Search results
1 – 10 of over 3000Thao-Trang Huynh-Cam, Long-Sheng Chen and Tzu-Chuen Lu
This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct…
Abstract
Purpose
This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability.
Design/methodology/approach
The real-world samples comprised the enrolled records of 2,412 first-year students of a private university (UNI) in Taiwan. This work utilized decision trees (DT), multilayer perceptron (MLP) and logistic regression (LR) algorithms for constructing EPMs; under-sampling, random oversampling and synthetic minority over sampling technique (SMOTE) methods for solving data imbalance problems; accuracy, precision, recall, F1-score, receiver operator characteristic (ROC) curve and area under ROC curve (AUC) for evaluating constructed EPMs.
Findings
DT outperformed MLP and LR with accuracy (97.59%), precision (98%), recall (97%), F1_score (97%), and ROC-AUC (98%). The top-ranking factors comprised “student loan,” “dad occupations,” “mom educational level,” “department,” “mom occupations,” “admission type,” “school fee waiver” and “main sources of living.”
Practical implications
This work only used enrollment information to identify dropout students and crucial factors associated with dropout probability as soon as students enter universities. The extracted rules could be utilized to enhance student retention.
Originality/value
Although first-year student dropouts have gained non-stop attention from researchers in educational practices and theories worldwide, diverse previous studies utilized while-and/or post-semester factors, and/or questionnaires for predicting. These methods failed to offer universities early warning systems (EWS) and/or assist them in providing in-time assistance to dropouts, who face economic difficulties. This work provided universities with an EWS and extracted rules for early dropout prevention and intervention.
Details
Keywords
The purpose of this study is to examine whether and how financial performance feedback influences green innovation performance by drawing on the behavioral theory of the firm…
Abstract
Purpose
The purpose of this study is to examine whether and how financial performance feedback influences green innovation performance by drawing on the behavioral theory of the firm (BTOF) and relying on motivation-based logic.
Design/methodology/approach
A total of 17,558 firm-year observations from 3,062 publicly traded firms in China are used as the research sample.
Findings
The results reveal that low-performing firms are less likely to conduct green innovation activities because managers burden pressure to meet short-term targets. This study further finds that these relations are moderated by institutional ownership.
Originality/value
This study contributes to the BTOF literature by linking performance feedback to green innovation activities. This study applies a motivation-based logic to relate performance below and above aspirations to green innovation activities. This study introduces institutional ownership as a boundary condition.
Details
Keywords
Vaclav Snasel, Tran Khanh Dang, Josef Kueng and Lingping Kong
This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate…
Abstract
Purpose
This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.
Design/methodology/approach
Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.
Findings
ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.
Originality/value
IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.
Details
Keywords
Yi-Chun Huang and Chih-Hsuan Huang
Prior research on green innovation has shown that institutional pressure stimulates enterprises to adopt green innovation. However, an institutional perspective does not explain…
Abstract
Purpose
Prior research on green innovation has shown that institutional pressure stimulates enterprises to adopt green innovation. However, an institutional perspective does not explain why firms that face the same amount of institutional pressure execute different environmental practices and innovations. To address this research gap, the authors linked institutional theory with upper echelons theory and organization performance to build a comprehensive research model.
Design/methodology/approach
A total of 800 questionnaires were issued. The final usable questionnaires were 195, yielding a response rate of 24.38%. AMOS 23.0 was used to analyze the data and examine the relationships between the constructs in our model.
Findings
Institutional pressures affected both green innovation adoption (GIA) and the top management team's (TMT's) response. TMT's response influenced GIA. GIA was an important factor affecting firm performance. Furthermore, TMT's response mediated the relationship between institutional pressure and GIA. Institutional pressures indirectly affected green innovation performance but did not influence economic performance through GIA. Finally, TMT's response indirectly impacted firm performance through GIA.
Originality/value
The authors draw on institutional theory, upper echelons theory, and a performance-oriented perspective to explore the antecedents and consequences of GIA. This study has interesting implications for leaders and managers looking to implement green innovation and leverage it for firm performance to out compete with market rivals as well as to make the changes in collaboration with many other companies including market rivals to gain success in green innovation.
