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This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private and foreign sector banks.

The Reserve Bank of India's database on the Indian economy is used to retrieve data over 13 years (2008–2021). Public sector (12), private sector (22) and foreign sector (44) banks are represented in the sample. Two-way ANOVA, multiple regression and panel regression statistical techniques are used in SPSS and EViews to examine the data. Further, the results are also validated by using robustness testing by applying the fully modified ordinary least square (FMOLS) and dynamic least square (DOLS) regression.

The results showed that, for private and foreign banks, the non-priority sector makes up the majority of the total gross non-performing assets, although both the priority and non-priority sectors are substantial for public sector banks. The largest contributors to the total gross non-performing assets in public, private and foreign banks are industries, agriculture and micro and small businesses. The FMOLS displays robustness results that are qualitatively similar to the baseline result.

Based on the study's findings about the patterns of non-performing assets originating from these specific industries, banks might improve the way in which these advanced loans are managed.

There has not been much research done on the subject of sub-sector-specific non-performing assets and how they affect total gross non-performing assets across the three sector banks. The study's primary focus will be on the issue of non-performing assets in the priority’s and non-priority’s sub-sectors, namely, agricultural, micro and small businesses, food credit, industries, services, retail loans and other priority and non-priority sectors.

This paper aims to explore and analyse stakeholders’ perceptions of the development priorities and suggests more effective strategies to assist sustainable economic growth in the United Arab Emirates (UAE).

The authors use the World Bank data set, which collects various stakeholders’ opinions on the UAE development. First, the exploratory factor analysis has been applied to detect the main groups of development priorities. Second, the fuzzy cluster analysis has been conducted to detect the groups of stakeholders with different attitudes towards the importance of extracted groups of priorities. Third, clusters have been compared according to demographics, media usage and shared prosperity goals.

The two main groups of development priorities have been extracted by the exploratory factor analysis: economic priorities and sustainability priorities. Four clusters have been detected according to the level of motivation when it comes to the economic and sustainability priorities: Cluster 1 (High economic – High sustainability), Cluster 2 (High economic – Medium sustainability), Cluster 3 (High economic – Low sustainability) and Cluster 4 (Low economic – Low sustainability). Members of the cluster that prefer a high level of economic and sustainability priorities (Cluster 1) also prefer more diversified economic growth providing better employment opportunities and better education and training for young people in the UAE.

Limitations stem from the survey being conducted on a relatively small sample using the data collected by the World Bank; however, this data set allowed a comparison of various stakeholders. Future research should consider a broader sample approach, e.g. exploring and comparing all of the Gulf Cooperation Council (GCC) countries; investigating the opinions of the expatriate managers living in the UAE that are not from GCC countries; and/or including other various groups that are lagging, such as female entrepreneurs.

Several practical implications were identified regarding education and media coverage. Since respondents prioritize the economic development factors over sustainability factors, a media campaign could be developed and executed to increase sustainability awareness. A campaign could target especially male citizens since the analysis indicates that males are more likely to affirm high economic and low sustainability priorities than females. There is no need for further diversification of media campaigns according to age since the analysis did not reveal relevant differences in age groups, implying there is no inter-generational gap between respondents.

This paper contributes to the literature by comparing the perceived importance of various development goals in the UAE, such as development priorities and shared prosperity indicators. The fuzzy cluster analysis has been used as a novel approach to detect the relevant groups of stakeholders in the UAE and their developmental priorities. The issue of media usage and demographic characteristics in this context has also been discussed.

The main research attempts guiding questions about management research agendas had been relevance questions versus rigor questions. Researchers have also attempted to set management research agendas in particular sectors. To the best of the authors’ knowledge, no research, however, has addressed the infrastructural and foundational questions of what moral priorities and ethical principles should guide the future development of management research. Because the Islamic theological approach is a “transcendental values integration” approach, it presents a potentially viable source of reference particularly for scholars interested in ethical philosophical paradigmatic approaches. Islamic literature has presented guiding principles as to how to balance priorities through the Jurisprudence of Priorities (Fiqh Al-Awlawiyyat). The purpose of this exploratory conceptual paper is to synchronize the Islamic background literature on the jurisprudence of priorities with management research development and agendas. The research is exploratory in nature.

The paper is conceptual, merging Islamic literature with management research for the development of a framework to potentially guide management researchers in prioritizing their research agendas.

