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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.

The purpose of this paper is to evaluate the impact of delivering healthy eating messages through an interactive health corner (HC) on improving healthy dietary habits in participants.

Self-administered questionnaires were administered to participants after the education session. In total, 5,292 valid questionnaires were obtained, yielding a response rate of 93.3 per cent. In the last three months of the pilot study, a random sample of 305 from 1,493 participants was chosen and followed up six months later. Bivariate analysis was used to study the association of knowledge gained and attitude. Behavioural change was measured in terms of whether participants had reported an increase in their consumption of healthier food.

Majority (>98 per cent) of participants reported that the HC corner was useful, and had helped increase their awareness and knowledge of creating healthier meals and making healthier food choices. 95.7 per cent were willing to make changes after visiting the HC. At six months follow-up, 84 per cent of the participants reported positive changes in their dietary habits. Those who made positive changes were younger (mean age: 58.0 years) compared with those who did not (mean age 61.0 years, p=0.035).

Incorporating cooking demonstrations as part of nutrition education is effective in inculcating healthy eating practices and changing self-reported eating habits in the short term. Further research is needed to verify actual change in eating habits and to determine if this change is sustainable in the long run.

Currently, no similar initiative has been implemented and studied to evaluate the effectiveness of this mode of health promotion in a primary care setting. This study will help the authors to evaluate if the intervention was effective in changing attitudes and behaviours after an education session at the HC.

There are over 300,000 male migrant workers in Singapore. Around 600 major workplace injuries are reported in Singapore each year, mainly in the manufacturing and construction injuries. Migrant workers who are affected by workplace injuries often face many challenges, including not being able to work and thus may be repatriated to their home countries, which affects their financial status and that of their families, whom they support. This research aims to explore the knowledge, attitudes and beliefs of injured migrant workers in Singapore, towards disability and vocational rehabilitation.

Fifteen male migrant workers, from Bangladesh, China and India, who had acquired disabling injuries in their workplaces in Singapore, were identified through purposive sampling. They were interviewed by a male interviewer, either in Mandarin Chinese or with the assistance of interpreters for Bengali-English and Tamil-English. Interviews were recorded, transcribed, translated to English, then analysed thematically.

The interviewees generally had a pessimistic outlook on their disability, which often impacted negatively on their self-worth and familial relationships. Many of them also had little knowledge of vocational rehabilitation and had not yet seriously considered future job prospects.

To the best of the authors’ knowledge, there are no similar studies exploring the knowledge, attitudes and beliefs of injured migrant workers in Singapore towards disability and vocational rehabilitation.

Generally, this paper aims to develop a model by identifying factors which will assist policy makers in implementing m-government in Tanzania. The paper identifies direct and indirect factors which may influence adoption of m-government among the rural farmers in Tanzania.

The paper conducted a survey by using Drop Off/Pick Up method to collect data from rural farmers. Stratified and multi-stage sampling were used to collect 407 valid responses from rural farmers in Tanzania. Data collected were analyzed by using structural equation modeling (SEM).

The results show that government support has direct influence, while awareness has indirect influence through relative advantage, ease of use, compatibility and visibility. Furthermore, relative advantage, compatibility, ease of use, visibility and results demonstrability have direct influence on rural farmers intention to adopt m-government.

This study contributes to knowledge because no study in this area has been conducted in developing countries to examine factors that influence adoption of m-government. Furthermore, this study tests the mediating effects of perceived characteristics of innovation which have not yet been investigated to date.

Successful businesses demand high-performing human resource management practices (HRMP) and effective knowledge management capacity (KMC) to enhance the overall organizational performance. Rapid growth of both local and multinational companies operating in knowledge-intensive industries has increased the global competition in the labor market, also for the developing economies. Therefore, attracting valuable human capital, retaining talents and managing effectively knowledge to deliver on the latest technologies and innovative solutions and services are the biggest challenges in the modern IT industry. The purpose of this paper is to examine the influence of HRMP on KMC through a cross-case analysis including four companies operating in Indian IT sector. Based on the existing studies in this field, five key HRMP have been identified (i.e. recruitment and selection, training and development, compensation and reward, employee retention and career development), as well as two key processes supporting the KMC (i.e. knowledge acquisition and knowledge sharing).

The paper adopts a qualitative research method based on a multiple case study, and it uses primary and secondary data collected through desk research and field interviews.

Results show the existence of HRMP aiming to enhance the individual learning, motivation and retention of employees for knowledge acquisition and knowledge sharing, in the strategic perspective to improve the organizational performance.

The paper presents some limitations, which may provide scope for future research. First, being the study a qualitative multiple case analysis, a more extensive research is needed to generalize the results and investigate further relationships existing between HRMP and KMC. Moreover, a deep investigation on the organizational performance dimensions (e.g. sales growth, cash turnover, financial goal achievement) is required to verify the existence of possible links. Finally, a further limit consists in considering only knowledge acquisition and knowledge-sharing processes, excluding another crucial knowledge management (KM) process such as knowledge application. As for the research implications, the paper contributes to investigate the role of HRMP in supporting KMC in Indian IT companies, which represents a context of research not so much investigated.

From a practitioner point of view, the study can be helpful to HR and KM managers for motivating employees to undertake learning processes and enhance their performance, as well as to acquire and share knowledge resources that are useful for the organization to remain innovative and stay competitive.

