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Organizational culture has been identified as an important factor in increased employee commitment. Particularly during a shortage of skilled workers, commitment is a meaningful indicator of higher loyalty and retention. However, limited research has studied the relationship between organizational culture and commitment from a global perspective. Most research focuses on specific aspects of culture and examines the aspects' effects on commitment separately. The author's objective is to identify influential organizational culture's dimensions and assess dimensions' relationship to commitment holistically.

For this purpose, the author analyzed a data set with 241,648 participants from 9 industries in Germany. The survey captures individual attitudes toward certain aspects of organizational culture and assesses workers' commitment to their organizations.

The results of a linear regression show that all cultural dimensions considered, namely transformational leadership behavior, team cohesion, compensation, fairness and caring attitude, if well-developed, positively and significantly influence organizational commitment. Interestingly, team cohesion has the greatest effect on commitment, followed by transformational leadership behavior, compensation, caring attitude and fairness.

This paper aims to examine the relationship between organizational culture and commitment holistically, thereby revealing which aspects of corporate culture are particularly important for increasing workers' commitment.

In parallel with technological developments, mobile devices have become an important part of our daily lives. Nowadays, people, particularly generation Z, actively engage with the Internet and mobile technologies, including smartphones. The new technologies have also made electronic learning (e-learning) and mobile learning (m-learning) tempting for learners in higher education. Despite the growing use of m-learning, particularly in developed countries, its utilization in higher education is still at its early stage and far from its potential. This study investigates the university students' acceptance of using m-learning with smartphones in a developing country context.

Quantitative data collected through conducting questionnaires with 405 higher education students in Turkey were analyzed with structural equation modelling.

The findings show that the acceptance of using m-learning is affected by several factors, including perceived enjoyment, complexity and facilitating conditions. The findings are particularly relevant in the current context, where the COVID-19 pandemic has pushed many higher education institutions to adapt m-learning systems to enhance student learning experiences.

This study's findings offer fresh and important insights that can be used by m-learning developers and educators for designing m-learning systems and using m-learning applications in enhancing students' experience and performance with m-learning.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0516.

Gender discrimination exists in various settings globally and harms women’s mental health. This study aims to understand the impact of gender discrimination on hopelessness and emotional vulnerability. Further, we attempted to determine whether benevolent childhood experiences (BCEs) moderate the relationships of gender discrimination with hopelessness and emotional vulnerability.

Data from 445 young women from India was gathered from a cross-sectional survey. Measures included gender discrimination inventory, Beck’s hopelessness inventory, emotional vulnerability scale and BCE scale.

Results yielded a significant positive association of gender discrimination with hopelessness and emotional vulnerability. BCEs were negatively related to hopelessness, emotional vulnerability and gender discrimination. Further, gender discrimination predicted increased feelings of hopelessness and emotional vulnerability. However, BCEs do not neutralize the effect of gender discrimination.

It is evident from this study that gender discrimination exists independent of socioeconomic class, domicile and educational qualification, taking a toll on women’s well-being and mental health. Incorporating attitudinal changes at the community and societal level in reducing gender norms responsible for negative outcomes will allow women to function to their full capacity and experience improved mental health.

The research on gender discrimination and its impact on women’s mental health is limited, especially exploring the role of BCEs. Previous studies have indicated that BCEs have protective roles in neutralizing adversities. However, the present study uniquely contributes to establishing the limited role of BCEs in the context of gender discrimination, though it contributes to mental health. The policy and psychosocial implications of the study are discussed.

This study aims to explore the influence of health-care service quality on customers’ perceived value, satisfaction, effectiveness and behavioural intention concerning district health centres (DHCs) in Hong Kong. This research also intends to assess customers’ perception of the subsidy scheme and its influence on the relationships amongst the aforementioned constructs.

The convenience and snowball sampling approaches were adopted, and the self-administered questionnaire was sent to 309 customers of DHCs.

Service quality attributes in terms of staffing and procedures positively increased customers’ perceived value and staffing, procedures and operations. Physical facilities positively promoted customers’ satisfaction, consequently improving DHCs’ effectiveness and behavioural intention. However, core treatments and services of DHCs did not impact customers’ perceived value and satisfaction. Furthermore, customers receiving subsidies exhibited a more positive perception than those without subsidies.

