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The effects of country-of-origin (COO) cues on product evaluations are well documented. However, research on the relative effects of COO compared to other geographical indicators, such as region-of-origin (ROO), on food purchases is still limited. This study investigates how geographical origin labels influence consumers' perceptions of product value and authenticity of foreign food, as well as subsequent purchase intention (PI) and willingness to pay premium prices (WTPPP). The moderating role of health consciousness on these relationships is also examined due to the coronavirus disease 2019 (COVID-19) pandemic.

This study uses a between-subjects experimental design conducted with 300 middle- and high-income Chinese consumers aged between 25 and 50 years. Hypotheses were tested using structural equation modelling.

Whilst under both COO and ROO cues, all five product values positively influenced consumers' WTPPP, only functional, economic and novelty values influenced PI. The ROO cue performed significantly better than the COO cue in eliciting functional, economic and novelty value perceptions, which triggered stronger PI and willingness to pay a premium price. These relationships were mediated by product authenticity (PA) and moderated by consumers' health consciousness (HC).

Because food labels provide salient product information that facilitates consumers' evaluation of products, marketers should assess which product value perceptions they wish to enhance and then choose the appropriate geographical indicators for their labelling strategies.

This study identifies the effects of COO and ROO cues on product values, authenticity, PI and WTPPP. It also provides valuable insights into the role of HC on consumers' purchase decisions, which also aids in understanding the impact of global crises on food purchases.

Cloud computing (CC) refers to the usage of virtualization technology to share computing resources through the internet. Task scheduling (TS) is used to assign computational resources to requests that have a high volume of pending processing. CC relies on load balancing to ensure that resources like servers and virtual machines (VMs) running on real servers share the same amount of load. VMs are an important part of virtualization, where physical servers are transformed into VM and act as physical servers during the process. It is possible that a user’s request or data transmission in a cloud data centre may be the reason for the VM to be under or overloaded with data.

VMs are an important part of virtualization, where physical servers are transformed into VM and act as physical servers during the process. It is possible that a user’s request or data transmission in a cloud data centre may be the reason for the VM to be under or overloaded with data. With a large number of VM or jobs, this method has a long makespan and is very difficult. A new idea to cloud loads without decreasing implementation time or resource consumption is therefore encouraged. Equilibrium optimization is used to cluster the VM into underloaded and overloaded VMs initially in this research. Underloading VMs is used to improve load balance and resource utilization in the second stage. The hybrid algorithm of BAT and the artificial bee colony (ABC) helps with TS using a multi-objective-based system. The VM manager performs VM migration decisions to provide load balance among physical machines (PMs). When a PM is overburdened and another PM is underburdened, the decision to migrate VMs is made based on the appropriate conditions. Balanced load and reduced energy usage in PMs are achieved in the former case. Manta ray foraging (MRF) is used to migrate VMs, and its decisions are based on a variety of factors.

The proposed approach provides the best possible scheduling for both VMs and PMs. To complete the task, improved whale optimization algorithm for Cloud TS has 42 s of completion time, enhanced multi-verse optimizer has 48 s, hybrid electro search with a genetic algorithm has 50 s, adaptive benefit factor-based symbiotic organisms search has 38 s and, finally, the proposed model has 30 s, which shows better performance of the proposed model.

User’s request or data transmission in a cloud data centre may cause the VMs to be under or overloaded with data. To identify the load on VM, initially EQ algorithm is used for clustering process. To figure out how well the proposed method works when the system is very busy by implementing hybrid algorithm called BAT–ABC. After the TS process, VM migration is occurred at the final stage, where optimal VM is identified by using MRF algorithm. The experimental analysis is carried out by using various metrics such as execution time, transmission time, makespan for various iterations, resource utilization and load fairness. With its system load, the metric gives load fairness. How load fairness is worked out depends on how long each task takes to do. It has been added that a cloud system may be able to achieve more load fairness if tasks take less time to finish.

This paper aims to focus on a medical goods distribution problem and pharmacological waste collection by plug-in hybrid vehicles with some real-world restrictions. In this research, considering alternative energy sources and simultaneous pickup and delivery led to a decrease in greenhouse gas emissions and distribution costs, respectively.