The research resulted in the conceptualization of a framework aiding researchers in the prioritization of their research agendas.

The research has implications for management scholars who are interested to prioritize their research projects and agendas. The research presents a schematic diagram and guiding framework through which scholars can reflect on their choice of research topics.

The research is also relevant to funding agencies as they devise the funding priorities in the management field.

This paper addresses the unique and foundational question of what moral priorities and ethical principles should guide the future development of management research. The authors build on a religious-philosophical approach, drawing on the Islamic jurisprudence of priorities as a literature base. The authors, therefore, address the key principles of responsible research regarding how it can be relevant on the infrastructural level to society and how the benefit to key stakeholders should be tackled. To the authors’ knowledge, this was not done in previous literature.

This chapter demonstrates that social business models do not meaningfully prioritize or impose accountability to “social good” over other purposes in ways that (a) best protect against owners changing their minds or entry of new owners with different priorities and (b) enable reliable accountability over time and across circumstances. This chapter further suggests a model – a “social primacy company” – that actually prioritizes “social good” and meaningful accountability to it. This chapter thus clarifies circumstances under which existing models might be most useful and are not particularly useful, especially as investors, entrepreneurs, employees, regulators, and others pursue shared, common understandings about purposes, priorities, and accountability.

Technology and market pressures are encouraging localized and small-series production in customer-driven industries. The purpose of this paper is to explore and understand the supply chain-, product- and process-design factors for small-series production in EU’s textile and apparel industry, to understand configuration decisions, priorities and challenges.

An interview study was undertaken with ten companies that represent diverse small-series production models and value chain roles. Interview data was analysed to identify supply network configuration characteristics, decision priorities and challenges.

Three small-series production models emerged from the analysis, differing with respect to adoption of process postponement and customization. The findings confirm and extend past research regarding diverse decision priorities and product, process, supply chain structure/relationship configurations. Challenges identified relate to planning (priorities) and implementation (configuration). Whereas competence availability and digital technology challenges are common, several difficulties are linked to production model like tensions related to priorities and small volumes, which are not found with customization.

Future research can make comparisons with other industry and location contexts; adopt dynamic approaches to distinguish between design and reconfiguration processes; and address indicated paradoxical-tensions.

The study findings can provide guidance for companies regarding identification of priorities and management of (planning/implementation) challenges impacting small-series production in T&A.

The paper brings a configuration perspective at the supply chain level to the problem of small-series production implementation, which demands holistic and context-specific understanding.

This paper aims to develop predictive methods, based on recurrent neural networks, useful to support facility managers in building maintenance tasks, by collecting information coming from a computerized maintenance management system (CMMS).

This study applies data-driven and text-mining approaches to a CMMS data set comprising more than 14,500 end-users’ requests for corrective maintenance actions, collected over 14 months. Unidirectional long short-term memory (LSTM) and bidirectional LSTM (Bi-LSTM) recurrent neural networks are trained to predict the priority of each maintenance request and the related technical staff assignment. The data set is also used to depict an overview of corrective maintenance needs and related performances and to verify the most relevant elements in the building and how the current facility management (FM) relates to the requests.

The study shows that LSTM and Bi-LSTM recurrent neural networks can properly recognize the words contained in the requests, thus correctly and automatically assigning the priority and predicting the technical staff to assign for each end-user’s maintenance request. The obtained global accuracy is very high, reaching 93.3% for priority identification and 96.7% for technical staff assignment. Results also show the main critical building elements for maintenance requests and the related intervention timings.

This work shows that LSTM and Bi-LSTM recurrent neural networks can automate the assignment process of end-users’ maintenance requests if trained with historical CMMS data. Results are promising; however, the trained LSTM and Bi-LSTM RNN can be applied only to different hospitals adopting similar categorization.

The data-driven and text-mining approaches can be integrated into the CMMS to support corrective maintenance management by facilities management contractors, i.e. to properly and timely identify the actions to be carried out and the technical staff to assign.

The improvement of the maintenance of the health-care system is a key component of improving health service delivery. This work shows how to reduce health-care service interruptions due to maintenance needs through machine learning methods.

This study develops original methods and tools easily integrable into IT workflow systems (i.e. CMMS) in the FM field.

This study examines the propensity to innovate in automation of family firms (FFs) based on the socio-emotional wealth (SEW) perspective.

