Search results

Interventions that improve timely access to outpatient health services are essential in managing demand. This process evaluation aimed to describe the implementation, mechanism of impact and context of an intervention to reduce waiting for first appointments in an outpatient epilepsy clinic.

The UK Medical Research Council framework was used as the theoretical basis for a process evaluation alongside an intervention trial. The intervention, Specific Timely Appointments for Triage (STAT), is a data-driven approach that combines a one-off backlog reduction strategy with methods to balance supply and demand. A mixed methods process evaluation synthesised routinely collected quantitative and qualitative data, which were mapped to the domains of implementation, mechanisms of impact and contextual elements.

The principles of the STAT model were implemented as intended without adaptation. The STAT model reached all patients referred, including long waiters and was likely generalisable to other medical outpatient clinics. Mechanisms of impact were increased clinic capacity and elimination of unwanted variation. Contextual elements included the complexity of healthcare systems and the two-tier triage practice that contributes to prolonged waiting for patients classified as non-urgent.

This process evaluation shows how a data-driven strategy was applied in a medical outpatient setting to manage demand. Improving patient flow by reducing waiting in non-urgent, outpatient care is a complex problem. Understanding how and why interventions work is important for improved timeliness of care, and sustainability of public health services.

Autistic individuals are employed and access higher education opportunities at significantly lower rates than their nondisabled peers (US Bureau of Labor Statistics [BLS], 2023; Newman, 2015). Schools are an optimal setting for intervention as most individuals access the school setting. However, traditional support to facilitate postsecondary transition effectively, such as transition plans, is currently lacking (Greene, 2018; Hughes et al., 2023). The authors of the present chapter conducted a systematic review to identify school-based interventions available for autistic youth intended to support the transition from high school to higher education, entrepreneurship, and employment. The data extraction methods used by the authors identified 19 articles on interventions. Across all studies, the authors found variation in the extent to which researchers addressed entrepreneurial skills and identified two key skill development areas across different intervention modalities: employability skills and interpersonal communication skills. Based on these results, the authors discuss available school-based programming intended to prepare autistic youth for postsecondary careers and entrepreneurial opportunities and the implications of existing interventions for practitioners and researchers interested in improving outcomes for autistic students as they transition to the workplace, particularly entrepreneurial endeavors.

Sustainability entails promoting social development and meeting current needs without jeopardizing future life on Earth. It encompasses responsible resource stewardship and a consideration of environmental, social, and economic impacts. Sustainable tourism, as defined by the World Tourism Organization (WTO), addresses these impacts and balances economic prosperity, social well-being, and environmental preservation. Despite the tourism industry’s growth, its carbon-intensive nature significantly contributes to climate change, necessitating the adoption of sustainable practices. The global carbon footprint from tourism has risen, projecting to reach 6.5 GtCO₂e by 2025, further stressing the environment. Sustainable tourism aligns with the United Nations’ Sustainable Development Goals, particularly SDG 8 and SDG 12, which emphasize inclusive and sustainable economic growth, and responsible consumption and production patterns. Technological advancements, such as AI and the Internet of Things, offer innovative data-driven solutions that not only revolutionize the tourism ecosystem but also mitigate its environmental impact. These technologies can help monitor and manage resource use in real time, promote renewable energy, and facilitate eco-friendly tourism practices. Embracing Industry 5.0, which integrates human capabilities with intelligent machines, the tourism sector can achieve human-centric, resilient, and sustainable growth. Future research should explore technology’s role in sustainable tourism, focusing on its environmental benefits and alignment with sustainability goals.

With increasing demands placed on Higher Education Institutions (HEIs) to engage with the Sustainable Development (SD) needs of its local communities, Community-Engaged Teaching and Learning (CETL) has emerged as a valuable tool to help HEIs cater to such demands. This study aims to explore and examine CETL practices at HEIs across the globe, particularly in relation to its role in furthering the SD agenda.

This study adopts an extensive review of academic literature as an investigative tool to probe different CETL approaches being practiced by HEIs, especially the ones aligned with sustainability.

The study revealed discernible findings on four aspects: (i) curricular strategies and pedagogical interventions adopted under the ambit of CETL for advancing the SD agenda, (ii) engagement and sustainability linked competencies and learning outcomes derived in the process, (iii) challenges constraining CETL practices at HEIs, and (iv) strategies for strengthening the same and ensuring its impactful implementation.

This study accrues value in illuminating the practice, role, impact and implications of SD oriented CETL practices, given that there are limited studies on the subject. It also contributes to the global call for HEIs to catalyze sustainable social development by making their teaching and learning functions more community-engaged and socially relevant.

Artificial Intelligence (AI) is a branch of computer science, and Chatbot relies on the technology of AI. Chatbot has an AI feature which can be used for many messaging applications. A chatbot has a very advanced and promising interaction between humans and machines. They are a representative of systematic evolution of a question-answering natural language processing (NLP). Today, India has over 4.6 crores investor accounts with Central Depository Services (India) Limited (CDSL) who are actively investing in stocks, mutual funds, insurance and banking schemes. Chatbot plays an important role today in investor awareness and grievance resolution. Chatbots offer several advantages like standardised operations, higher efficiency and time saving but it has several disadvantages such as lack of human touch and inability to understand fragmented or grammatically incorrect sentences. There are several objections as it may contribute to further unemployment in many sectors. Overall analysis indicates that Chatbot application has a lot of potential in the investment sector in country like India.

This paper aims to examine the impact of corporate environmental transparency (CET) on corporate financial performance under a mandatory environmental disclosure policy in China, the largest carbon-emitting country. It aims to clarify the concept of CET and investigate its short-term financial implications for key pollutant-discharging entities (KPEs).