Details
Keywords
Elena Adriana Biea, Elena Dinu, Andreea Bunica and Loredana Jerdea
Various scholars suggest that there is a lack of research on the recruitment in small and medium-sized enterprises (SMEs) and also a scarcity of theoretical basis for the…
Abstract
Purpose
Various scholars suggest that there is a lack of research on the recruitment in small and medium-sized enterprises (SMEs) and also a scarcity of theoretical basis for the recruitment procedures used by these companies. As the vast majority of studies concentrate on larger organizations, they may not accurately reflect the challenges faced by smaller-sized entities to profoundly and accurately comprehend their recruitment procedures. In addition, the use of technology in recruitment has grown in importance in today’s quickly evolving business environment, particularly in light of the COVID-19 pandemic footprint. This study aims to examine the recruitment procedures used by SMEs and how they have been compelled to adjust to different extents to these technological improvements by the effects of the aforementioned epidemic.
Design/methodology/approach
With the aim to investigate the current recruitment practices in SMEs and the extent to which digital technologies are embraced by these companies within human resources (HR) procedures, this research relied on interviews with SMEs representatives. The qualitative methods used provided access to relevant data and insights, as they allowed close interactions with top managers and CEOs of ten companies from various sectors. Thus, the research results draw a vivid and reliable image of the procedures and practices used by small and medium-sized companies to attract, select and retain their staff.
Findings
This study’s findings are of increased interest to HR professionals, recruiters and managers in SMEs, who aim to attract and retain the best talent and optimize their recruitment strategies in a rapidly changing business environment, enabled by technological advancements. Effective HR recruitment procedures adapted to the specific needs of small and medium-sized companies can lead to several benefits for the organization, including improved employee selection, reduced turnover and increased organizational productivity.
Research limitations/implications
Although the interviews examined here encompass recruitment techniques from SMEs in a variety of industries, the results’ generalizability is limited by the sample size and geography. Furthermore, the findings’ dependability is dependent on the accuracy of the data provided by the respondents.
Practical implications
This investigation confirms some of the theoretical underpinnings which point to the lack of formalized structures and procedures in the recruitment process in SMEs, which enjoy more flexibility in managing HR processes. In addition, the results reinforce the arguments indicating an adjustment between HR strategies or policies and organizational goals in smaller enterprises which adapt faster to changes in the market. Moreover, it becomes apparent that there is a relationship between the quality of job descriptions and the successful fit in attracting the right candidates for the open positions. Furthermore, digital technologies offer opportunities for expanding the recruiters’ reach to a wider audience and also support the selection stage, thus increasing the chances of finding suitable staff. As the need to shift from traditional recruitment to e-recruitment in SMEs has been highlighted in the literature, the qualitative research revealed that this need was driven on the one hand by the COVID-19 pandemic when these companies successfully adapted and implemented new online methods of recruiting, but also by the lack of skilled labor, leading to the expansion of recruitment to other parts of the country or even to other countries.
Social implications
With regard to the proportion of men and women used in small and medium-sized companies, there is a clear need to involve and train more women in the predominantly male-dominated industrial and IT sectors. From this point of view, companies tend to devote more interest to integrating communities of women in these industries, as well as in key management positions. Another point of interest that the study highlights is the fact that SMEs have started to get creative with the benefits package they propose to candidates and focus on remote work, hybrid office–home working, or seasonal work to offer future employees a better work–life balance.
Originality/value
The added value of this investigation is filling the gaps in the current literature concerning recruitment procedures currently used by SMEs, the challenges they face and the solutions they advanced to solve them. Furthermore, SMEs often drive innovation and competition in the market and play a crucial role in the supply chain of larger companies, providing them with the goods and services they need to operate and supporting the availability and reliability of products from larger companies. They are often the driving force behind revitalizing local economies and creating new employment opportunities. Consequently, the underlying significance of this study is rooted in the need to modernize and simultaneously improve HR recruitment procedures through the integration of technology and a focus on innovation.
