bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of supportive work environment on employee retention: the mediating role of person–organisation fit
Authors: Yusliza Mohd Yusoff , Noor Faezah Juhari , Ali Nora’aini , Mohamad Noor Noor Maizura , Ramayah T. , Tanveer M. Imran , Fawehinmi Olawole 
Published: February 2021

PurposeThis study aims to examine the relationships for the following: supportive work environment, person–organisation fit and employee retention among academic staff in one of the Malaysian public universities.Design/methodology/approachThis study used a conceptual framework to assess the direct impacts of supportive work environment (i.e. perceived climate, supervisory relationship, peer group interaction, perceived organisational support), person–organisation fit and employee retention. A self-administered questionnaire was distributed to 225 respondents.FindingsThe findings present the mediating influence of person–organisation fit on the relationships between supportive work environment and employee retention. The results reveal a direct and positive relationship between supportive work environment and academic staff retention. These results imply that individuals’ perceived towards an organisation can influence their decision to stay at the university.Research limitations/implicationsThis study had filled in the knowledge gap about the role of supportive work environment with person–organisation fit and the relationship for employee retention in Malaysia. Previous research emphasised on organisations’ role in employee retention and engagement in the manufacturing and service industry.Originality/valueThe findings of this study reveal how a supportive work environment can impact employee retention among academic staff. Specifically, the person–organisation fit describes the relationship between supportive work environment and employee retention.
Ensemble learning-based CNN for textile fabric defects classification
Authors: Zhao Xueqing , Zhang Min , Zhang Junjun 
Published: February 2021

PurposeClassifying the types of fabric defects in the textile industry requires a way to effectively detect. The traditional textile fabric defects detection method is human eyes, which performs very low efficiency and high cost. Therefore, how to improve the classification accuracy of textile fabric defects by using current artificial intelligence and to better meet the needs in the textile industry, the purpose of this article is to develop a method to improve the accuracy of textile fabric defects classification.Design/methodology/approachTo improve the accuracy of textile fabric defects classification, an ensemble learning-based convolutional neural network (CNN) method in terms of textile fabric defects classification (short for ECTFDC) on an enhanced TILDA database is used. ECTFDC first adopts ensemble learning-based model to classify five types of fabric defects from TILDA. Subsequently, ECTFDC extracts features of fabric defects via an ensemble multiple convolutional neural network model and obtains parameters by using transfer learning method.FindingsThe authors applied ECTFDC on an enhanced TILDA database to improve the robustness and generalization ability of the proposed networks. Experimental results show that ECTFDC outperforms the other networks, the precision and recall rates are 97.8%, 97.68%, respectively.Originality/valueThe ensemble convolutional neural network textile fabric defect classification method in this paper can quickly and effectively classify textile fabric defect categories; it can reduce the production cost of textiles and it can alleviate the visual fatigue of inspectors working for a long time.
Impact of artificial intelligence on impulse buying behaviour of Indian shoppers in fashion retail outlets
Authors: Jain Shailesh , Gandhi Aradhana Vikas 
Published: February 2021

PurposeThis paper aims to understand the impact of modern technologies such as artificial intelligence on impulse buying behaviour of Indian shoppers specifically in fashion retail outlets.Design/methodology/approachThe empirical study on the effect of artificial intelligence on impulse purchase decisions was conducted through an e-survey of the Indian shoppers. The data collected was analysed using factor analysis and multiple regression analysis.FindingsThe impact of modern technologies which are used by the retailers to enhance sale and consumer engagement was studied. The relationship between use of artificial intelligence parameters such as the purchase duration, recommended products, product information and human interaction and its impact on Impulse Purchase was studied and the results revealed that all these factors except product information had a significant impact on the impulse purchase decision of the buyer.Practical implicationsThis study will be useful to the fashion retailers to gauge the effect of incorporating artificial intelligence and its impact on driving sales by attracting shoppers to their outlets.Originality/valueThis study specifically focusses on the impact of modern technologies on impulse purchase of Indian shoppers in fashion retail outlets. Other research works have focussed on impact of visual merchandising, store layouts, store environment and promotional activities on impulse purchases. This is one of the few studies which deals with the impact of artificial intelligence on impulse buying behaviour of Indian shoppers specifically in the fashion retail segment.
Electroencephalogram (EEG) signal classification for brain–computer interface using discrete wavelet transform (DWT)
Authors: Rajashekhar U. , Neelappa D. , Rajesh L. 
Published: February 2021