Here, this problem has been modeled as mixed-integer linear programming with the traveling and energy consumption costs objective function. The GAMS was used for model-solving in small-size instances. Because the problem in this research is an NP-hard problem and solving real-size problems in a reasonable time is impossible, in this study, the artificial bee colony algorithm is used.

Then, the algorithm results are compared with a simulated annealing algorithm that recently was proposed in the literature. Finally, the results obtained from the exact solution and metaheuristic algorithms are compared, analyzed and reported. The results showed that the artificial bee colony algorithm has a good performance.

In this paper, medical goods distribution with pharmacological waste collection is studied. The paper was focused on plug-in hybrid vehicles with simultaneous pickup and delivery. The problem was modeled with environmental criteria. The traveling and energy consumption costs are considered as an objective function.

The purpose is to understand how farmers in rural American communities perceive crime, safety and policing.

An online survey, adapted from a version used in Victoria, Australia (Harkness, 2017), was modified and administered through social media and farming organizations throughout three US states. The survey covers topics relating to crime and victimization, feelings of safety or fear in rural areas, policing practices and trust in police in their areas and any crime prevention practices that respondents use.

With nearly 1,200 respondents and four scales investigated, results indicate that those respondents with more favorable views of law enforcement and the criminal justice system had the highest fear of crime, those who had been prior victims of crime had a higher fear of crime than those who did not, those with higher community involvement had higher fear of crime, and those from Nebraska compared to Colorado had higher fear of crime.

A better understanding of the agricultural community’s perceptions of crime, safety and policing will aid law enforcement in community policing efforts and in farm crime investigation and prevention. Limitations of the study, including the distribution method will be discussed.

Farm- and agriculture-related crimes have serious financial and emotional consequences for producers and local economies. Stereotypes about rural areas being “safe with no crime” are still prevalent. Rural American farmers’ perceptions of crime, safety and police are largely absent from the literature and are important for improving farm crime prevention.

This paper aims to provide a literature review on the cloud-based platforms for the education sectors. The several aspects of cloud computing adoption in education, remote/distance learning and the application of cloud-based design and manufacturing (CBDM) have been studied and theorised.

A four-step methodology was adopted to analyse and categorise the papers obtained through various search engines. Out of 429 research articles, 72 papers were shortlisted for the detailed analysis.

Many factors that influence cloud computing technology adoption in the education sector have been identified in this paper. The research findings on several research items have been tabulated and discussed. Based on the theoretical research done on cloud computing for education, cloud computing for remote/distance learning and CBDM, cloud computing could enhance the educational systems in mainly developing countries and improve the scope for remote/distance learning.

This study is limited to papers published only in the past decade from 2011 to 2020. Besides, this review was unable to include journal articles published in different languages. Nevertheless, for the effective teaching and learning process, this paper could help understand the importance and improve the process of adopting cloud computing concepts in educational universities and platforms.

This study is a novel one as a research review constituting cloud computing applications in education and extended for remote/distance learning and CBDM, which have not been studied in the existing knowledge base.

This study aims to examine the dynamics of traditional wayang kulit or shadow puppet knowledge management in a community-based enterprise (CBE) known as “Wisata Wayang” in Wukirsari Village, Yogyakarta, Indonesia.

A qualitative case study was adopted, which allows the author to explore the dynamics or uniqueness of an event or cultural phenomenon more deeply.

The shadow puppet is an artefact of Javanese culture with rich life philosophy and wisdom. It guides people the pursuit of harmony with themselves, others, the universe and God. The success of knowledge management of the shadow puppet at CBE was supported by the high entrepreneurial orientation of the administrators. This study showed that entrepreneurial orientation should be extended into sociopreneurial with additional aspects, including preservation mission and communality, promoting the emergence of grassroots innovations. The knowledge of shadow puppet craft in this village is passed through nyantrik, also known as apprenticeship.

No previous research has explored the dynamics of traditional knowledge management in the context of CBE in Indonesia. As Indonesia has rich traditional knowledge from hundreds of tribes and prominent communal cultures, this study of community-based knowledge management contributes new insights in the knowledge management literature.

