illness residing with a UK-based mental health company at 1 of 12 UK locations.

Analysis regarding preliminary outcomes relating to health and social need is presented with comparison between admission and six-months post-admission (N = 90). Additional analysis relating to outcomes at 12 months is also provided (N = 39). Significant outcomes are noted at both timepoints in terms of reducing unmet need and levels of formal and informal help given/required during tenancy.

The findings support that, even in the absence of clinical recovery, opportunities exist to make meaningful and valuable improvements to unmet need and functional independence, with implications for clinical practice in the context of supported living.

The findings provide encouraging early indications of the benefits of the model in making meaningful reductions to functional and psychological needs in individuals with severe and enduring mental illness.

As sustainability becomes more important in manufacturing, researchers recommend using the four-stage Hayes and Wheelwright (H-W) model of strategic manufacturing effectiveness (SME) to integrate sustainable manufacturing practices (SMPs) at a strategic level. However, there is limited research on this topic. This paper investigates SMPs encompassing four sustainable manufacturing capabilities (SMCs): pollution control, pollution prevention, product stewardship, and clean technology. It relates these SMCs to the four SME stages of the H-W model, both of which form a continuum of stages.

A theoretical model on the congruence between SMCs and SME stages is first established using organizational theories to identify the dominant combinations. This model is then tested by examining 178 SMPs of four large manufacturing firms.

The study reveals that the SMPs of the case firms clearly show SMC and SME stage characteristics. Few deviations from the relationships established in the theoretical model are observed, leading to a revision of the model. A major finding is that SMPs within an SMC category can span multiple SME stages.

The study proposes a revised model based on a small sample of case firms, which may limit its broader applicability.

Manufacturing practitioners can use the findings of this study to plan SMPs that align with their SME goals.

Towards incorporating sustainability in the H-W model, this is the first major exploratory study that establishes congruent relationship between SMCs and SME stages of the H-W model.

This study aims to understand the impact of a pilot of the actions against racism (AAR) intervention, aimed at enhancing educators’ multicultural efficacy and attitudes in a mid-Atlantic K-8 charter school.

AAR included eight sessions delivered over one school year. Experienced facilitators led these sessions, focusing on combating racism, prejudice and discrimination. Of the 84 school staff, 56 completed a baseline survey and 33 completed a postintervention survey.

Paired sample t-tests revealed a significant increase in multicultural attitudes, t(29) = 2.55, p = 0.016, whereas the increase in multicultural efficacy was not significant, t(28) = 1.93, p = 0.063. The authors examined cultural and emotional intelligence as moderators of the intervention’s impact. Higher baseline cognitive reappraisal scores (an indicator of emotional intelligence) were linked to a larger increase in multicultural efficacy from pre- to postintervention, B = −0.59, t (27) = −2.20, p = 0.037. The number of sessions attended was unrelated to the intervention’s impact.

This study was a single-site, uncontrolled pilot of AAR with a small sample size. Further research in additional settings with appropriately powered samples is needed to validate these results and extend findings to examine the impact of AAR on the student experience.

The study demonstrates the promising potential of AAR in improving teachers' multicultural attitudes and efficacy. Exploratory findings highlight the role of cognitive reappraisal in enhancing multicultural efficacy, contributing valuable insights for designing effective teacher training programs. This research supports the implementation of critical, identity-centered and asset-based pedagogies in education.

This study aims to integrate and extend leading contemporary underpinning frameworks such as the Stimulus Organism Response (S-O-R) model, Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) to assess the determinants of M-commerce usage during COVID-19 times. Besides direct effects, the study examines the mediating role of behavioral intention in affecting the relationship between a few external stimuli, internal states (of the organism) and M-commerce usage (the response). The study has also examined the moderating role of habitual behavior in the relationship between behavioral intention and M-commerce usage.

Data were gathered from 312 customers through an online survey using a structured questionnaire. PLS-based SEM, using Smart PLS 4.0, was employed to calibrate the measurement and structural models.

The study found that stimuli like social influence, perceived ease of use and perceived value substantially affected M-commerce usage. Behavioral intention has been found to mediate these cause-and-effect relationships partially or fully among the subject constructs. Additionally, a significant negative but weak moderating impact of habit (or habitual behavior) on the relationship between behavioral intentions and M-commerce usage has been corroborated.

Several studies have investigated the factors influencing the adoption and continued usage of M-commerce services while appealing to diverse theoretical frameworks. However, more research has yet to be expended to arrive at an integrated explanation grounded in these theoretical frameworks to examine the dynamics of M-commerce usage in tempestuous times like the COVID-19 outbreak. The most significant (counterintuitive) findings have been suppressing the effects of otherwise crucial elements like perceived security and habit in prompting M-commerce usage in the face of the socio-psychological pressures stemming from COVID-19 restrictions and consumers' lack of digital readiness. The study's outcomes offer several theoretical and practical implications for researchers, managers, practitioners, businesses and policymakers to develop effective strategies to mature M-commerce usage among the masses, especially during unusual times like COVID-19.

