Research Article
Effect of Logistics Activities on Operational Performance the Case of Bedele Brewery Share Company
Jabessa Hinkosa Dinsa,
Amanuel Tadele Kinati
Issue:
Volume 9, Issue 1, April 2024
Pages:
1-16
Received:
11 August 2023
Accepted:
31 August 2023
Published:
23 January 2024
Abstract: Nowadays, the role of logistics is increasingly recognized worldwide & its management was vital for the competitiveness of any firms’ weather manufacturing or service. An overall logistics activity was crucial for the day to day activities of any firms. The purpose of this study was to investigate the effect of logistics activities on operational performance of Bedele Brewery Share Company. The study has used explanatory and descriptive research design with both qualitative and quantitative approach. The study used both probability and non- probability sampling techniques. From the total of 395 employees working in the company’s production (operation), sales and transportation management, materials management, quality assurance, and warehousing departments; primary source of data were used. Questionnaire was distributed for 195 employees out of them186 was returned and analyzed with the help of SPSS version-25. Reliability of the instrument was tested by using Cronbach Alpha coefficient and pilot testing. Correlation analysis was used to determine the relationship between operational performance and logistics activities. In addition, regression analysis was used to analyze the effect of logistics activities on operational performance. The findings of the study revealed that transportation and inventory management, procurement practice, information flow and warehousing have significant positive effect on operational performance. In order to improve operational performance of the company, Bedele Brewery Share Company should upgrade investment on infrastructure for transportation of raw materials within Company. Using principle of economic order quantity that enables effective inventory management is also recommendable.
Abstract: Nowadays, the role of logistics is increasingly recognized worldwide & its management was vital for the competitiveness of any firms’ weather manufacturing or service. An overall logistics activity was crucial for the day to day activities of any firms. The purpose of this study was to investigate the effect of logistics activities on operational p...
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Research Article
The Use of AI to Analyze Social Media Attacks for Predictive Analytics
Issue:
Volume 9, Issue 1, March 2024
Pages:
17-24
Received:
26 January 2024
Accepted:
5 February 2024
Published:
2 April 2024
DOI:
10.11648/j.ajomis.20240901.12
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Views:
Abstract: Social engineering, on the other hand, presents weaknesses that are difficult to directly quantify in penetration testing. The majority of expert social engineers utilize phishing and adware tactics to convince victims to provide information voluntarily. Social Engineering (SE) in social media has a similar structural layout to regular postings but has a malevolent intrinsic purpose. Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM) was used to train a novel SE model to recognize covert SE threats in communications on social networks. The dataset includes a variety of posts, including text, images, and videos. It was compiled over a period of several months and was carefully curated to ensure that it is representative of the types of content that is typically posted on social media. First, by using domain heuristics, the social engineering assaults detection (SEAD) pipeline is intended to weed out social posts with malevolent intent. After tokenizing each social media post into sentences, each post is examined using a sentiment analyzer to determine whether it is a training data normal or an abnormality. Subsequently, an RNN-LSTM model is trained to detect five categories of social engineering assaults, some of which may involve information-gathering signals. Comparing the experimental findings to the ground truth labeled by network experts, the SEA model achieved 0.82 classification precision and 0.79 recall.
Abstract: Social engineering, on the other hand, presents weaknesses that are difficult to directly quantify in penetration testing. The majority of expert social engineers utilize phishing and adware tactics to convince victims to provide information voluntarily. Social Engineering (SE) in social media has a similar structural layout to regular postings but...
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,
Morolake Oladayo Lawrence