Details
Keywords
Hongyang Li, Yanlin Chen, Junwei Zheng, Yuan Fang, Yifan Yang, Martin Skitmore, Rosemarie Rusch and Tingting Jiang
In the absence of previous work, this study investigates how the psychological contract (PC) influences the safety performance of construction workers in China.
Abstract
Purpose
In the absence of previous work, this study investigates how the psychological contract (PC) influences the safety performance of construction workers in China.
Design/methodology/approach
The literature is first consulted to obtain a set of PC and safety performance measures that fits the specific situation of construction workers, which is then moderated by five construction experts. A questionnaire survey of 206 workers from 4 different construction sites is followed by a descriptive statistical analysis of the nature of the PC and level of the safety performance of the respondents. Finally, a regression analysis is used to ascertain the level of influence of the PS, and an analysis is made of the influence of PC on safety performance.
Findings
A set of PC and safety performance measures is identified that fits in the construction workers' specific situation. The PC of the respondents is found to be intact and well-performed, and their safety performance is maintained at a high level. Safety performance is highly influenced by the state of the PC, with the three dimensions of safety performance (safety result, safety compliance and safety participation) positively correlated with the three dimensions of the PC (normative, interpersonal and developmental).
Originality/value
Suggestions are made to improve safety production management and safety performance by providing adequate material and economic conditions, helping the workers establish good interpersonal relationships and realize their personal values.
Details
Keywords
This study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was…
Abstract
Purpose
This study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was done to explore the feasible measures and optimal incentives to achieve higher levels of green building in China.
Design/methodology/approach
First, the practice of green building in China was analyzed, and the specific influencing factors and incentive measures for green building development were extracted. Second, China-specific evolutionary game models were constructed between developers and homebuyers under the market regulation and government incentive mechanism scenarios, and the evolutionary paths were analyzed. Finally, real-case numerical simulations were conducted, subsidy impacts were mainly analyzed and optimal subsidy equilibriums were solved.
Findings
(1) Simultaneously subsidizing developers and homebuyers proved to be the most effective measure to promote the sustainability of green buildings. (2) The sensitivity of developers and homebuyers to subsidies varied across scenarios, and the optimal subsidy level diminished marginally as building greenness and public awareness increased. (3) The optimal subsidy level for developers was intricately tied to the building greenness benchmark. A higher benchmark intensified the developer’s responsiveness to losses, at which point increasing subsidies were justified. Conversely, a reduction in subsidy might have been appropriate when the benchmark was set at a lower level.
Practical implications
The expeditious advancement of green buildings holds paramount importance for the high-quality development of the construction industry. Nevertheless, the pace of green building expansion in China has experienced a recent deceleration. Drawing insights from the practices of green building in China, the exploration of viable strategies and the determination of optimal government subsidies stand as imperative initiatives. These endeavors aim to propel the acceleration of green building proliferation and materialize high-quality development at the earliest juncture possible.
Originality/value
The model is grounded in China’s green building practices, which makes the conclusions drawn more specific. Furthermore, research results provide practical references for governments to formulate green building incentive policies.
Details
Keywords
Tan Zhang, Zhanying Huang, Ming Lu, Jiawei Gu and Yanxue Wang
Rotating machinery is a crucial component of large equipment, and detecting faults in it accurately is critical for reliable operation. Although fault diagnosis methods based on…
Abstract
Purpose
Rotating machinery is a crucial component of large equipment, and detecting faults in it accurately is critical for reliable operation. Although fault diagnosis methods based on deep learning have been significantly developed, the existing methods model spatial and temporal features separately and then weigh them, resulting in the decoupling of spatiotemporal features.
Design/methodology/approach
The authors propose a spatiotemporal long short-term memory (ST-LSTM) method for fault diagnosis of rotating machinery. The authors collected vibration signals from real rolling bearing and gearing test rigs for verification.
Findings
Through these two experiments, the authors demonstrate that machine learning methods still have advantages on small-scale data sets, but our proposed method exhibits a significant advantage due to the simultaneous modeling of the time domain and space domain. These results indicate the potential of the interactive spatiotemporal modeling method for fault diagnosis of rotating machinery.