Health-care organisations are advised to strategically allocate resources (staffing, facilities and procedures and operations management) to optimise overall performance outcomes. DHC operators could reinforce the core services of DHCs and health-care voucher subsidies to local citizens so as to enhance the effectiveness of DHCs and behavioural intention of customers.

This study integrates the input–process–output approach in measuring the effectiveness of and customers’ behavioural intention towards newly established DHCs.

The scope of this study is to explore and summarize the pool of dimensions, models and measurement techniques of service quality used in healthcare services and to propose a comprehensive conceptual model for practitioners and researchers.

This research employs a comprehensive review of available literature by using multiple keywords on different electronic repositories using the recommendations of the PRISMA approach for the selection of articles. A critical analysis of available studies helped in compiling a list of core service quality dimensions in healthcare services.

This paper presents a comprehensive account of different dimensions and their measurement items used by various researchers to assess service quality in healthcare systems. Most of the researchers have used SERVQUAL model either in its original or modified form while the others have proposed and used totally different dimensions to assess the service quality in healthcare. Many dimensions are just an existing dimension of SERVQUAL that has undergone a name change while others are completely new. The dimensions used by many researchers have items drawn from more than one dimension of SERVQUAL model. The availability of so many dimensions and models adds to the confusion that researchers and practicing managers experience when determining the appropriate model to be used in their work. To mitigate this confusion, there is a need to develop a comprehensive model; the current work is an attempt to meet this need. Through our analysis, we identify four major service quality dimensions: clinical quality, infrastructural quality, relationship and managerial quality and propose a model named CIRMQUAL.

After exploring all available models in the domain of healthcare, this research presents the best possible areas to enhance the quality of healthcare services. It also enhances the research insights for academicians and working professionals by developing and proposing a comprehensive model for measuring healthcare service quality. The proposed model covers almost all of the service quality dimensions used by other researchers and will make the choice of dimensions/model easy for the future researchers/practitioners interested in measuring and improving the quality of services offered by their healthcare units. Such a comprehensive model has not been developed by any researcher thus far.

The purpose of this study is to capture patients' and employees' perception of quality of care in the Indian private hospitals and to find the possible perceptual gaps between both the groups.

Authors have referred to the Victorian patient satisfaction monitoring (VPSM) scale and studied the responses of 327 patients and 327 employees collected from six private Indian tertiary care hospitals. SPSS v26 software was used to conduct the data reliability test, descriptive analysis and Mann–Whitney U test.

Authors have found significant differences in perceptions of quality of care between the patients and employees in the Indian hospitals. Employees have high positive perceptions towards the provided medical care whereas the patients have less favourable perceptions for many quality indicators.

This study findings help the healthcare managers, practitioners and healthcare workers of the Indian hospitals to understand the perceptions of both the employees and the patients towards healthcare quality elements and help to reduce the existing perceptual gap in the process of providing quality healthcare services.

To the best of authors knowledge, this is one of the pioneering studies conducted in Indian healthcare industry to capture and compare the perceptions of both the employees' and the patients' perceptions of various quality of care elements. This study highlighted the existing perceptual gap between the employees and the patients on various healthcare quality elements and indicated the critical areas for improvement to provide high quality healthcare services.

Contextual to the recognition of the complex interplay between health and behavioral aspects, integrated behavioral health (IBH) has emerged. Although this model is becoming popular in the Western world, its presence in the global context is not promising. This paper aims to explore the need for IBH in India and address its barriers to implementation and possible solutions.

We analyzed the case of IBH and its potential implications for India using the current evidence base, authors' reflections and experience of implementing similar programs.

This paper identifies contextual factors, including increased instances of non-communicable diseases and psychosocial and cultural determinants of health, that necessitate the implementation of IBH programs in India. The key features of different IBH models and their applicability are outlined. The current status of IBH and potential challenges in implementation in India in terms of human resources and other factors are delineated. We also discuss the potential models for implementing IBH in India.