This study’s analysis is based on three aspects. First, the authors consider three main non-economic goals and priorities of FFs: the family’s relationship with employees (read as to care for their satisfaction and well-being); the inner pride of building and maintaining the family and firm image and reputation; and the inner feeling to be socially responsible. Second, the authors consider how these goals and priorities vary among FFs according to four dimensions: family ownership, the presence of family members on the board of directors, the involvement of young successors, and the presence of founding and later generations. Finally, the consequences of automation are considered: lower firm employment, lower employees’ satisfaction and well-being, and higher firm productivity. The analysis is based on a sample of 4,150 Italian firms.

The analysis revealed that FFs are less prone to innovate in automation than non-FFs. Specifically, family ownership, the presence of family members on the board of directors, and the presence of founding generation are negatively associated with innovation in automation. Instead, the involvement of young successors and the presence of later generation are positively associated with innovation in automation.

To the authors’ knowledge, this study is the first investigation that, based on SEW, examines how FFs act on the decision to innovate in automation, thereby providing empirical evidence.

“Integrated care” (IC) is an approach to health and social care delivery that aims to prevent problems arising from fragmented care systems. The collective content of the IC literature, whilst valuable, has become extensive and wide-ranging to such a degree that knowing what is most important in IC is a challenge. This study aims to address this issue.

A scoping review was conducted using Arksey and O'Malley's framework to determine IC priority areas.

Twenty-one papers relevant to the research question were identified. These included studies from many geographical regions, encompassing several study designs and a range of populations and sample sizes. The findings identified four priority areas that should be considered when designing and implementing IC models: (1) communication, (2) coordination, collaboration and cooperation (CCC), (3) responsibility and accountability and (4) a population approach. Multiple elements were identified within these priorities, all of which are important to ensuring successful and sustained integration of care. These included education, efficiency, patient centredness, safety, trust and time.

The study's findings bring clarity and definition to what has become an increasingly extensive and wide-ranging body of work on the topic of IC. Future research should evaluate the implementation of these priorities in care settings.

This research priority setting partnership (PSP) aims to collaboratively identify the “top ten” research priorities relating to communication and swallowing for children and adults with learning disabilities, across the lifespan in the UK, using a modified James Lind Alliance approach.

A steering group and reference group were established to oversee the PSP. A survey of speech and language therapists (SLTs) resulted in 157 research suggestions. These were further developed into 95 research questions through a multi-stakeholder workshop. Questions were prioritised via an online card-sort activity completed by SLTs, health-care or education professionals and carers. Research questions were analysed thematically. Ten adults with learning disabilities were supported to assign ratings to themes reflecting their prioritisation. The top ten research priorities were identified by combining results from these activities.

The top ten research priorities related to intervention, outcome measurement and service delivery around communication and dysphagia.

To the best of the authors’ knowledge, this is the first UK-wide research PSP on learning disabilities and speech and language therapy across the lifespan. It uses a novel approach to incorporate the preferences of people with learning disabilities in the prioritisation.

Halal integrity assurance is the primary objective of Halal supply chain management. Several halal-related risks are present that have the potential to breach halal integrity. Therefore, this study aims to develop the framework for the assessment of halal-related risk from a supply chain perspective.

Risk related to halal is identified through the combined approach of the systematic literature review and experts’ input. Further, these risks are assessed using the integrated approach of intuitionistic fuzzy number (IFN) and D-number based on their severity score. This integrated approach can handle fuzziness, inconsistency and incomplete information that are present in the expert’s input.

Eighteen significant risks related to halal are identified and grouped into four categories. These risks are further prioritised based on their severity score and classified as “high priority risk” or “low priority risks”. The findings of the study suggests that raw material status, processing methods, the wholesomeness of raw materials and common facilities for halal and non-halal products are more severe risks.

This study only focusses on halal-related risks and does not capture the other types of risks occurring in the supply chain. Risks related to halal supply chain management are not considered in this study. Prioritisation of the risks is based on the expert’s input which can be biased to the experts' background.

The proposed risk assessment framework is beneficial for risk managers to assess the halal related risks and develop their mitigation strategies accordingly. Furthermore, the prioritisation of the risks also assists managers in the optimal utilisation of resources to mitigate high-priority risks.

This study provides significant risks related to halal integrity, therefore helping in a better understanding of the halal supply chain. To the best of the authors' knowledge, this is the first comprehensive study for developing a risk assessment model for the halal supply chain.