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Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

The purpose of this study is to develop a model for investigating the sharing of harmful messages by employees using social media using the conspiracy theory from a socio-legal perspective. This study also examines the moderating role of different demographic parameters such as age, gender and education toward sharing harmful messages using social media.

Using the conspiracy theory and social impact theory as the foundation of this study, the authors developed theoretical model and validated it using the structural equation modeling technique with 342 participants from various organizations across Europe and Asia. The study also used different statistical measures to understand the demographic impacts toward sharing harmful messages.

It was found that epistemic, existential and social motives significantly and positively influence employees’ inappropriate message-sharing and seeking behavior, which in turn influences them to share harmful messages on social media. The study also indicates that there are some moderating impacts of employee demography toward sharing harmful messages using social media platforms.

This study investigates the antecedents of sharing harmful messages using social media by employees. The present study could be useful for the organizations leaders as well as policymakers and legal fraternity. The study uses a limited number of feedback to validate the model. Also, this is a cross-sectional study which is another limitation of this study.

This study has proposed and validated a theoretical model by using the conspiracy theory as well as the social impact theory which is unique. Moreover, this study adds value to the existing literature on the harmful impacts of social media and its societal impacts. Besides, the validated model of this study has a high explanatory power which is another uniqueness of this study.

In this chapter, we focus on specially designed instruction (SDI) as a core value for the field of specific learning disabilities (SLD). SDI is at the heart of special education, and the field of LD has been built on the core value that effective instruction improves student outcomes. We describe a two-step test and an extended example of what is and is not SDI for Matt, a student with an SLD. Finally, we discuss some of the confusion surrounding SDI and the need for the field to return to its core value of individualized, intentional, targeted, evidence- or high leverage practice–based, and systematic instruction for students with SLD.

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.

Cancer has become a priority among today’s health problems. Therefore, providing facilities that ensure high-quality cancer treatment has become an essential design problem. Additionally, a considerable number of studies have introduced the ‘healing environment concept’ as a substantial input for healthcare buildings. The purpose of this paper is to present a design guide for cancer treatment services that is compatible with the healing environment concept.

In this context, studies on the healing environment have been analyzed, and the legislation of some selected countries has been assessed. Then, all the filtered data are used to form the design guideline for chemotherapy department, radiation oncology department and inpatient care services under a new series of analysis criteria.

The resulting principles are revealed according to the criteria of general settlement principles, internal function relations, medical necessities, user experience, interior design, social interaction/privacy, safety, landscape design and outdoor relations by the help of proposed plans, diagrams and schematic drawings.

This research constitutes the first and yet only study in its field that aims to increase efficiency and user satisfaction and provide better patient-centered care while providing a design guide on health-care architecture.

This study employs the Social Identity Theory to examine the differential effects of personal and social dimensions of fear of missing out (FOMO) on sustainable food consumption (SFC) practices.

An online survey-based empirical study was conducted with 395 respondents. The data were analysed using structural equation modelling and Hayes process Macro in SPSS.

SFC was found to be positively influenced by personal FOMO. Contrary to expectations, social FOMO had a negative correlation with SFC. Social influence and social identity were shown to be positively correlated, whilst the social influence-SFC relationship was favourable. This approach was aided by social identity.

The study supports personal FOMO as an SFC-influencing factor. It evaluates the differential effects of FOMO’s personal and social dimensions on SFC. It also demonstrates that social FOMO negatively affects SFC, contrary to expectations.

The study advises sustainable food firms to reduce personal FOMO via advertising and messaging.

This research is amongst the first to segregate the differential effects of social and personal FOMO regarding SFC behaviour. Research has examined FOMO as a higher-order construct involving social and personal aspects. Second, FOMO is often associated with negative behaviours including social media addiction and substance abuse. This FOMO-related research analyses a desired behaviour.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

Microfinance programs across the countries are designed on the self-help and peer pressure model, aim at microentrepreneurship development. Despite of significant studies on microfinance-supported microentrepreneurship (MSM), not a single literature examines it from the systems thinking. In addition to that, the extant literature did not look MSM from the behavioral perspectives. To address the above gaps, the present study aims to examine self-help group (SHG)-based microfinance programs from the systems approach using the Stimulus-Organism-Behavior-Consequence (SOBC) model.

Information gathered from 786 women SHG members from four states of India through a structured interview schedule. Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were conducted to process data. Additional statistical tests were performed to test the reliability and validity.

It was found that the “positive stimulus” (social intermediation, financial intermediation and business development services) positively impacted; and “negative stimulus” (intermediation accountability, and intermediation assumption) negatively impact, to “motive” (attitude, subjective norms, and perceived control) for micro-entrepreneurship in the SHG-based microfinance. Further, “motive” positively predicted “behavioral intention”; the “behavioral intention” positively determined “consequences” of micro-entrepreneurship. Intermediation as stimuli acted as “input”; the motive and behavioral intention acted as the “process”, and the consequence acted as the “output” in the SHG-based microentrepreneurship system.

To the best of the author's knowledge, this paper is the first one to examine the behavioral systems of microentrepreneurship programs through the Stimulus-Organism-Behavior-Consequence (SOBC) model.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2022-0801

This study aims to examine the mediating effects of corporate governance mechanisms like the board of directors on the association between disruptive technology adoption by audit clients and the risk of material misstatements, including inherent risk and control risk. In particular, the authors study the mediating effects of board characteristics such as board size, independence and gender diversity.

Based on a sample of 100 audit clients listed on the FTSE 100 from 2015 to 2021, this study uses structural equation modelling to test the research objectives.

The findings indicate a significant and negative association between disruptive technology adoption by audit clients and inherent risk. However, there is no significant evidence observed for control risk. The utilisation of disruptive technology by the audit client has a significant impact on the board characteristics, resulting in an increase in board size, greater independence and gender diversity. The authors also find strong evidence that board independence mediates the association between disruptive technology usage and both inherent risk and control risk. In addition, board size and gender exhibit distinct and differential mediating effects on the association and across the two types of risks.

The study reveals that the significant role of using disruptive technology by audit clients in reducing the risk of material misstatements is closely associated with the board of directors, which makes audit clients place greater emphasis on the construction of effective corporate governance.

This study offers essential primary evidence that can assist policymakers and standard setters in formulating guidance and recommendations for board size, independence and gender quotas, ensuring the enhancement of effective governance and supporting the future of audit within the next generation of digital services.

With respect to relevant stakeholders, it is imperative for audit clients to recognise that corporate governance represents a fundamental means of addressing the ramifications of applying disruptive technology, particularly as they pertain to inherent and control risks within the audit client.

This study contributes to the existing literature by investigating the joint impact of corporate governance and the utilisation of disruptive technology by audit clients on inherent risk and control risk, which has not been investigated by previous research.