Integrating behavioral health in primary care is considered an effective and sustainable model to promote health and well-being across various target populations. Towards this end, this paper is the first to discuss the contextual factors of IBH in India. It is a significant addition to the knowledge base on IBH and its possible implementation barriers and strategies in low- and middle-income countries.

In Bangladesh (BD), delays in infrastructure are common. Many previous studies have explored the causes of infrastructure delays. However, this study investigated the causes of delays by taking responses from the stakeholders who are responsible for planning, design, funding, approval and implementation. There are few studies that have related infrastructure project delays to heterogeneity in stakeholders’ perceptions.

A structural equation (SE) model is developed with 350 normally distributed data points to understand the heterogeneity in stakeholders’ perceptions regarding delays in infrastructure projects in BD. Additionally, the relative importance index (RII) approach is used to assess the responses, validating the SE model.

The study finds that among the three latent variables, “Project itself related delay” has more influence on delays in infrastructure projects. Among the observed variables under the “project itself related delay” latent variable, “DPP approval process” has the most significance. From the heterogeneity analysis, the study found differences in responses among the stakeholders from “the Engineering Department,” “the Planning Office” and “the Construction Firm/Industry.” An important class of stakeholders believes that their stage is not being delayed and that other stages require attention.

The data sample is 350. More data can improve the accuracy of the findings. Most of the respondents are civil engineers (74%) and represent the owner of the project. Sample data from more stakeholders’ will enhance the accuracy of the result.

This study addresses the requirements of Bangladeshi project stakeholders and how their interactions cause delays in projects. Furthermore, the opinions of other stakeholders are taken into consideration when determining the specific factors of individual stakeholders that are causing delays. Practically, the distance between stakeholders should be reduced. A project manager can play a role in this regard. Initiatives should be taken on how to complete the project quickly by eliminating the requirements discussed among the stakeholders and bureaucratic complications. Instead of placing blame on one another, stakeholders should take the initiative to figure out how to work together to finish the project on schedule. The Planning Commission’s approval of the Development Project Proposal (DPP) and Revised Development Project Proposal (RDPP) should be obtained as soon as possible by owner stakeholders. In order to avoid frequently changing the DPP, owners should also exercise greater caution when choosing contractors. Contractor stakeholders should use efficient and proper manpower and equipment so that unexpected delays are not created during the execution of work. Since the role of the contractor stakeholder is the most important among the three types of stakeholders, the contractor should raise awareness and urge the owners to get the RDPP approved quickly.

The findings from the study can help mitigate delays in infrastructure projects in BD, taking into account the perceptions of various stakeholders.

This study aims to establish a comprehensive satisfaction analysis framework by mining online restaurant reviews, which can not only accurately reveal consumer satisfaction but also identify factors leading to dissatisfaction and further quantify improvement opportunity levels.

Adopting deep learning, Cross-Bidirectional Encoder Representations Transformers (BERT) model is developed to measure customer satisfaction. Furthermore, opinion mining technique is used to extract consumers’ opinions and obtain dissatisfaction factors. Furthermore, the opportunity algorithm is introduced to quantify attributes’ improvement opportunity levels. A total of 19,133 online reviews of 31 restaurants in Universal Beijing Resort are crawled to validate the framework.

Results demonstrate the superiority of Cross-BERT model compared to existing models such as sentiment lexicon-based model and Naïve Bayes. More importantly, after effectively unveiling customer dissatisfaction factors (e.g. long queuing time and taste salty), “Dish taste,” “Waiters’ attitude” and “Decoration” are identified as the three secondary attributes with the greatest improvement opportunities.

The proposed framework helps managers, especially in the restaurant industry, accurately understand customer satisfaction and reasons behind dissatisfaction, thereby generating efficient countermeasures. Especially, the improvement opportunity levels also benefit practitioners in efficiently allocating limited business resources.

This work contributes to hospitality and tourism literature by developing a comprehensive customer satisfaction analysis framework in the big data era. Moreover, to the best of the authors’ knowledge, this work is among the first to introduce opportunity algorithm to quantify service improvement benefits. The proposed Cross-BERT model also advances the methodological literature on measuring customer satisfaction.