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This study aims to investigate and test the impact of competitive priorities, in terms of quality, speed, dependability, flexibility, cost and patient engagement, on patient satisfaction with healthcare services. It considers patients’ rather than managers’ points of view to collect responses about competitive priorities.

This research employed a cross-sectional survey design to analyze a sample of customers through an empirical study of 488 patients in Qatar’s healthcare service context.

The confirmatory factor analysis results show that competitive priorities and engagement positively and significantly impact patient satisfaction.

Researchers can use this methodology to explore the role of competitive priorities in different service contexts and sectors. The researchers conducted the study in Qatar; therefore, the results are not generalizable to all healthcare sectors. However, regardless of geographic location, the research approach can be used in healthcare.

Managers can employ the developed scales to diagnose competitive priorities and improve customer service experiences.

The paper is original as it suggests using competitive priorities as a measurement tool for predicting patient satisfaction compared to prior research that mostly measured competitive priorities based on internal perspectives (managers’ perspectives). Further, this paper is original because it depends on the external perspective (customers’ perspective) for the competitive priorities for measuring patient satisfaction.

Near-fault pulse-like ground motions have distinct and very severe effects on reinforced concrete (RC) structures. However, there is a paucity of recorded data from Near-Fault Ground Motions (NFGMs), and thus forecasting the dynamic seismic response of structures, using conventional techniques, under such intense ground motions has remained a challenge.

The present study utilizes a 2D finite element model of an RC structure subjected to near-fault pulse-like ground motions with a focus on the storey drift ratio (SDR) as the key demand parameter. Five machine learning classifiers (MLCs), namely decision tree, k-nearest neighbor, random forest, support vector machine and Naïve Bayes classifier , were evaluated to classify the damage states of the RC structure.

The results such as confusion matrix, accuracy and mean square error indicate that the Naïve Bayes classifier model outperforms other MLCs with 80.0% accuracy. Furthermore, three MLC models with accuracy greater than 75% were trained using a voting classifier to enhance the performance score of the models. Finally, a sensitivity analysis was performed to evaluate the model's resilience and dependability.

The objective of the current study is to predict the nonlinear storey drift demand for low-rise RC structures using machine learning techniques, instead of labor-intensive nonlinear dynamic analysis.

Various scholars suggest that there is a lack of research on the recruitment in small and medium-sized enterprises (SMEs) and also a scarcity of theoretical basis for the recruitment procedures used by these companies. As the vast majority of studies concentrate on larger organizations, they may not accurately reflect the challenges faced by smaller-sized entities to profoundly and accurately comprehend their recruitment procedures. In addition, the use of technology in recruitment has grown in importance in today’s quickly evolving business environment, particularly in light of the COVID-19 pandemic footprint. This study aims to examine the recruitment procedures used by SMEs and how they have been compelled to adjust to different extents to these technological improvements by the effects of the aforementioned epidemic.

With the aim to investigate the current recruitment practices in SMEs and the extent to which digital technologies are embraced by these companies within human resources (HR) procedures, this research relied on interviews with SMEs representatives. The qualitative methods used provided access to relevant data and insights, as they allowed close interactions with top managers and CEOs of ten companies from various sectors. Thus, the research results draw a vivid and reliable image of the procedures and practices used by small and medium-sized companies to attract, select and retain their staff.

This study’s findings are of increased interest to HR professionals, recruiters and managers in SMEs, who aim to attract and retain the best talent and optimize their recruitment strategies in a rapidly changing business environment, enabled by technological advancements. Effective HR recruitment procedures adapted to the specific needs of small and medium-sized companies can lead to several benefits for the organization, including improved employee selection, reduced turnover and increased organizational productivity.

Although the interviews examined here encompass recruitment techniques from SMEs in a variety of industries, the results’ generalizability is limited by the sample size and geography. Furthermore, the findings’ dependability is dependent on the accuracy of the data provided by the respondents.

This investigation confirms some of the theoretical underpinnings which point to the lack of formalized structures and procedures in the recruitment process in SMEs, which enjoy more flexibility in managing HR processes. In addition, the results reinforce the arguments indicating an adjustment between HR strategies or policies and organizational goals in smaller enterprises which adapt faster to changes in the market. Moreover, it becomes apparent that there is a relationship between the quality of job descriptions and the successful fit in attracting the right candidates for the open positions. Furthermore, digital technologies offer opportunities for expanding the recruiters’ reach to a wider audience and also support the selection stage, thus increasing the chances of finding suitable staff. As the need to shift from traditional recruitment to e-recruitment in SMEs has been highlighted in the literature, the qualitative research revealed that this need was driven on the one hand by the COVID-19 pandemic when these companies successfully adapted and implemented new online methods of recruiting, but also by the lack of skilled labor, leading to the expansion of recruitment to other parts of the country or even to other countries.

