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The purpose of the study is to propose a framework for fleet management and make suitable distribution solution choices in the food industry.

This study reviews the literature to examine food distribution criteria. These criteria are used in the analytic hierarchy process (AHP) assessment and combined with discrete events simulation in a structured framework, which is validated through an empirical study.

The empirical case results demonstrate that both the AHP and discrete events simulation converge toward the same solution in most cases.

This study contributes to the literature on distribution management and develops a framework that can both guide future research and aid logistics practitioners in analysing distribution decision-making systems in dynamic environments.

Technological development has been a cornerstone of any emerging economy in the past few years. Blockchain has emerged as a promising technology in the past few years, revolutionizing business dynamics. There is always a concern or hesitation during such novel technological innovation. This paper aims to investigate the blockchain technology (BCT) implementation and acceptance in the supply chain function domain.

The proposed model is based on the Technology Readiness Index (TRI) and extended theory of planned behavior (TPB). The responses were collected from information technology (IT) professionals working at management positions in various manufacturing industries. A total of 147 usable responses were collected for analyzing hypotheses using structural equation modeling.

As per the findings, perceived ease of use significantly impacts perceived usefulness and attitude toward technology acceptability. Perceived usefulness is significant to attitude toward use. Trust in technology has a significant impact on building up the attitude to use the technology.

The novelty of this work lies in gauging the acceptability of new ways and means of transacting among supply chain professionals and decision-makers. This study provides a broader perspective regarding reluctance and acceptance of the BCT in the developing country that may help the technologist to elucidate better for smooth adoption.

COVID-19 continues to spread, and cause increasing deaths. Physicians diagnose COVID-19 using not only real-time polymerase chain reaction but also the computed tomography (CT) and chest x-ray (CXR) modalities, depending on the stage of infection. However, with so many patients and so few doctors, it has become difficult to keep abreast of the disease. Deep learning models have been developed in order to assist in this respect, and vision transformers are currently state-of-the-art methods, but most techniques currently focus only on one modality (CXR).

This work aims to leverage the benefits of both CT and CXR to improve COVID-19 diagnosis. This paper studies the differences between using convolutional MobileNetV2, ViT DeiT and Swin Transformer models when training from scratch and pretraining on the MedNIST medical dataset rather than the ImageNet dataset of natural images. The comparison is made by reporting six performance metrics, the Scott–Knott Effect Size Difference, Wilcoxon statistical test and the Borda Count method. We also use the Grad-CAM algorithm to study the model's interpretability. Finally, the model's robustness is tested by evaluating it on Gaussian noised images.

Although pretrained MobileNetV2 was the best model in terms of performance, the best model in terms of performance, interpretability, and robustness to noise is the trained from scratch Swin Transformer using the CXR (accuracy = 93.21 per cent) and CT (accuracy = 94.14 per cent) modalities.

Models compared are pretrained on MedNIST and leverage both the CT and CXR modalities.

The purpose of this study is to examine Indian language journals published in Arts, Humanities and Social Sciences (AHSS) included in the UGC-CARE list, which is an initiative of the University Grants Commission (UGC) of India. This study argues that although these journals do not appear in international databases, they are valuable because they frequently publish and have published for years, opinions, memoirs and critical review articles, especially the local culture.

This study examines 298 journals categorised into two groups: monolingual (189) and multilingual (109). The first group included 189 journals published in 15 Indian languages. Monolingual journals were examined using five criteria: year of publication, subject area, frequency, language and geographical zone of the publisher. Multilingual journals analysed as per languages covered.

The analysis reveals that the UGC-CARE List includes journals published between 1899 and 2019. The most common languages are Hindi (67), Urdu (31), Sanskrit (9) and Marathi (26). The frequency of majority (114) of journals is quarterly. Associations, universities, individual publishers and learned societies as publishers are dominant. Analysis of multilingual journals indicated that the highest number of journals (34) are published in English and Hindi.

