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Safe food-handling media campaigns have been successful at improving some safe food-handling behaviours among consumers. However, little is known about whether specific mechanisms of change, such as habit and perceived risk, can improve the effectiveness of safe food-handling campaign materials. Consequently, this study aims to determine if habit and risk-based behaviour change techniques can improve the effectiveness of safe food-handling media campaign materials.

A prospective experimental design was used. Participants completed baseline measures of habit, perceived risk and behaviour before watching two short safe food-handling video advertisements. Participants were then randomly assigned to complete either a habit or a perceived risk-based behaviour change technique task. Two weeks later, participants completed the baseline measures again. A series of multivariate analyses of variance were conducted to determine differences over time between the two groups in relation to habit, perceived risk and behaviour.

Significant increases in habit (p < 0.001), perceived risk (p < 0.001) and behaviour (p < 0.001) among all participants were found over the study period. However, there were no significant differences in these changes between participants who completed either task for the majority of the target behaviours and related constructs. This suggested that both habit and risk-based behaviour change techniques may help improve campaign materials; however, future research is needed to determine these effects in comparison to a non-active control group.

To the best of the authors’ knowledge, this is the first study to compare the use of two behaviour change techniques for improving safe food-handling health messaging materials. Future safe food-handling media campaigns would benefit from including habit and risk-based behaviour change techniques.

The outbreak of the pandemic makes it more difficult to manage the safety or health of construction workers in infrastructure construction. Risk events in construction workers' material handling tasks are highly relevant to workers' work-related musculoskeletal disorders. However, there are still many problems to be resolved in recognizing risk events accurately. The purpose of this research is to propose an automatic and non-invasive recognition method for construction workers in material handling tasks during the pandemic based on smartphone and machine learning.

This research proposes a method to recognize and classify four different risk events by collecting specific acceleration and angular velocity patterns through built-in sensors of smartphones. The events were simulated with anterior handling and shoulder handling methods in the laboratory. After data segmentation and feature extraction, five different machine learning methods are used to recognize risk events and the classification performances are compared.

The classification result of the shoulder handling method was slightly better than the anterior handling method. By comparing the accuracy of five different classifiers, cross-validation results showed that the classification accuracy of the random forest algorithm was the highest (76.71% in anterior handling method and 80.13% in shoulder handling method) when the window size was 0.64 s.

Less attention has been paid to the risk events in workers' material handling tasks in previous studies, and most events are recorded by manual observation methods. This study provided a simple and objective way to judge the risk events in manual material handling tasks of construction workers based on smartphones, which can be used as a non-invasive way for managers to improve health and labor productivity during the pandemic.

This empirical study explores the profound impact of management functions on the productivity of yard cargo handling equipment within container terminals.

By closely examining crucial management aspects such as planning, organizing, leading, and controlling, a comprehensive managerial behavior framework was developed through focus group studies (FGS) and focal interviews. These qualitative methods were complemented by the distribution of questionnaires to practitioners in Vietnam. To validate the concept of management functions and analyze their influence on effective management practices for equipment efficiency, a structural equation model (SEM) technique was employed using partial least-squares estimation (PLS).

The findings of this study demonstrate that planning (PL), organizing (OR), and controlling (CT) significantly contribute to the productivity of yard cargo handling equipment, while leading (LD) does not exhibit a direct positive impact.

Theoretically, this study contributes by providing clarity to the definition, purpose, and value of management functions in the field of cargo handling equipment management. Furthermore, these research findings offer valuable insights to terminal operators and managers, enabling them to optimize their management strategies and enhance productivity levels, ultimately resulting in improved operational outcomes.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

In business-to-business interactions, conflicts are inevitable, and conflict-handling strategies that consider different variables improve the decision-making process of actors. This study aims to reveal the role of power and criticality in conflict-handling research in logistics service networks.

A 2 × 2 between-subject experimental design with four different scenarios was used. One hundred sixty logistics service actors completed an online questionnaire. Data were analyzed with ANOVA and paired sample t-tests using the SPSS 28.0 program.

In comparative scenarios involving high and low power dynamics, individuals with high power and high criticality situations are more inclined to favor the dominating strategy compared to low-power and low-criticality contexts. However, when faced with specific circumstances characterized by both high power and high criticality, actors tend to prioritize the integrating strategy initially, followed by the dominating and obliging strategies in that order. Notably, the statistical analysis revealed no significant interaction effect between criticality and power concerning the integrating, obliging and dominating conflict-handling strategies.

This study used an experimental approach to investigate criticality and power as contextual elements in determining conflict-handling strategies in an inter-firm environment within logistics service networks. This study is particularly groundbreaking in its knowledge of the relationship among power dynamics, conflict criticality and conflict-handling strategies.

In a kitting supply system, the occurrence of material-handling errors is unavoidable and will cause serious production losses to an assembly line. To minimize production losses, this paper aims to present a dynamic scheduling problem of automotive assembly line considering material-handling mistakes by integrating abnormal disturbance into the material distribution problem of mixed-model assembly lines (MMALs).

A multi-phase dynamic scheduling (MPDS) algorithm is proposed based on the characteristics and properties of the dynamic scheduling problem. In the first phase, the static material distribution scheduling problem is decomposed into three optimization sub-problems, and the dynamic programming algorithm is used to jointly optimize the sub-problems to obtain the optimal initial scheduling plan. In the second phase, a two-stage rescheduling algorithm incorporating removing rules and adding rules was designed according to the status update mechanism of material demand and multi-load AGVs.

Through comparative experiments with the periodic distribution strategy (PD) and the direct insertion method (DI), the superiority of the proposed dynamic scheduling strategy and algorithm is verified.

