Search results

The present study aims to examine the households’ attitudes and intentions to adopt an indoor air purifier against the smog crisis in India by using a comprehensive theoretical framework based on the combination of the Protective Action Decision Model (PADM) and the Theory of Planned Behavior (TPB). The United Nations Sustainable Development Goals (SDGs) 2030 also emphasized ensuring a healthy and safe life, especially by achieving SDG-3, SDG-11 and SDG-13.

Using purposive sampling, the data were collected through a survey questionnaire distributed to 382 households, and study hypotheses were assessed by using partial least squares structural equation modeling employing SmartPLS.

The results revealed that mental health risk perception (MHRP) was the most influential determinant of households’ attitudes toward adopting air purifiers, followed by smog knowledge, physical health risk perception (PHRP), information seeking and product knowledge. Notably, results revealed that households’ attitude is a leading determinant of their adoption intention toward the air purifier compared to subjective norms (SN) and perceived behavioral control (PBC).

To the best of the authors’ knowledge, the present study is the first to provide new insights into an individual’s protective behavior response toward ecological hazards by examining the households’ adoption intention toward the air purifier against the smog crisis using PADM and TPB model inclusively. In addition, the present study analyzes the impact of both PHRP and MHRP on individuals’ protective behavior separately. Also, this study provides theoretical contributions and important practical implications for the government, manufacturers and air purifier sellers.

The study investigated which variables and family dynamics influence the entrepreneurship and succession process in the Italian ice cream sector. In light of the consequences of Covid-19, the research has identified the elements on which female leadership is based.

Data were collected using the qualitative approach by conducting semi-structured interviews at a homemade ice cream production organization.

Findings highlight that to pursue business longevity, one must maintain one’s family identity and values and, therefore, offer quality products. However, the company must know how to innovate to remain competitive and optimize its processes. All this is possible by creating a dialogue and transferring knowledge within the family business to strengthen and prepare future successors. The analysis of the family structure highlights how cultural family identity has privileged gender identity as a factor that has guided the development process since the first generation, in this case, allowing for expansion in terms of size and family. In addition, the results of the analysis highlighted two distinct scenarios within the same case study: the first emphasises the limits of the lack of management of a succession process; the second shows the openness of the organization to the introduction of innovations, expansion strategies and the entry of new partners outside the family.

This study contributes to the knowledge and understanding of how, in light of the pandemic, the resilience of these family businesses contributes to redesigning their internal governance system in favour of the second generation and effectively accelerating the succession process.

The present study explored the extent to which home–school interactions for students with disability are addressed within Australian Federal, and State and Territory government and Catholic education department policies and guidelines.

Utilising a framework adapted from Trezona et al.’s (2018a, b) Organisational Health Literacy Responsiveness self-assessment tool, a document analysis of pertinent policies and guidelines provided an opportunity to understand the prominence of home–school interactions within these guiding documents, the prioritisation of home–school interactions, as well as stipulated actions, implementation resources and monitoring processes.

The findings of this analysis indicate that there are varying approaches to identifying and articulating home–school interactions and associated processes, as well as the roles and responsibilities assigned to stakeholders across the education system(s). Recommendations for increasing in-school and in-classroom translation of documented priorities and objectives are presented.

The article concludes with a broad conceptualisation of home–school interactions for students with disability as established within the analysed documents, as well as considerations for policymakers and researchers involved in policy and guideline development and implementation.

The paper examines whether special purpose governments follow the pecking order model when raising capital, replacing firm equity in the original model with local intergovernmental revenues. Special purpose governments are a relatively underexamined component of state and local governments, and their capital structure choices have important implications for America’s aggregate fiscal health. This paper seeks to illuminate special purpose governments’ choices among available forms of capital.