To generate electricity, solar photovoltaic (PV) systems are among the best, most eco-friendly and most cost-effective solutions available. Extraction of maximum possible electricity from the solar PV system is complicated by a number of factors brought on by the ever-changing weather conditions under which it must operate. Many conventional and evolutionary algorithm-based maximum power point tracking (MPPT) techniques have the limitation of not being able to extract maximum power under partial shade and rapidly varying irradiance. Hence, the purpose of this paper is to propose a novel hybrid slime mould assisted with perturb and observe (P&O) global MPPT technique (HSMO) for the hybrid bridge link-honey comb (BL-HC) configured PV system to enhance the better maximum power during dynamic and steady state operations within less time.

In this method, a hybridization of two algorithms is proposed to track the true with faster convergence under PSCs. Initially, the slime mould optimization (SMO) algorithm is initiated for exploration of optimum duty cycles and later P&O algorithm is initiated for exploitation of global duty cycle for the DC–DC converter to operate at GMPP and for fast convergence.

The effectiveness of the proposed HSMO MPPT is compared with adaptive coefficient particle swarm optimization (ACPSO), flower pollination algorithm and SMO MPPT techniques in terms of tracked GMPP, convergence time/tracking speed and efficacy under six complex partial shading conditions. From the results, it is noticed that the proposed algorithm tracks the true GMPP under most of the shading conditions with less tracking time when compared to other MPPT techniques.

This paper proposes a novel hybrid slime mould assisted with perturb and observe (P&O) global MPPT technique (HSMO) for the hybrid BL-HC configured PV system enhance the better maximum power under partial shading conditions (PSCs). This method operated in two stages as SMO for exploration and P&O for exploitation for faster convergence and to track true GMPP under PSCs. The proposed approach largely improves the performance of the MPP tracking of the PV systems. Initially, the proposed MPPT technique is simulated in MATLAB/Simulink environment. Furthermore, an experimental setup has been designed and implemented. Simulation results obtained are validated through experimental results which prove the viability of the proposed technique for an efficient green energy solution.

This study aims to provide a contextualized look at the artisan sector in Zambia and asks: What factors contribute to scaling positive impact in artisan ventures in Zambia, and how can these factors be leveraged to promote positive economic, social and environmental outcomes for women and their communities.

This study uses an explanatory sequential mixed-methods approach to gain a multi-layered understanding of artisan craft social enterprises in Zambia.

Purpose is found to be the primary driver of social and environmental impact in artisan social enterprises in Zambia, with female leadership a critical factor. Access to finance, markets and resources are also essential to help these organizations achieve their social missions.

While this study provides valuable insights into the artisan sector, its scope was limited to the Zambian context, making the generalizability of the findings to other geographies uncertain.

This research makes a valuable contribution to the literature on social enterprises by highlighting the critical role of female leadership and purpose in driving positive impact in artisan businesses in Zambia. Additionally, the study underscores the importance of understanding the mechanisms through which artisan social enterprises create positive change. The study highlights the importance of artisan craft employment for women in Zambia and illustrates the impact of Zambian artisan ventures, both formal social enterprises and informal businesses, on creating positive social and environmental impacts in the country.

This study examines the cultural history of the Api-Opi deity in Opi, Nsukka, Enugu State of Nigeria. The study sets out to examine the re-emergence of youthful worshippers of Api-Opi, despite the penetration of Christianity in the area.

The study employed ethnographic observation and field visits to the shrine of Api-Opi in Opi community of Enugu State, Nigeria. In addition, this study uncovers new information drawn from semi-structured interview questions undertaken in the study area between March and October of 2019.

Against certain claims on the impact of Christianity on Africa's traditional religions, the study found that the Api-Opi deity has withstood these post-colonial changes, growing its followership, particularly amongst the youths. It demonstrated the resilience of Igbo Traditional Worship System even in the midst of culture clash and religious iconoclasm advanced by Christianity in Igboland, Nigeria.

Evidence from this study helps debunk the notions of Eurocentric scholars who say African traditional religions are fetish, barbaric or primitive. It also shows how indigenous communities have protected and preserved their religious heritage despite the wave of modernization and other eternal influences. The study contributes to the increasing conversations about the role of traditional religion in the cultural resilience/revitalization of indigenous communities.