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This study aims to use Lean principles, including the traditional seven types of waste and four additional service-specific waste types, to identify and eliminate wasteful activities.

The study integrates existing literature to identify different types of waste and conducts a case study within the Malaysian Customs Administration. The application process flow for License Manufacturing Warehouse is examined, and waste is identified and eliminated using the principles of waste elimination in Lean.

The study identifies eight prevalent types of waste in service processes, with motion being the most common and duplication the least. The case study in the Malaysian Customs Administration reveals no instances of waste in communication and error categories, indicating commendable efficiency in these areas. These insights offer valuable benchmarks for organizations seeking to optimize processes and address specific types of waste.

This paper is crucial for showcasing the practical implementation of waste elimination theory in Lean across the service sector, focusing on the Malaysian Customs Administration. It offers targeted insights into tailoring these principles for real-world efficiency gains, contributing valuable strategies for waste reduction in a specific organizational context.

This research proposes weighted grey relational analysis (WGRA) method to evaluate the performance of 325 multilevel dispatching rules in the wafer fabrication process.

The research methodology involves multilevel dispatching rule generation, simulations, WGRA and result analysis. A complete permutation of multilevel dispatching rules, including the partial orders, is generated from five basic rules. Performance measures include cycle time, move, tool idling and queue time. The simulation model and data are obtained from a wafer fab in Malaysia. Two seasons varying in customer orders and objective weights are defined. Finally, to benchmark performance and investigate the effect of varying values of coefficient, the models are compared against TOPSIS and VIKOR.

Results show that the seasons prefer different multilevel dispatching rules. In Normal season, the ideal first basic dispatching rule is critical ratio (CR) and CR followed by shortest processing time (SPT) is the best precedence pairing. In Peak season, the superiority of the rule no longer heavily relies on the first basic rule but rather depends on the combination of tiebreaker rules and on-time delivery (OTD) followed by CR is considered the best precedence pairing. Compared to VIKOR and TOPSIS, WGRA generates more stable rankings in this study. The performance of multicriteria decision-making (MCDM) methods is influenced by the data variability, as a higher variability produces a much consistent ranking.

As research implications, the application illustrates the effectiveness and practicality of the WGRA model in analyzing multilevel dispatching rules, considering the complexity of the semiconductor wafer fabrication system. The methodology is useful for researchers wishing to integrate MCDM model into multilevel dispatching rules. The limitation of the research is that the results were obtained from a simulation model. Also, the rules, criteria and weights assigned in WGRA were decided by the management. Lastly, the distinguishing coefficient is fixed at 0.5 and the effect to the ranking requires further study.

The research is the first deployment WGRA in ranking multilevel dispatching rules. Multilevel dispatching rules are rarely studied in scheduling research although studies show that the tiebreakers affect the performances of the dispatching rules. The scheduling reflects the characteristics of wafer fabrication and general job shop, such as threshold and look-ahead policies.

In electronics assembly, the losses of electronic components throughout the surface‐mounting process (including kitting and setup) are hard to trace. This affects accurate material planning and manufacturing costing. This paper aims to investigate this issue and to generate a suitable mixture of strategies for the relevant causes.

The project is executed by an undergraduate manufacturing engineering student and several company engineers over a period of ten weeks. Define, measure, analyze, improve, and control (DMAIC) approach delineates the project stages. The solutions devised must be in agreement with lean philosophies and practices currently upheld in the company.

Component losses stem from multiple sources and are complicated by inherent information inaccuracies. A right mixture of strategies is envisaged on analysis on these sources. An average 18 percent of decrement in component losses in monetary value is achieved in the initial 16 weeks of the improvement phase.

The DMAIC approach induces a focused, systematic and thorough study on the selected area. For the limitations, this study is based on a single industrial case. The evidence may be anecdotal and idiosyncratic to the electronics assembly industry. The final solutions which emerged need to factor in the organization current maturities in Lean and Six Sigma concepts.

Component loss is a common problem faced by electronics assembly industries. In this paper, the nature of the problem and the related investigation are extensively illustrated in the context of the case study. As many electronics assembly industries have embarked on Lean or Lean Six Sigma journeys, the savings and data accuracy improvement achieved in this case study provide valuable benchmarks.

The issues related to electronic component losses have not been reported in established literature to date. This is also the first reported success case study of applying DMAIC to address these issues in a lean company.

The purpose of this paper is to introduce an affective computing-based method of identifying sleeping beauties and their princes in five educational technology journals.

This study develops an information technology-based methodology to analyze sleeping beauties in the field of educational technology. The authors seek to determine the characteristics of studies which trigger the awakening of sleeping beauties (called “princes”). The keywords and Hirsch index (H-index) are used as two essential analysis indicators.