This study explores the distribution of insufficient effort responders according to methods of classifying students’ evaluation of teaching effectiveness in higher education. Five different methods were found in the literature to classify students’ evaluation of teaching effectiveness in higher education.

Quantitative research methodology was used to achieve the goals of this study. Data from a major public university was used through 20 five-point items that are designed to measure students’ evaluation of teaching effectiveness. The dataset that consisted of 26,679 surveys was analyzed. Detecting insufficient efforts responding was based on item response theory procedures.

The results show that insufficient effort responders are distributed differently to students’ evaluation of teaching effectiveness in higher education levels according to different methods of classifying these levels. The results of this study suggest using a percentage of students’ agreement of 4 or 5 for each item to classify SET levels and deleting IERs before interpreting SET results.

According to the results of this study, it is recommended to research the relationships between IER and SET scores and students’ motivation to participate in evaluating teaching effectiveness.

According to the results of this study, it is recommended to:1– Exclude the IERs from the dataset before generating SET reports. 2– Use the percentage of 4 (agree) and 5 (strongly agree) satisfactions of SET items to classify and interpret SET results.

Reviewing the literature shows the absence of studies that explore the distribution of insufficient effort responders according to methods of classifying students’ evaluation of teaching effectiveness in higher education. The results suggest using a percentage of students’ agreement of 4 or 5 for each item to classify SET levels and deleting IERs before interpreting SET results.

Advances in information technology and the increasing digitalization of the general public have favored the growth of the sharing economy. The sharing economy is based on transactions of idle resources between individuals to satisfy cogent needs. Notwithstanding the great interest in this emerging phenomenon, it is still not clear which factors are driving the shift in consumer consumption behavior from the traditional economy toward this new economic model. Grounded in self-determination theory, we contend that what is needed is a holistic approach that considers the three elements involved in sharing economy transactions, namely (1) consumer motivations, (2) web-based platforms and (3) types of assets exchanged.

To conduct our study, we used the Flash Eurobarometer 467 database titled “The Use of the Collaborative Economy,” collected by the European Union with Flash Eurobarometer datasets and openly available to the public. Consequently, our study aims to provide results based on a large-scale quantitative analysis involving a large number of individuals and multiple sectors.

Our findings provide empirical evidence of the positive effects of the shift in consumption behavior toward the sharing economy brought about by (1) consumers’ intrinsic motivations, (2) the quality of the platform and (3) the human asset-based categories of products offered.

This research seeks to advance understanding of the factors that facilitate the adoption of the sharing economy, and we provide managers and policymakers with suggestions regarding the factors they may leverage to further favor the spread of this economic model.

The present study examines the antecedents of learned helplessness, i.e. intrinsic and environmental constraints and consequences, i.e. intention to travel and expectation in the context of people with disability (PwD) tourism context by applying the “Theory of Learned Helplessness”.

The survey method was used to gather data from 209 physically disabled people who had visited/traveled to any tourist destination in the past twelve months. Structural equation modeling technique was used to analyze data.

The findings reveal that intrinsic and environmental constraints positively influence learned helplessness. Consequently, learned helplessness negatively effects intention to travel and positively affects expectation of PWD tourist' toward a travel destination. Furthermore, learned helplessness contributed as a mediator between intrinsic constraints and intention to travel toward a tourist destination.

Even though the body of literature on associations studied pertaining the conceptual lens of learned helplessness is widely recognized, there is dearth of literature investigating the connections between travel constraints, learned helplessness, PwDs intention and their expectation in travel destination context.

This paper aims at understanding the differences between user profiles in collaborative consumption (CC) platforms in order to improve their management approaches and set up customized strategies. Particularly, the authors investigate the emerging role of prosumers and their influence on the active participation and growth of CC platforms. Moreover, the authors study user experience to help promoting users' recommendation and offering intention.

The sample includes responses from 6,388 users of CC platforms across the EU. The data were collected through the European Commission's Flash Eurobarometer survey 467 and analyzed through a partial least squares structural equation modeling (PLS-SEM) and a fuzzy set qualitative comparative analysis (fsQCA).

The PLS-SEM findings suggest that prosumers are more likely than consumers to recommend and offer services through CC platforms. Furthermore, previous experience using platforms positively affects the switch from consumers to prosumers. The fsQCA suggests that only economic advantages affect the switchover decision.

This study deepens the hitherto unexplored prosumer role in CC platforms and its antecedents and drivers.

The main limitations concern the generalizability outside of the EU, the unbalanced coverage of sectors and the number of moderator variables.

Prosumers act as golden actors because they contribute to enlarge both the customer base (through recommendations) and the provider base (through offering intention). Hence, managers should focus on prosumers' experiences to increase the critical mass and positive externalities of CC platforms.

This study helps understand the importance of the role of prosumers in the growth of CC platforms. The study provides more robust results through a cross-country and mixed-method research.