Search results

The purpose of this study is to identify the causative factors of metro construction safety accidents, analyze the correlation between accidents and causative factors and assist in developing safety management strategies for improving safety performance in the context of the Chinese construction industry.

To achieve these objectives, 13 types and 48 causations were determined based on 274 construction safety accidents in China. Then, 204 cause-and-effect relationships among accidents and causations were identified based on data mining. Next, network theory was employed to develop and analyze the metro construction accident causation network (MCACN).

The topological characteristics of MCACN were obtained, it is both a small-world network and a scale-free network. Controlling critical causative factors can effectively control the occurrence of metro construction accidents. Degree centrality strategy is better than closeness centrality strategy and betweenness centrality strategy.

In practice, it is very difficult to quantitatively identify and determine the importance of different accidents and causative factors. The weights of nodes and edges are failed to be assigned when constructing MCACN.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to control construction risks and reduce safety accidents. More safety resources should be allocated to control critical risks. It is recommended that safety managers implement degree centrality strategy when making safety-related decisions.

This paper establishes the MCACN model based on data mining and network theory, identifies the properties and clarifies the mechanism of metro construction accidents and causations.

The timeliness and quality of information provided to board members are crucial for them to effectively monitor and advise a firm. This study examines the influence of board composition and structure on (1) the board’s actions to mitigate the information asymmetry problem by implementing enterprise information systems (EIS) and (2) the board of directors’ awareness of information asymmetry, their perception of its causes and their efforts to address it.

Our research employs a mixed-methods approach. First, using data from 115 publicly listed Chinese companies, we empirically assess the likelihood of top-level EIS modules adoption at the firm level. Subsequently, through 23 semi-structured interviews, we aim to gain deeper insights into the behavioral motivations behind directors’ attempts to reduce information asymmetry.

The study reveals that boards with a higher number of independent directors or with a strategy committee – indicative of a greater concern regarding information asymmetry problems – are more inclined to adopt top-level EIS modules. Additionally, we identify three primary sources of information asymmetry that directors consider significant in prompting the adoption of top-level EIS modules to alleviate perceived information asymmetry.

This study contributes to both the corporate governance and information systems literature. The implementation and utilization of EIS at the board level have not been extensively explored previously. Moreover, while the issue of information asymmetry at the board level is recognized as a critical governance challenge, the ways in which directors perceive and address this issue remain largely unknown. Our research seeks to illuminate this relatively less-explored area.

This paper aims to contribute to understanding Brazilian fashion consumer behavior. The subsequent research question is formulated as follows: How are the consumers purchasing new clothes and disposing of used ones, and how is their awareness of sustainable fashion consumption and disposal of used clothes?

An online questionnaire was sent to nearly one thousand e-mails. A database was formed with 182 complete answers to 13 questions concerning consumer behavior toward sustainability, especially clothing acquisition, use and disposal. A multimethod approach was used to analyze the initial attributes, applying descriptive statistics, cluster analysis and data mining.

This survey obtained valuable answers from Brazilian fashion consumers grouped into four clusters. Age and yearly income were more critical in determining the clusters. Only four attributes were chosen by the algorithm to build the trees (age, annual income, yearly spending on clothes and how long the clothes are worn). The consumer's profile may help the fashion industry redirect investments in sustainability. The most critical factor leading to the sustainability of clothing fashion was the duration of the clothes. The study dealt with a limited sample size that was not representative of Brazil's broader population. Despite numerous attempts to seek responses through e-mail, the participant pool was predominantly composed of highly educated individuals.

This assessment of Brazilian consumer behavior toward sustainability and fashion presents essential knowledge to understand the relationships among variables affecting the purchase and discharge of clothes.

The purpose of this research is to present an integrated methodological framework to aid in performance stewardship of management institutions according to their strategies based on a holistic evaluation encompassing social, economic and environmental dimensions.

A Mamdani fuzzy inference system (FIS) approach was adopted to design the quantitative models with respect to balanced scorecard (BSC) perspectives to demonstrate dynamic capability. Individual models were developed for each perspective of BSC using Mamdani FIS. Data was collected from subject matter experts in management education.

The proposed methodology is able to successfully compute the scores for each perspective. Effective placement, teaching learning process, faculty development and systematic feedback from the stakeholders were found to be the key drivers for revenue generation. The model is validated as the results were well accepted by the head of the institution after implementation.

The model resulting from this study will assist the institution to cyclically assess its performance, thus enabling continuous improvement. The strategy map provides the causality of the objectives across the four perspectives to aid the practitioners to better strategize. Also this study contributes to the literature of BSC as well to the applications of multi-criteria decision-making (MCDM) techniques.

Mamdani FIS integrated BSC model is a significant contribution to the academia of management education to quantitatively compute the performance of institutions. This quantified model reduces the ambiguity for practitioners to decide the performance levels for each metric and the priorities of metrics.

This paper is a case study of student response systems used in large-class teaching. It considers the benefits, including the engagement of students and academic gains such as reduced administration. The constraints and impacts in classroom teaching are noted, drawing upon the experience of two teachers with their learning captured as a means of dissemination of practice to support other teachers who may be considering adopting and later adapting such practices (Gribble and Beckmann, 2023).

An autoethnographical account was undertaken using an action-learning approach as a sense-making exercise. These accounts enabled a depth of insight beyond the anecdotal evidence experienced by an individual teacher alone.

The findings show that while student response systems have constraints, these can be addressed by putting pedagogical concerns in front of any technology deployment, reaping benefits for students and teachers. Once engaged in using the system, students become more willing to enter further discussions. However, the limitations of both systems indicate that there may be a need for multiple systems to be available based on the pedagogical needs of the class.

The exploration of student response systems and outcomes of positive engagement by students in classroom settings provides insight to those wishing to explore such systems for use in large-class teaching settings.

This work extends discussions surrounding interactivity using student response systems. Additionally, practical insights from the users into their experiences with their students in using such systems provide alternatives for engagement in delivering large-class learning at scale.

In this paper, the heterogeneity of the linkages among financial development, productivity and growth across income groups is emphasized.

An empirical analysis is conducted with an illustrative sample of 130 economies over the period 1991–2019 and classified into four subsamples: Organisation for Economic Co-operation and Development (OECD), developing, least developed and net food importing developing countries. Forecast error variance decompositions and panel vector auto-regressive estimations are computed, with insightful findings.

Higher levels of output stimulate the economic development in the agricultural sector, mainly via the productivity channel and, in the most developed economies, also through access to credit. Differently, in developing and least developed economies, the role of access to credit is marginal. The findings have practical implications for stakeholders involved in the planning of long-run investments. In less developed economies, priorities should be given to investments in technology and innovation, whereas financial markets are more suited to boost the development of the agricultural sector of developed economies.

The authors conclude on the credit–output–productivity nexus and contribute to the literature in (at least) three ways. First, they assess how credit access, agricultural output and agricultural productivity are jointly determined. Second, they use a novel approach, which departs from most of the case studies based on single-country data. Third, they conclude on potential causality links to conclude on policy implications.