To address our research inquiry regarding whether special-purpose governments adhere to the pecking order theory, we narrow our focus to a specific group of transit entities. Our investigation utilizes data sourced from two distinct repositories: the United States Census of Governments and the National Transit Database. To facilitate integration of these disparate datasets, we establish a correspondence between them using the Federal Information Processing Standard and the transit identification number. Initially, our analysis employs maximum likelihood estimation, comparing these estimates to those generated by a naïve model. Subsequently, we derive parameter estimates through the application of a bivariate probit model.

The paper supports the pecking order hypothesis where internal funds are consumed first, debt is consumed next and IGR is consumed last. The results are robust and are not influenced by simultaneity bias.

The paper uses transit special purpose governments as the special purpose government of interest. These transit special purpose governments have high fixed costs that may inform their capital structure decisions relative to non-transit special purpose governments. Additionally, transit special purpose governments often have a profit-maximizing objective that may not uniformly apply to other special purpose governments, such as school districts, who lack such an incentive.

Our research should grab the attention of state and local politicians, voters, policy experts and scholars. Special-purpose governments, a key part of our governmental system, are on the rise. Understanding them better can guide decision-making on how to allocate resources, set policies and plan strategically. This knowledge boosts financial reporting quality, transparency, accountability and public confidence. Journalists can leverage our findings to ensure accurate and thorough reporting, fostering accountability and trust. Additionally, debt markets and analysts can factor this information into their risk assessments.

The paper enhances our understanding of how special purpose governments interact with existing models of corporate finance when making capital structure decisions.

Based on the Natural resource-based view (NRBV), this study aims to analyze the association between the Sustainable Development Goals related to Gender Equality, Decent Work, Innovation, and Climatic Action in the Food Industry.

A quantitative study is adopted based on the 2019 World Bank Enterprise Survey microdata. The database includes 1,242 food enterprises from 16 European Union countries. We applied logistic regression with cluster robust standard errors.

Despite global efforts to promote decent work and gender equity, the anticipated results have not yet been achieved, suggesting varying performance in different contexts. Food firms, characterized by significant environmental impacts and seasonal tasks, employ diverse Human Resource Management (HRM) strategies based on whether they pursue innovation or environmental objectives. Grounded in the NRBV, our findings underscore the importance of investing in qualified workers and offering attractive wages to meet environmental goals, as well as providing stable contracts for female workers. The NRBV framework also highlights the crucial role of product and process innovations, whether green or not, in achieving climate action objectives.

European policies must be adapted to the human resources characteristics in the food industry, providing specific training on environmental and innovation issues and contributing to more work stability and gender equality.

Our study applies the NRBV to analyze how human resources and product/process innovations can boost environmental preservation in an industry characterized by strong environmental impacts, seasonal tasks, and financial constraints.

Given the urgency of corporate engagement in sustainable development, companies seek ways to involve their employees in sustainability efforts. In this regard, gamified systems have gained attention as a novel tool to promote sustainable employee behavior. However, as the research field matures, researchers and practitioners are confronted with a scattered academic landscape that makes it difficult to grasp how gamification can be designed to engage employees in sustainable behavior and to understand how gamification effects unfold at psychological, behavioral and corporate levels of sustainability.

This paper uses a systematic literature review to consolidate the existing knowledge on gamification designs and their effects on sustainable employee behavior.

Studies have explored a variety of utilitarian and achievement-, immersion- and social-related gameful affordances to promote positive behavior- and system-related psychological effects as a basis for employee engagement in sustainable behavior. However, the evidence regarding their impact on rational decision-making processes and overcoming the intention-action gap inherent in sustainability is still limited. Nevertheless, several studies in focused areas indicate the potential to elicit behavioral changes that drive sustainability outcomes at the corporate level as well.

Our study provides three main contributions. First, we develop a conceptual framework that illustrates how gamification can drive sustainable behavior in the workplace. Second, we derive seven agenda points to guide future research on gamification for corporate sustainability. Third, we deduce three practical approaches to use gamification as a strategic intervention to promote sustainable behavior in organizations.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

Prior evidence that financial reporting quality (FRQ) of publicly listed firms improves investment efficiency in developed markets leaves unaddressed questions of whether this relationship holds in emerging and frontier markets and what channels influence this relationship. This study aims to test the role of financial constraints faced by firms and managerial risk-taking on the association of FRQ and investment efficiency in 13,231 publicly listed firms in 24 emerging and frontier markets.