PurposeThis work proposes classification of two-class motor imagery electroencephalogram signals using different automated machine learning algorithms. Here data are decomposed into various frequency bands identified by wavelet transform and will span the range of 0–30 Hz.Design/methodology/approachStatistical measures will be applied to these frequency bands to identify features that will subsequently be used to train the classifiers. Further, the assessment parameters such as SNR, mean, SD and entropy are calculated to analyze the performance of the proposed work.FindingsThe experimental results show that the proposed work yields better accuracy for all classifiers when compare to state-of-the-art techniques.Originality/valueThe experimental results show that the proposed work yields better accuracy for all classifiers when compare to state-of-the-art techniques.
Digital tools to support teacher professional development in lesson studies: a systematic literature review
Authors: Hrastinski Stefan 
Published: February 2021

PurposeLesson study is one of the most adopted models of teacher professional development. However, as education has become increasingly digital, this study aims to investigate the use of digital tools to support teacher professional development in lesson studies.Design/methodology/approachThis article systematically reviews journal articles on the use of digital tools to support teacher professional development in lesson studies.FindingsWhile the lesson study model is typically based on the premise that teachers prepare and observe a lesson at a school, the reviewed research suggests that digital tools open new ways to conduct lesson studies. Six themes on the use of digital tools to support teacher professional development in lesson studies are identified: analyzing videos from the teachers' classrooms, analyzing external video resources, fictional animations as a complement to videos, structured digital lesson study work, hybrid teacher collaboration and digital teacher collaboration. Opportunities for further research are suggested.Practical implicationsThe identified themes can inspire practice on how to use digital tools to support teacher professional development in lesson studies.Originality/valueLittle attention has been paid to the use of digital tools to support teacher professional development in lesson studies.
Blockchain as supply chain technology: considering transparency and security
Authors: Xu Pei , Lee Joonghee , Barth James R. , Richey Robert Glenn 
Published: February 2021

PurposeThis paper discusses how the features of blockchain technology impact supply chain transparency through the lens of the information security triad (confidentiality, integrity and availability). Ultimately, propositions are developed to encourage future research in supply chain applications of blockchain technology.Design/methodology/approachPropositions are developed based on a synthesis of the information security and supply chain transparency literature. Findings from text mining of Twitter data and a discussion of three major blockchain use cases support the development of the propositions.FindingsThe authors note that confidentiality limits supply chain transparency, which causes tension between transparency and security. Integrity and availability promote supply chain transparency. Blockchain features can preserve security and increase transparency at the same time, despite the tension between confidentiality and transparency.Research limitations/implicationsThe research was conducted at a time when most blockchain applications were still in pilot stages. The propositions developed should therefore be revisited as blockchain applications become more widely adopted and mature.Originality/valueThis study is among the first to examine the way blockchain technology eases the tension between supply chain transparency and security. Unlike other studies that have suggested only positive impacts of blockchain technology on transparency, this study demonstrates that blockchain features can influence transparency both positively and negatively.
Sustainability balanced scorecard architecture and environmental performance outcomes: a systematic review
Authors: Jassem Suaad , Zakaria Zarina , Che Azmi Anna 
Published: February 2021