To the best of the authors’ knowledge, this study is the first to consider the impact of material-handling errors on the material distribution scheduling problem when using a kitting strategy. By designing an MPDS algorithm, this paper aims to maximize the absorption of the disturbance caused by material-handling errors and reduce the production losses of the assembly line as well as the total cost of the material transportation.

This research investigates the role of customer forgiveness as the result of online service recovery transparency in predicting customer engagement. It also examines the moderating roles of timeliness and personalization in this proposed model.

An online survey study using retrospective experience sampling and a scenario-based experimental study were conducted to test the proposed hypotheses.

Customer forgiveness positively influences customer engagement and plays a mediating role in the relationship between service recovery transparency and customer engagement. Additionally, timeliness and personalization moderate the positive influence of service recovery transparency on customer forgiveness. The positive influence of service recovery transparency on customer forgiveness is more apparent when levels of timeliness and personalization decrease.

To retain focal customers' engagement after a service failure, firms must obtain their forgiveness. One of the firm's online complaint handling strategies to increase the forgiveness level of focal customers is to provide a high level of service recovery transparency (i.e. responding to their complaints in a public channel), especially when the firm is unable to respond to online complaints quickly or provide highly personalized responses.

This research provides new insights into the underlying mechanism of customer engagement by applying the concept of customer forgiveness. It also contributes to the social influence theory by applying the essence of the theory to explain how other customers' virtual presence during the online complaint handling influences the forgiveness of focal customers in order to gain their engagement. Additionally, it provides insight into the conditions under which the role of service recovery transparency can be very effective in dealing with online complaints.

In 2020, an outbreak of Salmonella Stanley linked to imported dried wood ear mushrooms affected 55 individuals in the United States of America. These mushrooms, commonly used in Asian cuisine, require processing, like rehydration and cutting, before serving. The US Centres for Disease Control and Prevention advise food preparers to use boiling water for rehydration to inactivate vegetative bacterial pathogens. Little is known about how food handlers prepare this ethnic ingredient and which handling procedures could enable Salmonella proliferation.

This study used content analysis to investigate handling practices for dried wood ear mushrooms as demonstrated in YouTube recipe videos and to identify food safety implications during handling of the product. A total of 125 Chinese- and English-language YouTube videos were analysed.

Major steps in handling procedures were identified, including rehydration, cutting/tearing and blanching. Around 62% of the videos failed to specify the water temperature for rehydration. Only three videos specified a water temperature of 100 °C for rehydrating the mushrooms, and 36% of the videos did not specify the soaking duration. Only one video showed handwashing, cleaning and sanitising of surfaces when handling the dried wood ear mushrooms.

This study found that most YouTube videos provided vague and inconsistent descriptions of the rehydration procedure, including water temperature and soaking duration. Food preparers were advised to use boiling water for rehydration to inactivate vegetative bacterial pathogens. However, boiling water alone is insufficient to inactivate all bacterial spores. Extended periods of soaking and storage could be of concern for spore germination and bacterial growth. More validation studies need to be conducted to provide guidance on how to safely handle the mushrooms.

This study will make a distinctive contribution to the field of food safety by being the first to investigate the handling procedure of a unique ethnic food ingredient, dried wood ear mushrooms, which has been linked to a previous outbreak and multiple recalls in the United States of America. The valuable data collected from this study can help target food handling education as well as influence future microbial validation study design and risk assessment.

Saudi Arabia's 2030 vision targets an increase of 34% in non-oil revenue participation in the GDP, thus the need for automation and digital transformation. The Company ER is a market leader producing high-quality dairy products in the Kingdom and is a pioneer in the production industry. The company has recently increased the capacity of its milk factory to meet its vision. An investment was made to automate the pallet handling procedures at the milk factory to provide increased production for daily consumption. The new automation transition in Company ER's milk factory provides a unique opportunity to utilize lean management tools to improve the current automated processes before commercialization.

OEE (overall equipment effectiveness) will monitor losses for different operational losses in the new automated system and indicate system improvements, with 85% as the target. Based on DMADV (design, measure, analyze, design and validate) methodology, this study analyzes the entire automated pallet handling system. It uses lean tools to identify areas for improvement, identify waste elements and propose solutions to achieve Company ER's OEE targets.

In this paper, the outcomes will be presented as documented solutions that address the losses encountered in the production system, showing a 12.8% increase in the system's OEE.

Owing the time and resource constraint, this study only involved automated pallet handling procedures in a milk production facility. Hence, the generalization of the result is slightly limited. More studies in several different processes and sectors are required.

This study provided a valuable tool for researchers for gaining deeper understanding regarding the lean manufacturing and its implementation. For practitioners, it is useful to evaluate the degree of lean manufacturing tools in their material handling systems.

This study is the first attempt to develop lean manufacturing constructs for evaluating the automated pallet handling procedures in a milk production facility.

The authors aim to explore how perspective-taking and attribution of blame lead to side-taking by human resource professionals (HRPs) when making judgements and handling complaints of sexual harassment.

Employing qualitative methodology, the authors used semi-structured in-depth interviews with 35 HRPs from 30 companies in Sri Lanka. Attribution theory and perspective-taking were used as theoretical lenses.

In handling complaints of sexual harassment incidents, HRPs take the perspectives of the alleged perpetrator, complainant, or the company and attribute the blame to the alleged perpetrator or the complainant. Irrespective of the gender of the HRPs and the perspective they take, they would most often blame the female complainants due to sexual harassment myths and misperceptions and traditional sex-role beliefs. Thus, they either take the side of the alleged perpetrator or the company, explicitly/implicitly or intentionally/unintentionally.

The central originality of this research is the finding that HRPs take sides in resolving complaints of sexual harassment and perspective-taking and attribution of blame by HRPs lead to this side-taking in organisational settings.