In this paper, a data mining approach is proposed for monitoring the conditions leading to a rail wheel high impact load. The proposed approach incorporates logical analysis of…
Abstract
Purpose
In this paper, a data mining approach is proposed for monitoring the conditions leading to a rail wheel high impact load. The proposed approach incorporates logical analysis of data (LAD) and ant colony optimization (ACO) algorithms in extracting patterns of high impact loads and normal loads from historical railway records. In addition, the patterns are employed in establishing a classification model used for classifying unseen observations. A case study representing real-world impact load data is presented to illustrate the impact of the proposed approach in improving railway services.
Design/methodology/approach
Application of artificial intelligence and machine learning approaches becomes an essential tool in improving the performance of railway transportation systems. By using these approaches, the knowledge extracted from historical data can be employed in railway assets monitoring to maintain the assets in a reliable state and to improve the service provided by the railway network.
Findings
Results achieved by the proposed approach provide a prognostic system used for monitoring the conditions surrounding rail wheels. Incorporating this prognostic system in surveilling the rail wheels indeed results in better railway services as trips with no-delay or no-failure can be realized. A comparative study is conducted to evaluate the performance of the proposed approach versus other classification algorithms. In addition to the highly interpretable results obtained by the generated patterns, the comparative study demonstrates that the proposed approach provides classification accuracy higher than other common machine learning classification algorithms.
Originality/value
The methodology followed in this research employs ACO algorithm as an artificial intelligent technique and LDA as a machine learning algorithm in analyzing wheel impact load alarm-collected datasets. This new methodology provided a promising classification model to predict future alarm and a prognostic system to guide the system while avoiding this alarm.
Details
Keywords
Osman Inanç Güney and Luca Giraldo
The purpose of this paper is to understand consumer attitudes toward organic eggs by identifying their profiles and estimating the degree of their willingness to pay (WTP) for…
Abstract
Purpose
The purpose of this paper is to understand consumer attitudes toward organic eggs by identifying their profiles and estimating the degree of their willingness to pay (WTP) for eggs with different attributes in order to evaluate the position of organic eggs.
Design/methodology/approach
Empirical data were collected from a face-to-face cross-sectional market survey, which involved a choice experiment design and a series of questions related to respondents’ attitudes and preferences in terms of organic egg consumption. A total of 552 consumers who are responsible for their household purchases were sampled, while the survey was performed in the major cities of seven regions of Turkey. The gathered data from the questions on consumer attitudes and preferences were analyzed using ordered probit, while the choice experiment data were analyzed through the use of conditional logit and mixed logit models.
Findings
Consumers perceive organic eggs to be healthy, nutritious and delicious food. In the study, we obtained three consumer groups (collectivist consumers, individualist consumers and reluctant consumers) with different characteristics in relation to organic egg consumption. When the motivations for organic egg consumption were analyzed, it was found that individual benefits have a greater impact than collectivist benefits on consumers’ choice to purchase organic eggs. According to the results of the regression analysis, consumers are willing to pay ₺0.76 more per egg for organic eggs compared to conventional eggs. Overall, consumers are reluctant to pay a premium in view of the functionality aspect of eggs.
Research limitations/implications
The results will help the actors within the egg industry to develop production and market-planning processes for differentiated egg markets according to consumer preferences and in terms of having the opportunity to select their ideal customer segments.
Originality/value
The research is the first study that analyses the motivations and the willingness of Turkish consumers to purchase organic eggs through using a choice experiment design and regression models. Original findings include the segmentation of consumers according to personal beliefs and norms. The research is also important in terms of comparing two regression model results in methodical terms. The similarity among the obtained results from the regression analysis increased the reliability of the study.
Details
Keywords
Hany Samir Salib and Medhat Endrawes
This study aims to examine the relationships between social and environmental reporting (SER) and the size and university ranking of 39 Australian universities. The study examines…
Abstract
Purpose
This study aims to examine the relationships between social and environmental reporting (SER) and the size and university ranking of 39 Australian universities. The study examines Australian universities and the impact of size on corporate social responsibility (CSR) using an accountability model. Not many studies have considered this relationship in the university environment.
Design/methodology/approach
The study uses content analysis by applying the Global Reporting Initiative (GRI) disclosure index to university annual reports and adopting the accountability model of Coy et al. (2001) to examine the impact of the size of Australian universities on SER, measured by the number of student enrolments. Data was collected in 2014. This classification of Australian universities based on size was adopted from Universities Australia (2022). The authors collected data about the academic ranking of Australian universities using the Shanghai ranking (Shanghai, 2022).
Findings
The authors predict and find that there is no relationship between SER and size. As the authors expected, the level of SER is marginally influenced by the world academic ranking of universities. The findings provide significant insight into the SER practices of Australian universities. The authors expand the SER literature and practice nationally and internationally.
Originality/value
Few studies have explored CSR in Australian universities. The current study expands the debate on SER using an accountability model in Australian universities. This paper describes CSR in 39 Australian universities and the importance of size and university ranking. The results offer new insights into the relationship between CSR in Australian universities and their size and ranking.