Between 2000 and 2015, these five journals included 7,864 articles with a total of 77,700 citations and 24,312 keywords. This study identified articles as being in deep sleep (75.7 percent), less deep sleep (14.7 percent), and awakening (5.5 percent) states. According to the analytical results, 431 of 7,864 articles are qualified as “sleeping beauties.” Of the 431 sleeping beauties identified, 232 articles were awakened by trend princes, while 286 were awakened by H-index princes. A total of 128 sleeping beauties were awakened by both prince types. Besides, impact factors (IFs) of journals do not have a significant effect on the number of sleeping articles.

There are two main research limitations in this study. The first one is the amount of target journals. Only five well-known educational technology journals are analyzed in this research. There may be more valuable sleeping publications in other journals not been found. The second limitation is that the authors merely pick up the lead author of citing papers as the indicator to determine the H-index prince. The contributions of the rest of authors are not taken are not taken into consideration. These limitations should be further studied.

To the knowledge, this study is the first one reporting the identification of sleeping beauty and princes in educational technology field. Furthermore, the authors devise an informational method to determine sleeping publications, sleeping beauty, and princes. A systematic analysis of five well-known journals in the field of educational technology field confirms the existence of “sleeping beauties.” It is reported that improvements to a journal’s IF are positively correlated to increased numbers of sleeping beauties being awakened. To reduce the number of such articles, or to reduce the overall sleeping duration, journal editors should not only seek to raise the journal’s IF, but also strategically select keywords for maximum visibility, and promote articles to high H-index authors.

In a programming course, students often need tutors' assistance to complete learning activities, as they lack enough background knowledge to complete tasks. A further problem is that without individual tutoring, the knowledge gap between students increases. Therefore, the authors have proposed an instant response learning supplement tool (IRLST) to support students' learning, in order to facilitate students' independent problem-solving skills.

The authors divided the students into two groups according to their learning styles: verbal and visual. The IRLST was used to collect and analyze the information on their usage and provide supplementary resources to facilitate their learning. The proposed system also analyzed the student usage, background knowledge and exam scores to assess their academic performance.

According to the results of statistical analysis, students' learning performance improved significantly, especially low-scoring students. Moreover, as compiler messages were not recognized, students tended to identify the same problems. Thus, it is suggested that teachers not only should focus on improving the students' syntax but also strengthening their background knowledge and debugging skills.

There are two main limitations in this study: (1) as most of the students were in the visual learning group, the size of the groups was impacted, thus it was not possible to establish a control group; (2) one specific version of the IRLST system did not send reliable advice or supplementary content occasionally.

The IRLST developed in this study can be used to provide immediate supplementary resources to help students overcoming programming problems and developing problem-solving skills.

The purpose of this paper is, based on leisure constraints and means-end theories, to identify the e-leisure constraints of using the video-sharing websites/apps; demonstrate how means-end theory can be used to reveal the differences between high- and low-leisure constraints in an e-leisure environment; and provide designers and marketers with valuable insights for developing e-leisure products and e-marketing strategies.

Both qualitative and quantitative approaches are employed to collect data. By eliminating three participants whose age range did not meet our criterion (15 to 24 years old), 57 one-on-one in-depth interviews were then content analyzed to design the survey questionnaire. A total of 514 valid samples were collected for hierarchical value map (HVM) construction.

By comparing the full HVM vs the e-leisure constraints HVM, the analytical results indicate that the importance of attributes, consequences and values for the young people using video-sharing websites/apps is quite different. “Unable to resume the video after leaving the screen,” “creating playlist,” “providing movies” and “location restrictions” are extremely important features that influence the willingness of such users with high e-leisure constraints to participate in e-leisure activities. By understanding the differences between these two HVMs, it is possible to provide marketers or designers with valuable insights for website/app design and marketing strategies.

This study only focused on young people’s perceptions of video-sharing websites/apps, so the findings are limited to those aged between 15 and 24 years old. Since managers today are challenged to design effective strategies that can meet target users’ demands across different ages with different economic, social and sub-cultural groups, future research may consider gathering a wider age range of respondents in order to obtain more robust results.

This is the first paper integrating leisure constraints theory and means-end theory to understand young people’s cognitive structure of using video-sharing websites/apps, especially when they encounter e-leisure constraints.

This study aims at exploring users' motives to form attachments within the social Q&A community context and identifying the differences between active users and lurkers when building emotional attachments. By utilizing the media system dependency (MSD) theory, this study investigates into the driving factors of dependency relations (understanding, orientation and play) to user attachments (i.e. attachment to the social Q&A community, attachment to content creators).

The research model is empirically validated by an online questionnaire among users of a social Q&A community. Deriving from the actual behavioral data, the authors divide 262 valid responses into 157 active users and 105 lurkers according to whether they post or not. The partial least squares (PLS) method is exploited to analyze the relationships in the model. In addition, the PLS-based multi-group analysis is conducted for comparing active users and lurkers.

The empirical results confirm that dependency relations (understanding, orientation and play) significantly influence user attachments. Multi-group analysis suggests that the effect of understanding dependency relations on attachment to content creators is stronger for active users than for lurkers. However, the effect of orientation dependency relations on user attachment is significant for lurkers but not significant for active users.

