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A region’s transforming care partnership identified that autistic adults without an intellectual disability (ID) may be falling through gaps in services when presenting with a significant emotional and/or behavioural need in the absence of a mental health diagnosis. The region’s intensive support teams (ISTs) for adults with ID therefore piloted a short-term “behavioural support service” for this population. The purpose of this paper is to evaluate this pilot.

This study represents a mixed-methods service evaluation over a four year pilot period. The quantitative component examined referral rates and demographic data of accepted and declined referrals; and length of referral episodes and Health of The Nation Outcomes Scores (HoNOS) for accepted referrals. The qualitative component used thematic analysis to identify key themes relating to reasons for referral, clinical/therapeutic needs, and the models of support that most informed assessments and interventions at individual and systems levels.

The ISTs accepted 30 referrals and declined 53. Most accepted referrals were male (83%), and under 24 years old (57%). Average HoNOS scores were above the thresholds generally associated with hospital admission. Key qualitative themes were: transitional support; sexual risks/vulnerabilities; physical aggression; domestic violence; and attachment, trauma and personality difficulties. Support mostly followed psychotherapeutic modalities couched in trauma, attachment and second- and third-wave cognitive behavioural therapies. Positive Behaviour Support (PBS) did not emerge as a model of preference for service users or professionals.

This project represents one of the first of this type for autistic adults without an ID in the UK. It provides recommendations for future service development and research, with implications for Transforming Care policy and guidance.

This study aims to address three research questions pertaining to climate neutrality within the supply chain of metal and mining industry: (1) How can an organization implement practices related to climate neutrality in the supply chain? (2) How do members of the supply chain adopt different measures and essential processes to assist an organization in responding to climate change-related concerns? (3) How can the SAP-LAP framework assist in analyzing and proposing solutions to attain climate neutrality?

To address the proposed research questions concerning climate neutrality, this study employs a case study approach utilizing the SAP-LAP (situation, actor, process–learning, action, performance) framework. Within the SAP-LAP framework, adopting a natural resource-based perspective, the study thoroughly examines the intricacies and interactions among existing situations, pertinent actors and processes that impact climate initiatives within a metal and mining company.

The study's findings suggest that organizations can achieve the objective of climate neutrality by prioritizing resources and capabilities that lead to reduced GHG emissions, lower energy consumption and optimal resource utilization. The study further proposes key elements that significantly influence the pursuit of climate neutrality within enterprises.

This study is one of the earliest contributions to the development of a holistic understanding of climate neutrality in the supply chain of the metal and mining industry.

The study will assist practitioners and policymakers in comprehending the present circumstances, actors and processes involved in enterprises' supply networks in order to attain climate neutrality in supply chains, as well as in taking the right steps to enhance performance.

This study presents a climate neutrality model and provides valuable insights into emission management, contributing to the achievement of the climate neutrality objective.

In an era where complex technological advances increasingly govern service delivery, it is incumbent on service firms to pioneer innovative strategies to sustain customer engagement and cultivate loyalty. This conceptual paper examines the transformative potential of artificial intelligence (AI) in the realm of online customer communities, with a particular focus on its creation, management and enhancement facets. The authors explore how AI can revolutionize the dynamics of customer interaction, feedback mechanisms and overall engagement within the service industry.

This conceptual paper draws from marketing and management literature focusing on customer communities and AI in service and customer engagement contexts with a robust future research agenda.

A classification of online customer community engagement is provided along with a conceptual framework to guide our understanding of the integration of AI into online customer communities.

This exploration underscores the imperative for service firms to embrace AI-driven approaches to online customer community management, not only as a means to optimize their operations but as a vital strategy to stay competitive in the ever-evolving digital landscape. This paper examines the novel combination of AI with online customer communities and provides the framework in the form of an input-process-output (IPO) model for future research into this integration.

World Health Organizations (WHO) (2023) states that governments and employers have a responsibility to uphold that right by providing work that simultaneously prevents workers from experiencing excessive stress and mental health risks. The business environment continues to produce a lot of stress on workers, which includes internal pressures to achieve results and employees suffer the consequences. Some companies have turned to mindfulness as a technique that helps mitigate these consequences and have joined Kaizen as a process improvement technique in the work environment. Therefore, this study has a research purpose: “to comprehend the possible linkage between Kaizen philosophy from an individual perspective, with Mindfulness ZEN Buddhism technique to understand the individual benefit (well-being) of each employee in organizations.” The answer to this represents the research gap in this article. The research questions governing this study are as follows: RQ1: Does Mindfulness is used as Kaizen technique of personal-individual improvement in 21st-century organizations? RQ2: What elements and characteristics of Kaizen and mindfulness can be found working together? And RQ3: Which qualitative impact of mindfulness and Kaizen in the workplace outcome (well-being, performance of the job (process)) and relationships with other employees)?