With regard to the proportion of men and women used in small and medium-sized companies, there is a clear need to involve and train more women in the predominantly male-dominated industrial and IT sectors. From this point of view, companies tend to devote more interest to integrating communities of women in these industries, as well as in key management positions. Another point of interest that the study highlights is the fact that SMEs have started to get creative with the benefits package they propose to candidates and focus on remote work, hybrid office–home working, or seasonal work to offer future employees a better work–life balance.

The added value of this investigation is filling the gaps in the current literature concerning recruitment procedures currently used by SMEs, the challenges they face and the solutions they advanced to solve them. Furthermore, SMEs often drive innovation and competition in the market and play a crucial role in the supply chain of larger companies, providing them with the goods and services they need to operate and supporting the availability and reliability of products from larger companies. They are often the driving force behind revitalizing local economies and creating new employment opportunities. Consequently, the underlying significance of this study is rooted in the need to modernize and simultaneously improve HR recruitment procedures through the integration of technology and a focus on innovation.

This paper examines the nexus between supply chain social capital (relational social capital and structural social capital), supply chain responsiveness (operations system responsiveness and supplier network responsiveness) and firm performance. Additionally, the study examines the mediating role of supply chain responsiveness on the relationship between supply chain social capital and firm performance.

The authors test their hypotheses on a sample of 120 firms operating in Ghana. The measurement model and hypothesized paths were assessed using partial least squares structural equation modelling.

The findings revealed that structural social capital had a significant direct effect on firm performance, but relational social capital did not. It was also revealed that both relational and structural social capital have significant effects on operations system responsiveness and supplier network responsiveness. Additionally, operations system responsiveness fully mediated the effect of relational social capital on firm performance and partially mediated the effect of structural social capital on firm performance. Supplier network responsiveness, on the other hand, partially mediated the effect of both relational and structural social capital on firm performance.

This study contributes to the limited literature on supply chain social capital by unearthing the mechanisms through which supply chain social capital enhances firm performance. Specifically, the study demonstrates the intervening role of operations system responsiveness and supplier network responsiveness in the supply chain social capital–firm performance link.

This study aims to examine the role of trust and digital literacy in influencing citizens’ adoption of e-government services.

Grounded in the technology acceptance model (TAM), a research model was developed focusing on e-filing services adoption. Hypotheses were formulated to assess the moderating effect of digital literacy on the relationship between trust and the key TAM determinants of perceived usefulness and perceived ease of use. A questionnaire-based survey of 876 citizens who have used e-filing using the snow-ball sampling technique was adopted to generate data. The data was analyzed using PLS-SEM through the aid of SmartPLS 4 to assess the measurement model and structural relationships.

Trust positively influences perceived usefulness and ease of use, which in turn drive adoption. Additionally, digital literacy significantly moderates the impact of trust on usefulness and ease of use perceptions – the effect is stronger for higher digital literacy.

The study adopted a single country developing economy context limiting cross-cultural applicability. Second, the focus on e-filing adoption precludes insights across other e-government services. Third, the reliance on perceptual measures risks respondent biases and fourth, the study is a cross-sectional survey design.

The findings emphasize multifaceted strategies to accelerate e-government adoption. Nurturing citizen trust in e-government systems through enhanced reliability, security and transparency remains vital. Simultaneously, initiatives to cultivate digital access, skills and proficiencies across population segments need to be undertaken.

This study integrates trust and digital literacy within the theoretical model to provide a more holistic understanding of adoption determinants. It highlights the need for balanced technology-enabled and social interventions to foster acceptance of e-government services.

In this paper, the authors examine the strategies used to reduce labour costs in three public hospitals in South Africa, which were effective and why. In the democratic era, after the revelations of large-scale corruption, the authors ask whether their case studies provide lessons for how public service institutions might re-make themselves, under circumstances of austerity.

A comparative qualitative case study approach, collecting data using a combination of interviews with managers, focus group discussions and interviews with shop stewards and staff was used.