This study enriches the knowledge of the MSD theory by extending it to the social Q&A community setting. Based on the MSD theory, the relationships between three sides of dependency relations and two types of user attachments are hypothesized in the research model. Besides, the impact of user heterogeneity in building user emotional attachment still lacks consideration. This study is one of the first in the field of comparison studies to compare active users and lurkers in such context, providing a novel contribution in understanding the motivations and emotional responses of different users.

Although many universities have begun to provide artificial intelligence (AI)-related courses for students, the influence of the course on students' intention to participate in the development of AI-related products/services needs to be verified. In order to explore the factors that influence students' participation in AI services and system development, this study uses self-efficacy, AI literacy, and the theory of planned behaviour (TPB) to investigate students' intention to engage in AI software development.

The questionnaire was distributed online to collect university students' responses in central Taiwan. The research model and eleven hypotheses are tested using 151 responses. The testing process adopted SmartPLS 3.3 and SPSS 26 software.

AI programming self-efficacy, AI literacy, and course satisfaction directly affected the intention to participate in AI software development. Moreover, course playfulness significantly affected course satisfaction and AI literacy. However, course usefulness positively affected course satisfaction but did not significantly affect AI literacy and AI programming self-efficacy.

The model improves our comprehension of the influence of AI literacy and AI programming self-efficacy on the intention. Moreover, the effects of AI course usefulness and playfulness on literacy and self-efficacy were verified. The findings and insights can help design the AI-related course and encourage university students to participate in AI software development. The study concludes with suggestions for course design for AI course instructors or related educators.

The Communist revolution in China has led to the appearance in this country of increasing numbers of Chinese books in Russian translation. The Chinese names in Cyrillic transcription have presented many librarians and students with a new problem, that of identifying the Cyrillic form of a name with the customary Wade‐Giles transcription. The average cataloguer, the first to meet the problem, has two obvious lines of action, and neither is satisfactory. He can save up the names until he has a chance to consult an expert in Chinese. Apart altogether from the delay, the expert, confronted with a few isolated names, might simply reply that he could do nothing without the Chinese characters, and it is only rarely that Soviet books supply them. Alternatively, he can transliterate the Cyrillic letters according to the system in use in his library and leave the matter there for fear of making bad worse. As long as the writers are not well known, he may feel only faintly uneasy; but the appearance of Chzhou Ėn‐lai (or Čžou En‐laj) upsets his equanimity. Obviously this must be entered under Chou; and we must have Mao Tse‐tung and not Mao Tsze‐dun, Ch'en Po‐ta and not Chėn' Bo‐da. But what happens when we have another . . . We can hardly write Ch'en unless we know how to represent the remaining elements in the name; yet we are loth to write Ch'en in one name and Chėn' in another.

Total quality management (TQM) and knowledge management (KM) are two similar and complementary management philosophies synergistic combinations that can form a cycle of improvement and development. This paper aims to investigate the impact of TQM factors on knowledge creation in the organizations of Bangladesh.

A list of TQM factors was identified through reviewing the relevant literature. Knowledge creation was analyzed through the framework proposed by Nonaka and Takeuchi (1995). Data were collected through a self-administered questionnaire survey among 450 top and mid-level managers of the organizations. A quantitative research approach, namely, structural equation modeling (SEM) was used in the study. The data were analyzed in SmartPLS 3.

From the study, it is found that a positive and significant relationship exists between leadership, employee empowerment, benchmarking, customer focus and information technology with the knowledge creation process and four knowledge conversion modes. In contrast, a negative and significant relationship has been found between employee training and continuous improvement with the knowledge creation process and three knowledge conversion modes.

Previous researches in Bangladesh empirically validated the effect of TQM on organizational performance, competitive advantage, financial performance, market performance and productivity. But, no such study was undertaken to empirically validate the effect of TQM on knowledge creation process for organizations of Bangladesh. Here, the study has a unique contribution. The empirical support for the hypotheses to explain and predict the contribution of the TQM in promoting knowledge creation.

The findings highlight the role of leadership practices. Organizational leadership needs to focus more on following issues: gathering required knowledge from the superior sources; transforming prevailing knowledge into a meaningful format to perform activities in better and innovative ways; employing opinions from experiences; facilitating mechanism for employees to update their knowledge; creating a virtual network; implementing customer relationship management system and providing tools and technologies to employees for performing KM activities more efficiently. On the other hand, negative effect of employee training and continuous improvement on knowledge creation sheds light on understanding the reasons for this kind of relationship and formulating effective strategies to resolve problems inside the organizations. In this regard, employees need to be well equipped through regular and appropriate training. Also, employees need to use problem-solving approach to identify problems inside the organizational system thereby availing opportunities for continuous improvement.

This study was conducted to identify factors that enable knowledge creation in organizations from developing countries like Bangladesh. TQM has been adopted in many organizations. But, its effect was mostly measured to determine its impact on improving organizational performance or competitiveness or identifying its critical success factors of implementation. Hence, this study sheds light on identifying the effect of TQM from a new perspective.