This research used a qualitative approach due to the recent phenomenon studied. In a certain way, it was used a mixed-method (combination of qualitative data – web search secondary data analysis and qualitative research-Convergence Model). First, it was done an intensive web search with the aim to identify companies' corporate mindfulness programs, along with companies which have applied mindfulness and Kaizen programs. It was identified a group of big companies with global and international presence (“famous” for their products and services) in diverse industrial and service sectors, country of origin and business locations; with the purpose of getting a holistic vision of all organizations which have practice Kaizen and mindfulness. Therefore, this study explored secondary data related to both practices, analyzing reports or briefings published in management magazines and official WEB pages and/or business magazines.

As a result of the triangulation of the data with its secondary data convergence model and qualitative research, a theoretical framework was reached that shows the benefits of the two combined twin techniques of Kaizen and mindfulness. The worker experiences a path that goes from concentrating on the execution of their processes, following their operating standards (Standardize, Do, Check, Act [SDCA] cycle), going through the evolution to continuous improvement or Plan-Do-Check-Act (PDCA) cycle, experiencing work with concentration-awareness and reducing your daily stress, maintaining high sensitivity to the work process and your environment and finally, discovering an essential life purpose. Finally, worker experiences benefit when there is wide application of both with the SDCA and PDCA cycles such as high motivation, constant learning from your mistakes, day-to-day learning and the Munen Musso (not using the mind).

The main limitation is the qualitative methodological bias and secondary data research. In addition, to have a theoretical sample. However, the richness of the data helps to overcome this limitation. On the other hand, the qualitative research interviews are for a certain geographical area, therefore, the results cannot be generalized.

The results of this research can shed light on operations managers in the use of techniques for continuous improvement and improvement of people's quality of life, such as mindfulness. In Mexico, they are beginning to be used jointly (twin techniques) to comply with Regulation 035 of psychosocial risk, the researchers are sure that in other countries it will be used in the same way to comply with regulations. However, the research findings show the benefits that can be provided to workers in organizations by applying Kaizen and Mindfulness together.

To the best of the authors’ knowledge, according to the literature review, this is the first article that explores the relationship between Kaizen and Mindfulness as twin techniques that help improve the individual quality of life of employees in organizations.

This paper aims to identify the key issues that healthcare knowledge-intensive organizations (KIPOs) should focus on to define themselves as socioenvironmentally and governance responsible for integrating environmental, social, and governance (ESG) logic into their business strategy. At the same time, this provides an understanding of how healthcare KIPOs contribute to achieving the Sustainable Development Goals of the 2030 Agenda.

Taking a cue from the model developed by the World Economic Forum, an “ESG Processing Map” was constructed to identify qualitative disclosures that a healthcare company should consider when implementing sustainability logic. The aspects investigated were processed, considering national and international standards, frameworks and disclosures. The social network analysis technique was used to systemize and combine the outcomes of these processes and analyze their consistency with sustainable development.

Through the “ESG Processing Map,” 13 areas of action and 27 topics specific to the health sector were defined on which to intervene in sustainability in order to concretely help HCOs to place specific corrective and improvement actions over time concerning socioenvironmental and governance aspects.

The paper provides contribute, on the one hand, to enriching and updating the academic literature on ESG logic in a still underexplored field and, on the other hand, to provide these types of organizations with a “compass” to guide and orient their business strategies towards sustainability.

The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

The lean startup approach (LSA) is extensively utilized by early-stage entrepreneurs, with “pivot” serving as a key pillar. However, there is a research gap concerning the boundary conditions impacting LSA and pivot decisions, especially when addressing societal challenges, as in the context of transformational entrepreneurship. In this regard, the healthcare sector, further compounded by a lack of research on startups and scale-ups, presents an embraced opportunity to provide multiple contributions for both theory and practice.

The present investigation employs a grounded approach to explore the experiences of the co-founders of a fast-growing Italian e-health startup. A narrative strategy was employed to organize conditions and evolving strategic action/interactions into three different pivoting phases of the startup – before the pivot, its enactment and aftermath – with primary and secondary data collected over a period of one year.

Pivoting in digital healthcare unfolded as a liminal experience marked by factors such as high regulation, multiple stakeholders, technological and symbolic ambivalence, resource-intensive demands and institutional actors acting as pathway pioneers, leading to an information overload and unforeseeable uncertainty to manage. These factors challenge entrepreneurs' ability to attain optimal distinctiveness, presenting the paradoxical need for vertical flexibility for scaling up.

By uniquely illuminating the sector’s constraints on entrepreneurial phenomena, this study provides a valuable guide for entrepreneurs and institutional actors in addressing societal challenges.

This study introduces a process model of transformational information crafting when pivoting, highlighting the role of entrepreneurs' transformational stance and platform-mediated solutions as engines behind strategies involving information breaking and transition, preceding knowledge-driven integration strategies.