As the influence of HRMP on KMC has not been widely studied in the Indian IT industry, the study may open the field for further studies on a deeper investigation of the relationships existing between human resources management (HRM), KM and organizational performance in knowledge-intensive industries in India and, more in general, in developing economies.

Drawing on the third-person effect (TPE) theory and the theory of planned behavior (TPB) as a theoretical framework, the current study aims to explore the cognitive mechanisms behind how third-person perception (TPP) of misinformation about public health emergencies affects intention to engage in corrective actions via attitude, subjective norms and perceived behavioral control.

A total of 1,063 participants in China were recruited via a professional survey company (Sojump) to complete an online national survey during the outbreak of coronavirus (COVID-19) in China. Structural equation modeling using Mplus 7.0 was used to address the research hypotheses.

The results reveal that attention to online information about public health emergencies significantly predicted TPP. In addition, TPP positively influenced attitude and perceived behavioral control, which, in turn, positively encouraged individuals to take corrective actions to debunk online misinformation. However, TPP did not significantly influence subjective norms. A potential explanation is provided in the discussion section.

The research extends the TPE theory by providing empirical evidence for corrective actions and uncovers the underlying cognitive mechanism behind the TPE by exploring key variables of the TPB as mediating constructs. These are all significant theoretical contributions to the TPE and offer practical contributions to combating online misinformation.

The research extends the TPE theory by providing empirical evidence for a novel behavioral outcome (i.e. corrective actions in response to misinformation) and uncovers the cognitive mechanism underlying the TPE by exploring key variables of the TPB as mediating constructs. These are all significant theoretical contributions to the TPE and offer practical contributions to combating online misinformation.

The purpose of this paper is to identify various risk drivers which affect a food processing supply chain and to create a map of how those risk drivers propagate risks through the supply chain and impact important performance measures.

This study involves experts from food processing companies to elucidate the contextual relationships among the risk drivers and between risk drivers and performance measures. This is used to quantify the relationships and to determine the indirect and overall relationships applying Fuzzy Interpretive Structural Modeling.

Three categories of risk drivers which Indian food processing companies need to pay maximum attention to minimize risks are identified. These are supplier dependency and contracting, supplier variability, visibility and traceability and manufacturing disruptions. Analysis shows that collaborating with suppliers and logistics service providers, developing mutually beneficial contracts with them while ensuring that adequate technology investments are made can significantly mitigate risks and consequently improve margins and lead to revenue growth.

This study has been carried out with experts from large food processing companies in India, and hence, the results cannot be generalized across other types of food processing companies.

The proposed methodology can help understand the interrelationships between supply chain risks and between those risks and performance measures. Thus, it can help a food processing company to create business cases for specific supply chain risk mitigation projects.

This study is one of the earliest to create a comprehensive risk propagation map for food processing companies which helps in quantifying the impact the risk drivers have on each other and on performance measures.

Although well established in North America and Europe, the study of supply chain management (SCM) is still at a relatively early stage in its development in China. The transformation and rapid growth of the Chinese economy has, nevertheless, created major supply chain challenges for the country making SCM a very fertile area of business research. In Western countries, research on SCM is now mature and underpinned by a solid body of theory. The purpose of this paper is to examine the extent to which research on SCM in China has also developed a theoretical basis.

The research involved a systematic review of 150 papers published in 18 journals in the fields of SCM, logistics, operations management and marketing during the period 2004-2014. A three-step process was adopted to select appropriate journals, identify relevant articles and classify them in terms of their theoretical content.

The study has confirmed that, because of its unique economic, political and cultural setting, supply chain development in China has presented new research challenges. Many examples were found of researchers conducting quasi-experiments to test the applicability of established theories to Chinese supply chains while others have tried to develop new ones that are more closely aligned with the Chinese economy and management practices. Researchers have exhibited a heavy reliance on existing theories, with relatively few attempting to customise them to the Chinese context or to construct new ones.

Given the broad scope of SCM, it is possible that the journal and paper selection processes have accidentally screened out relevant papers. The total sample of papers is, nevertheless, large for an explorative study of this type and should, therefore, give an overall impression of the level of theory development in Chinese SCM research.

This study provides a general framework within which to assess the application and development of theories in the Chinese SCM context. It is principally concerned with three components: the SCM phenomena studied, the Chinese business environment and the theoretical contribution of the research. The paper is targeted more at an academic audience than practitioners, though provides an overview of the research so far undertaken on SCM in China that should be of wider interest.

This study is the first of its kind to review China-based SCM research systematically from the perspective of theory development. It should support the evolution of SCM theory not only in China but also more generally.

The service industry is facing the huge impact of digital transformation, in which artificial intelligence (AI) plays one of the most important roles. This study aims to expand the understanding of the AI acceptance framework and confirm whether consumers’ digital skills have a moderating effect on the research model.

Hypotheses were tested using a data set of 1,641 individuals. Partial least squares structural equation modeling and multi-group analysis were used to estimate the model.

The results indicate that antecedent factors influence consumers’ willingness to use AI devices in services. The two groups of different digitally savvy respondents differ because the influence of anthropomorphism, social influence and hedonic motivation on respondents’ perceived efforts to use AI devices in service delivery depends on respondents’ digital skills.

The novel contribution of this study is reflected in a comprehensive model that explains the moderating effect of individual digital skills on willingness to use AI devices. The attitudes of experienced and digitally skilled consumers are valuable and highlight some important theoretical, practical implications and future lines of research.