Originality/value
The authors propose a ST-LSTM method for fault diagnosis of rotating machinery. The authors collected vibration signals from real rolling bearing and gearing test rigs for verification.
Details
Keywords
Lipeng Pan, Yongqing Li, Xiao Fu and Chyi Lin Lee
This paper aims to explore the pathways of carbon transfer in 200 US corporations along with the motivations that drive such transfers. The particular focus is on each firm’s…
Abstract
Purpose
This paper aims to explore the pathways of carbon transfer in 200 US corporations along with the motivations that drive such transfers. The particular focus is on each firm’s embeddedness in the global value chain (GVC) and the influence of environmental law, operational costs and corporate social responsibility (CSR). The insights gleaned bridge a gap in the literature surrounding GVCs and corporate carbon transfer.
Design/methodology/approach
The methodology comprised a two-step research approach. First, the authors used a two-sided fixed regression to analyse the relationship between each firm’s embeddedness in the GVC and its carbon transfers. The sample consisted of 217 US firms. Next, the authors examined the influence of environmental law, operational costs and CSR on carbon transfers using a quantitative comparison analysis. These results were interpreted through the theoretical frameworks of the GVC and legitimacy theory.
Findings
The empirical results indicate positive relationships between carbon transfers and GVC embeddedness in terms of both a firm’s position and its degree. From the quantitative comparison, the authors find that the pressure of environmental law and operational costs motivate these transfers through the value chain. Furthermore, CSR does not help to mitigate transfers.
Practical implications
The findings offer insights for policymakers, industry and academia to understand that, with globalised production and greater value creation, transferring carbon to different parts of the GVC – largely to developing countries – will only become more common. The underdeveloped nature of environmental technology in these countries means that global emissions will likely rise instead of fall, further exacerbating global warming. Transferring carbon is not conducive to a sustainable global economy. Hence, firms should be closely regulated and given economic incentives to reduce emissions, not simply shunt them off to the developing world.
Social implications
Carbon transfer is a major obstacle to effectively reducing carbon emissions. The responsibilities of carbon transfer via GVCs are difficult to define despite firms being a major consideration in such transfers. Understanding how and why corporations engage in carbon transfers can facilitate global cooperation among communities. This knowledge could pave the way to establishing a global carbon transfer monitoring network aimed at preventing corporate carbon transfer and, instead, encouraging emissions reduction.
Originality/value
This study extends the literature by investigating carbon transfers and the GVC at the firm level. The authors used two-step research approach including panel data and quantitative comparison analysis to address this important question. The authors are the primary study to explore the motivation and pathways by which firms transfer carbon through the GVC.
Details
Keywords
Construction sustainability (CS) is a strategic reaction to the sustainability expectations of the construction industry's external stakeholders. The extant literature has viewed…
Abstract
Purpose
Construction sustainability (CS) is a strategic reaction to the sustainability expectations of the construction industry's external stakeholders. The extant literature has viewed the environmental, social and economic dimensions of CS as having independent effects on financial performance. Due to the influence of common stakeholders, however, interactions in these dimensions will be present in their effect on financial performance. Accordingly, this study identifies the mechanisms of the interactions between the three CS dimensions and how they jointly affect financial performance.
Design/methodology/approach
Content analysis of GRI reports of 60 large construction organisations, followed by a hierarchical regression analysis was used to identify the interactions between environmental, social and economic CS in their effect on financial performance.
Findings
Economic CS was found to indirectly, and not directly, affect financial performance, the effect being mediated by both environmental and social CS. Environmental CS was found to have a strong negative effect on financial performance, whilst social CS was found to have a strongly significant positive effect on financial performance.
Practical implications
The motivation for engaging in CS is that investment in economic CS will have a positive effect on both environmental and social CS outcomes, which, in turn can have a combined effect on financial performance.
Originality/value
This is one of the first studies investigating the effect of interactions between the environmental, social and economic CS dimensions on the financial performance of construction organisations. It is also one of the first studies that applies a sociotechnical framework to this relationship.
Details