A multidimensional model is used to construct a comprehensive CET index for KPEs in China. Empirical tests are conducted to assess the relationship between CET and corporate financial performance.

The study finds a negative relationship between CET and corporate financial performance in the short term. Increased environmental transparency necessitates higher environmental resource allocation, adversely affecting profits. The results remain unchanged from a battery of robustness tests. Despite mandatory disclosure, companies tend to provide general and vague information rather than specific and meaningful environmental data.

The findings provide rich practical implications for policymakers to improve a mandatory environmental disclosure policy. The paper also contributes to the existing knowledge by developing a measure of CET and presenting new evidence to the debate on whether corporate environmental disclosure can be regarded as transparency.

Policymakers are advised to refine mandatory environmental disclosure regulations to ensure genuine transparency and to implement policy measures that alleviate the financial burdens of companies with high CET levels, thereby encouraging sustainable practices.

This paper contributes to the existing knowledge by developing a measure of CET and providing new evidence on the debate over whether environmental, social and governance (ESG) disclosure equates to transparency. It emphasizes the complexity of transparency and the inadequacy of current environmental disclosure practices among KPEs. The study underscores the need for financial support for companies with high CET levels to alleviate short-term financial strains and promote long-term sustainability.

With the recent proliferation of AI, organisations are transforming not only their organisational design but also the input and output operational processes of the hiring process. The purpose of this paper is to explore the organisational and operational dimensions resulting from the deployment of AI during talent acquisition process.

The authors conducted semi-structured interviews and meetings with human resources (HRs) professionals, recruiters and AI hiring platform providers in Sweden. Using an inductive data analysis rooted in the principles of grounded theory, the study uncovered four aggregate dimensions critical to understanding the role of AI in talent acquisition.

With insights from algorithmic management and ambidexterity theory, the study presents a comprehensive theoretical framework that highlights four aggregate dimensions describing AI’s transformative role in talent recruitment. The results provide a cautionary perspective, advising against an excessive emphasis on operational performance driven solely by algorithmic management.

The study is limited in scope and subject to several constraints. Firstly, the sample size and diversity are restricted, as the findings are based on a limited number of semi-structured interviews and meetings with HRs professionals, recruiters, and AI hiring platform providers. Secondly, the rapid evolution of AI technologies means that the study’s findings may quickly become outdated as new advancements and applications emerge.

The results provide managers with actionable information that can lead to more precise and strategic management practices, ultimately contributing to improved organizational performance and outcomes. Plus, enhancing their ability to make informed decisions, optimize processes and address challenges effectively.

The results signal both positive and negative impacts on employment opportunities. On the positive side, AI can streamline recruitment processes, making it easier for qualified candidates to be identified and hired quickly. However, AI systems can also perpetuate existing biases present in the data they are trained on, leading to unfair hiring practices where certain groups are systematically disadvantaged.

By examining the balance between transactional efficiency and relational engagement, the research addresses a crucial trade-off that organizations face when implementing AI in recruitment. The originality lies in its critique of the prevailing emphasis on e-recruiting.

Drawing on work from home (WFH), job demand-control and street-level bureaucracy literature streams, this paper specifically focuses on the emerging trend of WFH for public sector employees in a developing country context of Egypt.

The empirical sample comprises focus group discussions with a total of 40 public sector employees in Egypt. Thematic analysis was subsequently used on focus group discussion transcripts to bring out main themes linked to this topic.

Our findings show that employee (marginal discretion power, pharaonism, corruption), citizen (unfamiliarity with digital services) and country (lack of proper info-structure, overstaffing in the public sector)- level challenges hinder and/or slow down the potential for WFH in Egyptian public sector.

A major implication of our paper relates to highlighting the criticality of e-governance and WFH for public sector employees, as well as highlighting multilevel challenges associated with those. At the same time, socio-economic and political consequences of offering such options need to be considered in a country like Egypt where most public organisations are overstaffed, and those employees lack modern day employability skills. Hence, there needs to be an open debate in countries such as Egypt on the consequences of e-governance and WFH and whether it may facilitate delivering citizen services digitally. Also, high power distance culture plays a role in this context, and any change cannot be successful unless that specific aspect is confronted.

This study contributes to the emerging WFH literature by being one of the pioneering studies to offer a multilevel (micro, meso and macro) assessment of this phenomenon in the under-researched fragile developing country’s context.

This paper aims to analyze the influence of organizational and contextual factors on companies’ decisions to set absolute emissions targets and science-based targets (SBTs).

This study uses a sample of 23,166 observations across 69 countries from 2016 to 2020 to analyze the likelihood of firms to establish absolute emissions targets and SBTs.

The results show that firm size, governance, climate-related regulation and moral acceptance in the country in question positively influence companies’ decisions on these matters. Furthermore, while profitability has a positive influence on the participation of companies in the SBT initiative (SBTi), both the financial risk involved and sector emissions intensity can discourage companies from participating in the SBTi or from establishing absolute emissions targets.

This study may allow regulators and policymakers to encourage carbon information disclosure with a greater focus on aspects that specifically contribute to evaluating ways of promoting effective behavior on the part of companies in the fight against climate change.

The results of this study serve to support the demands of civil society, as well as to guide regulators in the design of measures in the fight against climate change and steer the decision-making of investors in moving toward a low carbon economy.

To the best of the authors’ knowledge, this study is the first to examine whether organizational and contextual factors affect companies’ propensity to set absolute emissions targets and SBTs.