Quality management practices (QMP) have stood as one of the critical strategic differentiators for enhancing firm performance. The production and manufacturing industry is the main driving force of economic growth and social development for any developed or developing country. This study aims to focus on two primary dimensions of QMP: soft quality management practices (SQMP) and hard quality management practices (HQMP) from the socio-technical system perspectives. Based on institutional theory perspectives, the study explores the impact of SQMP and HQMP on quality performance (QP), innovation performance (IVP) and financial performance (FP) in Indian oil processing organizations.

A proposed research model is validated using 289 cross-sectional survey data collected from the senior officials of oil processing firms in India. Covariance-based structural equation modeling is used to verify the proposed theoretical model.

SQMP, directly and indirectly, influenced QP and IVP while only indirectly to FP mediated through QP. HQMP directly impacted only QP while indirectly to IVP and FP mediated through QP.

Impact of organizational legitimacy in proper utilization or application of QMP in achieving the firm sustainable growth. The future study may address the following Research Question (RQ) also: How do QMP enhance the legitimacy of organizations operating in the oil processing industries? Are there specific mechanisms or pathways through which improved performance contributes to enhanced organizational legitimacy? How does legitimacy impact the success and sustainability of organizations, particularly, within the context of the oil processing industries? Are there regulatory requirements or industry certifications that organizations must adhere to in order to maintain legitimacy?

Similarly, manufacturing firms establish QMP of interaction and maintaining relationships with all the stakeholders, total employee empowerment and involvement, workforce commitment and workforce management, helping to control their reputations and maintain legitimacy (Li et al., 2023). Similarly, in the health industry, the health management information system (HMIS), which uses the DHIS2 platform, establishes that isomorphism legitimizes data QMP among health practitioners and, subsequently, data quality. Further, it was concluded that mimetic isomorphism led to moral and pragmatic legitimacy. In contrast, normative isomorphism led to cognitive legitimacy within the HMIS structure and helped to attain the correctness and timeliness of the data and reports, respectively (Msendema et al., 2023). Quality, flexibility and efficiency of Big Data Analytics through better storage, speed and significance can optimize the operational performance of a manufacturing firm (Verma et al., 2023).

The study provides the academician with the different dimensions of QMP. The study demonstrates how a firm develops multiple performance capabilities through proper QMP. Also, it shows how vital behavioral and managerial perspectives are to QMP and statistically solid tools and techniques. The study draws their importance to risk factors involved in the firms. Since the SQMP play a vital role, thus, emphasis on the behavioral dimension of quality requires more investigation and is in line with hard technological advancements in the quality field.

The study of the impact of HQMP and SQMP on performance is still not established. There are inconsistencies in the findings. The study of the impact of HQMP and SQMP in oil processing industries has not dealt with before. The effects of HQMP and SQMP on the firm’s FP have least been dealt. In context to the intended influence of QM implementation, QP has not been examined as a potential mediator between FP. Research carried out in the past is limited to American and European countries. However, a limited study was done in Asia, and no study has been conducted in the Indian context.

This study aims to analyze a conspicuous corpus of literature related to the field of technology-based intensive care research and to develop an architecture model of the future smart intensive care unit (ICU).

Papers related to the topics of electronic health record (EHR), big data, data flow and clinical decision support in ICUs were investigated. These concepts have been analyzed in combination with secondary use of data, prediction models, data standardization and interoperability challenges. Based on the findings, an architecture model evaluated using MIMIC III is proposed.

Research identified issues regarding implementation of systems, data sources, interoperability, management of big data and free text produced in ICUs and lack of accuracy of prediction models. ICU should be treated as part of a greater system, able to intercommunicate with other entities.

The research examines the current needs of ICUs in interoperability and data management. As environment changes dynamically, continuous assessment and evaluation of the model with other ICU databases is required.

The proposed model improves ICUs interoperability in national health system, ICU staff intercommunication, remote access and decision support. Its modular approach ensures that ICUs can have their own particularities and specialisms while ICU functions provide ongoing expertise and training to upgrade its staff.

The microfinancing sector is infamous for being prone to high credit risks due to loan defaults by its poor borrowers. Conversely, the sector is also criticized for creating debt traps for the poor. The dual nature of these peculiar problems in microfinancing causes the market failure phenomenon. Therefore, the current study explores whether public policy intervention is required to address market failure.

The study undertakes a critical review of existing literature, the news, the policy documents and other publicly available information to shape the viewpoints in this study. Constructive criticism is used to build arguments to arrive at a conceptual framework that depicts how public policy should interact with markets to address the peculiar problems of the microfinancing sector.

The findings indicate that market failure in microfinancing is real and pressing. Therefore, public policy is invited, though in its limited form. While the policy intervention may help the formal microfinancing arena by regulating the interest rates, the policy administration in the informal sector is likely to fail. Therefore, the policy should attempt to create an environment of inclusiveness. Policies that rely on coercion are not recommended. In the long run, subsidies via policy intervention are discouraged. Instead, the policy should motivate the microfinancing sector to become self-reliant.

The study is one of its kind to provide perspectives on specific market failures and policy interventions in microfinancing, particularly in economies where formal and informal sectors coexist and are equally crucial.