Management in two hospitals relied on their financial power, divisions between unions and employees' loyalty. They lacked the insight to manage different actors, and their efforts to outsource services and draw on the Extended Public Works Program failed. They failed to support staff when working beyond their scope of practice, reducing employees' willingness to take on extra responsibilities. In the remaining hospital, while previous management had been removed due to protests by the unions, the new CEO provided stability and union–management relations were collaborative. Her legitimate power enabled unions and management to agree on appropriate cost cutting strategies.

Finding an appropriate balance between the new reality of reduced financial resources and the needs of staff and patients, requires competent unions and management, transparency and trust to develop legitimate power; managing in an authoritarian manner, without legitimate power, reduces organisational capacity. Ensuring a fair and orderly process to replace ineffective management is key, while South Africa grows cohorts of competent managers and builds managerial experience.

The study investigates the consumer’s attitude to using artificial intelligence (AI) devices in hospitality service settings considering social influence, hedonic motivation, anthropomorphism, effort expectancy, performance expectancy and emotions.

This study employed a quantitative methodology to collect data from Bangladeshi consumers who utilized AI-enabled technologies in the hospitality sector. A total of 343 data were collected using a purposive sampling method. The SmartPLS 4.0 software was used to determine the constructs' internal consistency, reliability and validity. This study also applied the partial least squares structural equation modeling (PLS-SEM) to test the research model and hypotheses.

The finding shows that consumer attitude toward AI is influenced by social influence, hedonic motivation, anthropomorphism, performance and effort expectancy and emotions. Specifically, hedonic motivation, social influence and anthropomorphism affect performance and effort expectations, affecting consumer emotion. Moreover, emotions ultimately influenced the perceptions of hotel customers' willingness to use AI devices.

This study provides a practical understanding of issues when adopting more stringent AI-enabled devices in the hospitality sector. Managers, practitioners and decision-makers will get helpful information discussed in this article.

This study investigates the perceptions of guests' attitudes toward the use of AI devices in hospitality services. This study emphasizes the cultural context of the hospitality industry in Bangladesh, but its findings may be reflected in other areas and regions.

This study aims to investigate the integration of heritage language and culture in technology-enhanced bilingual education and examine the dominance of the English language and culture in computer-assisted language learning settings.

This research used a narrative inquiry methodology. The data came from semi-structured interviews with 25 bilingual teachers in the Kurdistan region of Iraq and Texas.

The study found a significant bias in the use of technology toward the target language, often at the expense of heritage language and culture. The curricula analyzed were predominantly focused on superficial cultural elements of the target language, leading to a neglect of deeper cultural engagement.

This research highlights the phenomenon of cultural cringe within bilingual education and the skewed use of technology toward the target language.

The purpose of this study is to examine the impact of computer-assisted language learning on cultural adaptation and language learning in non-traditional classroom settings.

The data of this study came from extended periods of observation, multiple rounds of semi-structured interviews and home visits. Using narrative inquiry, it analyzes an immigrant's journey of language learning and cultural adaptation within a virtual knowledge community.

The findings of this study reveal the profound impact of virtual knowledge communities on enhancing second language learning and facilitating cultural adaptation.

This study offers original insights by demonstrating the transformative power of virtual knowledge communities for the purpose of second language acquisition and cultural adaptation.

Coronavirus disease (COVID-19) has challenged leadership in hospitals worldwide. The experiences of leadership during the pandemic changed leadership significantly. This study aims to describe nurse leaders’ perceptions of what future leadership in hospital settings in the post-pandemic era needs to be like.

A qualitative descriptive study was used. A total of 20 nurse leaders from the Finnish central hospital were interviewed from June to October 2021. The data were analysed using inductive content analysis.

The analysis revealed five main categories describing nurse leaders’ perceptions of future leadership in hospital settings in the post-pandemic era: digitalisation and hybrid working culture, development of sustainable working conditions, moving smoothly to the post-pandemic era, dissolution of traditional regimes of organisation and flexibility in leadership.

In the post-pandemic era, the constantly changing demands and challenges currently facing healthcare systems have significantly increased the complexity of hospital organisations. This requires critical evaluation and change to traditional leadership. Enhancing flexibility and authenticity in leadership, strengthening competencies, implementing a wide range of digital resources and increasing the appeal of the nursing profession to build the next generation of nurses – all of these are needed to provide sustainability in future healthcare.

The results identify the critical points of leadership that need to be developed for future challenges and for maintaining a sufficient supply of qualified professionals. Acting on this information will enhance flexibility in organisations and lead to acceleration of changes and the development of new kinds of leadership in the future