Available accounting data from 1998 to 2022 are collected for all listed firms across 41 industries in 24 countries. Causal relationships are tested using fixed-effect regression analysis, several additional tests and robustness checks are applied using alternative proxies and concerns for endogeneity are addressed using two-stage least square and system generalised method of moments analysis.

Findings show that FRQ of firms in emerging and frontier markets positively affects investment efficiency, the affirmative impact of FRQ on investment efficiency is higher when firms are facing more financial constraints and when managerial risk-taking is lower and financial constraints and risk-taking have a more pronounced impact on the link between FRQ and investment efficiency in the under-investment scenario.

These findings contribute to the growing body of evidence, shedding light on the meticulous interplay between FRQ and investment efficiency in frontier and emerging markets. Specifically, the increased financial constraints encountered by firms and a more conservative approach to managerial risk-taking emerge as crucial factors complementing this relationship.

Safety research has focused on drivers, pedestrians and vehicles, with scarce attention given to highway traffic officers (HTOs). This paper develops a robust prediction model which enables highway safety authorities to predict exclusive incidents occurring on the highway such as incursions and environmental hazards, respond effectively to diverse safety risk incident scenarios and aid in timely safety precautions to minimise HTO incidents.

Using data from a highway incident database, a supervised machine learning method that employs three algorithms [namely Support Vector Machine (SVM), Random Forests (RF) and Naïve Bayes (NB)] was applied, and their performances were comparatively analysed. Three data balancing algorithms were also applied to handle the class imbalance challenge. A five-phase sequential method, which includes (1) data collection, (2) data pre-processing, (3) model selection, (4) data balancing and (5) model evaluation, was implemented.

The findings indicate that SVM with a polynomial kernel combined with the Synthetic Minority Over-sampling Technique (SMOTE) algorithm is the best model to predict the various incidents, and the Random Under-sampling (RU) algorithm was the most inefficient in improving model accuracy. Weather/visibility, age range and location were the most significant factors in predicting highway incidents.

This is the first study to develop a prediction model for HTOs and utilise an incident database solely dedicated to HTOs to forecast various incident outcomes in highway operations. The prediction model will provide evidence-based information to safety officers to train HTOs on impending risks predicted by the model thereby equipping workers with resilient shocks such as awareness, anticipation and flexibility.

This study explores the complex interaction of environmental policies on corporate cash and capital investment decisions.

The study utilizes a 10-year dataset from 2010 to 2019, comprising publicly listed firms from 10 prominent Asian countries. The analysis was conducted by employing the System GMM.

The regression has revealed that most of the business investments are negatively affected by environmental regulation (ENR), while green innovation (GNI) is positively significant to investments. Moreover, we indicated that ENR raises the cash balance, while GNI tends to reduce it. There was a strong negative correlation found between cash reserves and investment; this implies a crowding-out effect: excess liquidity dilutes the propensity for capital expenditure. The findings emphasized cash balances as a moderator in the relationship between environmental policies and investments. More specifically, maintaining greater cash reserves is an insulating mechanism against the otherwise damaging impact of stringent ENR on corporate investment decisions and a protective measure for financial soundness against external environmental stress.

It is especially important considering the heterogeneous effects obtained across high-income, upper-middle-income and lower-middle-income countries, responding differentially to environmental policies. The results show support for a balanced integration of fiscal incentives, subsidies or tax credits, especially in lower-middle-income countries, to promote sustainable practices without imposing prohibitive compliance costs.

The current analysis supplements the new insights regarding the transformation channel of environmental policies into industrial investment and how cash holdings diversify this channel.