Journals that fulfil the stringer criteria of three UGC-CARE journal analysis protocols find a place in the CARE List. The list is dynamic and is updated quarterly to maintain its currency and therefore its credibility. The list is available at http://ugccare.unipune.ac.in and is the list preferred by Indian Higher Education Institutes.

UGC-CARE List includes journals published by Indian publishers especially in the fields of Arts, Humanities and Social Sciences. It is the first initiative to battle against the predatory journals and effort to bring the Indian legacy of journals on the world map of journals and periodicals.

The advent of the COVID-19 pandemic brought various and radical changes at the worldwide level. Globally, severe preventive measures were imposed to respond to the crisis such as lockdowns which forced the people to quarantine themselves inside their houses for longer periods. This issue stressed the crucial role of healthy houses in providing the various needs of residents during crises.

This study methodology adopted both inductive approach and a Study Application Model to define the Healthy House Criteria and fulfill the study objectives. Under the inductive approach a holistic literature review was undertaken while the Study Application Model implied defining the conception of the overall Criteria of the Healthy House's interior design under the COVID-19.

The finding of the study showed some areas needed to improve current healthy house's criteria in terms of its interior design that may be used to cope with potential crises such as the COVID-19. Based on the revealed findings, the researcher suggested a conceptual framework for healthy house's criteria and further research areas.

The current research may provide applicable framework for both interior designers and households in terms of how to design and implement a healthy house, which is valid to accommodate residents during potential crises such as the COVID-19.

This article aims to (1) increase the knowledge of how coworkers experience voicing the organization on external social media and (2) deepen and nuance the knowledge of the sources of voice control involved in such communication processes. The study helps understand coworker voicing on social media as situated identity expressions through which coworkers negotiate and contest the organizational identity, thereby co-constituting a polyphonic organization.

The study draws upon a constitutive perspective on communication and a communication-centered perspective on identity and organizational identification to investigate the voicing of organizational members of the Swedish Police Force on social media. The article is based on a qualitative study where interviews with police officers and communication professionals at the Swedish Police Authority constitute the main empirical material. A content analysis of selected social media accounts provided important background information to the interviews and enriched the understanding of coworker voice.

This analysis shows that coworkers voice the organization differently. Furthermore, the study of how coworkers experience this voicing indicates that these variations in how coworkers voice the organization depend on how strongly they identify or disidentify with organizational identity and image expressions voiced by significant others. Based on the analysis, this study presents four voice positions highlighting coworkers' varying degrees of identification/disidentification when voicing their organization on social media and reflecting upon their experiences of voicing. Furthermore, the analysis also demonstrates four sources of voice control: (1) management, (2) colleagues, (3) significant non-members and (4) the status and position of the coworker's voice. These four sources of voice control influence coworkers' voices on social media.

This study also contributes with practical implications, for example that the traditional idea of monophonic organizations must be revised and also embrace a polyphonic, bottom-up approach to strengthening internal trust and organizational identity. This comes naturally with the price of less control and predictability by management but with the benefits of increased coworker engagement and pride.

This study contributes new knowledge and a nuanced understanding of coworker voice on social media and the sources of control that influence coworkers' voices.

Since the idea of “Unethical Pro-organisational Behaviour” (UPB) was introduced in 2010, a substantial corpus of empirical research has contributed to its expanding, contemporary knowledge. This includes research studies on how leadership exerts an influence on UPB. This paper aims to consolidate the current understanding of organisational leadership’s impact on employee UPB and offer future research agendas.

A systematic literature review (SLR) using the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines was adopted for the study. Literature that satisfied the search conditions was examined. The factors determining leadership’s influence on UPB were studied, and the findings were thematically synthesised.

Leader behaviour plays a large part in influencing UPB in organisations. Leader-member exchange and organisational belonging create favourable circumstances for UPB in organisations. UPB is moderated by the employee’s personal moral orientation.