PurposeThis study aims to assess the current state of research on the use of sustainability balanced scorecards (SBSCs), as they relate to environmental performance-related outcomes. It also seeks to present a conceptual framework proposing relationships between SBSC and environmental performance.Design/methodology/approachThis paper conducts a systematic literature review of articles published in double-blind peer-reviewed journals that are listed on Scopus and/or Web of Science databases.FindingsThe first part of the paper reveals that two architectures of SBSC appear to be dominant in the literature (SBSC-4 where sustainability parameters are integrated with the four perspectives of the balanced scorecard and SBSC-5 where sustainability is shown as an additional standalone fifth perspective). The next part of the paper presents a conceptual model relating SBSC as decision-making tools to environmental performance outcomes. The paper also indicates that SBSC knowledge mediates the above relationships. Furthermore, based on the theory of expert competence, the presence of experts possibly moderates the relationship between SBSC architecture and environmental performance outcomes.Research limitations/implicationsThe literature indicates a lack of consensus on establishing a clear linkage on the relationship between SBSC architecture and environmental performance outcomes. As a result, a holistic conceptual framework where SBSC knowledge acts as a mediator and presence of experts as a moderator may be able to provide a more consistent relationship between SBSC architecture and environmental performance outcomes.Practical implicationsThe conceptual framework proposed provides factors to be considered by decision makers, for effective outcomes when aiming to achieve environmental stewardship objectives.Social implicationsEnvironmental performance by business organisations have come under close scrutiny of stakeholders. As a result, the holistic model proposed in the current study may pave the path for decision-makers to achieve superior environmental outcomes, leading to greater satisfaction of stakeholders such as the communities that are impacted by the business operations of an organisation.Originality/valueThis is the first paper to propose a model for future research regarding the link between SBSC and environmental performance outcomes – with expert managers acting as moderators and SBSC knowledge acting as a mediator.
Multi-objective optimization of safety instrumented systems maintenance strategy: a case study
Authors: Touahar Hafed , Ouazraoui Nouara , Khanfri Nor El Houda , Korichi Mourad , Bachi Bilal , Boukrouma Houcem Eddine 
Published: February 2021

PurposeThe main objective of safety instrumented systems (SISs) is to maintain a safe condition of a facility if hazardous events occur. However, in some cases, SIS's can be activated prematurely, these activations are characterized in terms of frequency by a Spurious Trip Rate (STR) and their occurrence leads to significant technical, economic and even environmental losses. This work aims to propose an approach to optimize the performances of the SIS by a multi-objective genetic algorithm. The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).Design/methodology/approachThe optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).FindingsA case study concerning a safety instrumented system implemented in the RGTE facility has shown the great applicability of the proposed approach and the results are encouraging. The results show that the selection of a good maintenance strategy allows a very significant minimization of the PFDavg, the frequency of spurious trips and Life Cycle Costs of SIS.Originality/valueThe maintenance strategy defined by the system designer can be modified and improved during the operational phase, in particular safety systems. It constitutes one of the least expensive investment strategies for improving SIS performances. It has allowed a considerable minimization of the SIS life cycle costs; PFDavg and the frequency of spurious trips.
New framework for the management of waqf land registration system in Malaysia
Authors: Ghazali Noor Azimah , Sipan Ibrahim , Haji Mohammad Mohammad Tahir Sabit , Ab Aziz Muhammad Arif 
Published: February 2021

Purpose
This paper aims to propose a new framework for the management of a waqf land registration system in Malaysia that is compliant with Islamic law and the Malaysian legal system. The study sought to answer the following two research questions: what are the issues of the waqf land registration system and how to solve the issues of waqf land registration in Malaysia.

Design/methodology/approach
This study used a qualitative research method by using content analysis, legal investigation and doctrinal research. Data were collected through semi-structured interviews with lawyers, academicians and executive officers from the Department of Land and Mines, the State Islamic Religious Council and reviewed documents mainly from the Department of Waqf, Zakat and Hajj Malaysia.

Findings
A new framework for the management of waqf land registration in Malaysia was identified, which was developed based on current waqf issues such as problematic registration methods, lengthy and complicated procedures, interference in the jurisdiction of the civil court and idle waqf land. The framework overcame the flaw of the previous waqf land registration system in Malaysia.

Originality/value
The new framework will provide solutions to the current registration system within the National Land Code, 1965, which will secure property in the future.
Enhancing supply chain sensing capability through social media: an environmental scanning perspective
Authors: Song Jiahe , Lee Kang-Bok , Zhou Zhongyun , Jia Lin , Cegielski Casey , Shin Soo Il 
Published: February 2021