Details
Keywords
This paper aims to assess COVID-19 (C-19) pandemic influence in the 37 factors identified from extant literature as factors influencing the viability of local construction firms…
Abstract
Purpose
This paper aims to assess COVID-19 (C-19) pandemic influence in the 37 factors identified from extant literature as factors influencing the viability of local construction firms (LCFs).
Design/methodology/approach
A sample size of 65 staff of 31 LCFs that were awarded construction projects contracts in institutions in Nigeria was purposefully selected and accessed based on relevant predetermined criteria. Respondents’ views on factors determining the viability of LCFs were obtained. Factors known to be influenced by C-19 are 25 of the 37 factors rated on a five-point Likert scale of importance by the respondents. Mean scores were used to rank the factors and principal component analysis was used to obtain key component factors (CFs) influenced by the C-19 pandemic.
Findings
Six of the first ten “extremely important” and “very important” factors are known to be influenced by C-19 pandemic. A total of 8 CFs having 20 variables with factor loadings of more than 0.5 each were known to be influenced by C-19. The C-19 pandemic influenced LCFs’ cash flow and management of construction labour, plant and equipment amidst variables that had above 0.8 factor loading.
Research limitations/implications
A limitation of this study is the inability to conduct close contact interview during this period to obtain personal views on the influence of C-19 on LCFs. However, this does not reduce the quality of findings of this study, as there are valid literature basis hinging this study findings.
Practical implications
The paper recommends that all stakeholders pay prompt attention to the factors adversely affected by the C-19 pandemic to improve or at the least sustain the viability of LCFs.
Originality/value
This paper fulfils a present pertinent need of assessing the influence of the C-19 pandemic on various factors influencing the viability of construction firms.
Details
Keywords
Subir Bairagi, Matty Demont, Marie Claire Custodio and Jhoanne Ynion
The purpose of this paper is to analyze geographic heterogeneity of consumer preferences for intrinsic quality attributes of rice in South and Southeast Asia and the drivers of…
Abstract
Purpose
The purpose of this paper is to analyze geographic heterogeneity of consumer preferences for intrinsic quality attributes of rice in South and Southeast Asia and the drivers of demand for these attributes, with a particular focus on rice fragrance and the role of gender.
Design/methodology/approach
Stated-preference surveys were conducted with 4,231 urban and rural consumers in 37 cities across seven countries (Bangladesh, India, Cambodia, Indonesia, the Philippines, Thailand, and Vietnam) during 2013–2014 and analyzed through a rank-ordered logistic regression with incomplete ranking choice data.
Findings
Preferences for rice attributes are found to be significantly heterogeneous among consumers in South and Southeast Asia. Urban Thai consumers tend to prioritize appearance and cooking characteristics over taste and nutritional benefits, relative to all other surveyed consumers. In contrast with South Asian consumers, Southeast Asian consumers have largely adopted Thai preferences for rice texture and fragrance, a trend that was earlier coined “Jasminization.” We find that demand for rice fragrance is mainly driven by women, educated consumers, large families, families spending a lower share of their food expenditures on rice, and consumers in Southeast Asia (particularly the Philippines and Cambodia).
Originality/value
Little is known about geographic heterogeneity, drivers, and the role of gender in demand for rice fragrance. This paper fills these knowledge gaps. Our findings suggest that the more women are empowered in grocery decision-making, the more demand for aromatic rice is expected to rise. These insights can assist market-driven and gender-responsive rice breeding programs in simultaneously enhancing rice farmers' livelihoods and gender equity.
Details
Keywords
Taofeeq Durojaye Moshood, James O.B. Rotimi and Wajiha Shahzad
This study aims to investigate the crucial role of information quality in the construction industry and its impact on organizational performance. The research objectives are…
Abstract
Purpose
This study aims to investigate the crucial role of information quality in the construction industry and its impact on organizational performance. The research objectives are threefold: (1) to identify and analyse key factors influencing information quality in construction organizations; (2) to examine how information quality affects strategic decision-making processes in the industry; and (3) to assess the extent to which information quality impacts overall organizational performance.
Design/methodology/approach
The study commences by gathering data from databases such as Scopus, Elsevier, Taylor and Francis, and Emerald Insight. The collected data is then analysed using ATLAS.ti 9 to construct a model linking information quality with strategic decision-making and organization performance.
Findings
The literature review analysis reveals the complex interplay between information quality, strategic decision-making and organizational performance in the construction industry. Key findings include identifying critical factors influencing information quality, such as technological infrastructure, organizational processes and personnel skills. The study highlights the necessity for organizations to recognize potential challenges in information management and formulate strategies to overcome them.
Originality/value
This research makes a significant contribution to the field by providing a comprehensive framework for understanding the role of information quality in strategic decision-making within the construction industry. The study’s originality lies in its systematic approach to synthesizing existing literature and developing visual representations of complex relationships between information quality, decision-making processes and organizational performance.