UPB is unethical behaviour that benefits the organisation and is likely to be rewarded. However, there is a cost that other stakeholders pay. UPB has been researched since 2010, as well as the role of leaders in perpetuating UPB. However, there has not been an SLR of this study. This paper seeks to capture the essence of the research so far and pave a path for future research on the subject. These insights would prove valuable to management practitioners and academic experts.

This study aims to understand and a lay a foundation of how analytics has been used in depression management, this study conducts a systematic literature review using two techniques – text mining and manual review. The proposed methodology would aid researchers in identifying key concepts and research gaps, which in turn, will help them to establish the theoretical background supporting their empirical research objective.

This paper explores a hybrid methodology for literature review (HMLR), using text mining prior to systematic manual review.

The proposed rapid methodology is an effective tool to automate and speed up the process required to identify key and emerging concepts and research gaps in any specific research domain while conducting a systematic literature review. It assists in populating a research knowledge graph that does not reach all semantic depths of the examined domain yet provides some science-specific structure.

This study presents a new methodology for conducting a literature review for empirical research articles. This study has explored an “HMLR” that combines text mining and manual systematic literature review. Depending on the purpose of the research, these two techniques can be used in tandem to undertake a comprehensive literature review, by combining pieces of complex textual data together and revealing areas where research might be lacking.

Cost overrun in infrastructure projects is a constant concern, with a need for a proper solution. The current estimation practice needs improvement to reduce cost overruns. This study aimed to find possible statistical modelling techniques that could be used to develop cost models to produce more reliable cost estimates.

A bibliographic literature review was conducted using a two-stage selection method to compile the relevant publications from Scopus. Then, Visualisation of Similarities (VOS)-Viewer was used to develop the visualisation maps for co-occurrence keyword analysis and yearly trends in research topics.

The study found seven primary techniques used as cost models in construction projects: regression analysis (RA), artificial neural network (ANN), case-based reasoning (CBR), fuzzy logic, Monte-Carlo simulation (MCS), support vector machine (SVM) and reference class forecasting (RCF). RA, ANN and CBR were the most researched techniques. Furthermore, it was observed that the model's performance could be improved by combining two or more techniques into one model.

The research was limited to the findings from the bibliometric literature review.

The findings provided an assessment of statistical techniques that the industry can adopt to improve the traditional estimation practice of infrastructure projects.

This study mapped the research carried out on cost-modelling techniques and analysed the trends. It also reviewed the performance of the models developed for infrastructure projects. The findings could be used to further research to develop more reliable cost models using statistical modelling techniques with better performance.

Many studies have explored the relationship between green human resource management practices (GHRM) and employees’ green creative behavior (EGCB) within the hospitality industry. However, most prior studies have relied primarily on mono-method approaches, thereby limiting the depth of understanding about the underlying mechanism through which GHRM impacts employee behavior. The authors, in this paper, aim to argue that the connection between GHRM cannot be universal, and some individual factors will act as boundary conditions between these relationships. The authors employ a mixed-methods research design to address this gap to identify potential boundary conditions.

The authors adopted a two-phase approach, integrating qualitative (study 1) and quantitative (study 2) methodologies. Through qualitative research, the authors uncover valuable insights and construct a framework that is subsequently tested in the quantitative phase.

The findings suggest that the strength of the GHRM-EGCB relationship is contingent on the level of Environmental Specific Psychological Empowerment (ESPE) among employees. Employees with a higher degree of ESPE exhibit a stronger connection between GHRM perceptions and EGCB. Furthermore, the authors identify employees’ altruistic values (EAV) as an important moderator, indicating that the intervening effect of ESPE on the GHRM-EGCB relationship is particularly pronounced among employees with high levels of altruism.

By unmasking the complexity through a mixed-methods design, this study contributes to the existing literature by providing a more nuanced understanding of the mechanism between GHRM and green creative behavior.