PurposeThe purpose of this study is to investigate the relationship between social media and sensing capability for supply chain management (SCM) from an environmental scanning perspective. The authors consider upstream supply and downstream customer markets as two aspects of social media-enabled environmental scanning (SMES). The moderating effects of three uncertainties are explored.Design/methodology/approachThe data were collected from 178 supply chain professionals through a survey. Generalized estimating equations (GEE) were used to analyze the data.FindingsSMES in both supply and customer markets enhance sensing capability. Interestingly, the results reveal an accelerating effect on sensing by the incremental effort of SMES-supply. However, that of SMES-customer leads to a decelerating outcome for sensing. Also, uncertainties, especially the demand- and technology-related, play a series of interacting effects according to SMES levels.Research limitations/implicationsThis research contributes to the literature of operations and supply chains regarding social media strategies and dynamic capabilities. It opens the black box of environmental scanning behavior on social media and adds new knowledge on the dynamic influence of such behavior toward organizational sensing capability for SCM. In addition, further understanding on supply chain uncertainty as a moderator is also strengthened through this research.Originality/valueThis research is the first to empirically uncover the effect of social media on sensing capability for SCM through the lens of environmental scanning. The results support the employment of social networking for improving supply and demand sensing.
Digital storytelling with chatbots: mapping L2 participation and perception patterns
Authors: Bailey Daniel , Southam Ashleigh , Costley Jamie 
Published: February 2021

Purpose
This study aims to increase language learning (L2) output by incorporating a digital storytelling chatbot system (known as a “storybot”) that focused interactions on a narrative. This study also sought to investigate student perceptions of these storybot interactions and improve on poor perception rates from previous studies.

Design/methodology/approach
This one-sample exploratory study was of student-storybot participation rates and student perceptions towards a storybot activity designed to increase L2 output. A combination of storybot participation analytics and survey analysis of student perception was carried out.

Findings
The use of storybots in the L2 class resulted in mixed participation rates. Students read nine times more than they wrote, indicating a high degree of reading comprehension necessary for storybot interaction. Survey results revealed that students believed storybots helped them meet their L2 goals, were relevant to their L2 and were easy to navigate.

Research limitations/implications
Interactions were through text messaging so no impact on speech or pronunciation could be observed. Further, the context was within a single university class in South Korea, restricting the generalization of findings to outside regions or with younger learners. Finally, while storybots proved to be valuable reading comprehension activities, the next step in this line of chatbot research should incorporate more writing prompts.

Practical implications
Storybots revealed explicit benefits to reading comprehension, as measured by cohesion between storybot delivered comprehension questions and student responses. Moreover, storybots can be used as examples for students in their own story creation, classroom forms to collect relevant student information regarding learning objectives and platforms for class quizzes.

Social implications
Storybots scaffold students through conversations, which abide by socio-pragmatic norms, providing models for L2 learners to incorporate in real-world text-based communication. Additionally, a wide range of idiomatic expressions is contextualized in comprehensible interactions that students can learn from the storybot then practice with friends.

Originality/value
This study contributes to the growing research on the use of chatbots for second L2 and offers specific insight into the use of narrative storybots as a means to increase L2 output and potentially benefit L2 reading comprehension.
The impact of corporate governance on the relationship between earnings management and CEO compensation
Authors: Assenso-Okofo Oheneba , Jahangir Ali Muhammad , Ahmed Kamran 
Published: February 2021

PurposeThe study examines whether corporate governance moderates the relationship between CEO compensation and earnings management.Design/methodology/approachThe study uses 1,800 firm-year observations from 2005 to 2010 and employ multiple regression analyses and other sensitivity tests.FindingsThe study finds a positive relationship between CEO compensation and earnings management. The study’s results also suggest that CEO bonus compensation increases in relation to earnings management and therefore the study infers that managers may become involved in earnings management to increase their compensation. However, the study finds that the relationship is moderated by a strong corporate governance system which reduces the impact of earnings management on CEO compensation.Research limitations/implicationsThe study is conducted in a specific context, and therefore it may be subject to a set of limitations. The study emphasises exclusively on whether executives manage earnings to increase their compensation. The study does not consider the issue of several other and potentially contradictory motivations here.Practical implicationsThe study’s findings highlight potential implications and offer useful propositions for stakeholders, particularly accounting and corporate governance regulators, to consider. The findings offer a basis for the accounting professions to further discuss and improve accounting standards to provide adequate regulations and monitoring to decrease managerial opportunistic behaviours in earnings manipulations. The findings also emphasise the need for appropriately designed CEO compensation packages in such a manner that improves the manager–shareholder alignment and reduces the information asymmetry problem. The results signify that corporate governance plays a vital role in mitigating the relationship between CEO compensation and earnings management.Originality/valueThis study adds to the existing literature by documenting empirical support on the link between earnings management and CEO compensation against a backdrop of high demand for strong corporate governance practices.