Assessment of Turkish HR Professionals on Determining the Importance of Factors in Point Factor as a Method of Job Evaluation

Job evaluation is a procedure for assessing the relative jobs with a view to differentiating jobs to positions. In this study, it is aimed to redetermine the importance of main and sub factors used in point factor method which is one of job evaluation methods by human resource professionals located in different sectors based on the manifacturing sector. The determining factors importance is a phenomenon open to subjective judgments. Also, with some developments such as change of technology and ways of doing business, factors weights should be redetermined or updated now and again. So, it is thought that the explore of reviews from different parties (job evaluation experts, technical managers, HR professionals, employees, etc.) about importance of all factors is very important. Accordingly, data about importance of factors were received from 40 human resource professionals through survey method and they were analyzed by analytic hierarchy process. At the end of research, similar results to job evaluation scale generated and used by Turkish Metal Industry Employer’s Union (MESS) were achieved. However, it was found that “education and basic knowledge” which was the most important sub factor in job evaluation scale developed by Turkish Metal Industry Employer’s Union was least important sub factor as result of study. Keywords: job evaluation, point factor method, analytic hierarchy process, multi criteria decision making, Turkish HR professionals

Managing your supply chain pantry: food waste mitigation through inventory control

In this paper, we report through case study findings that the food supply chain can be improved by implementing a proper inventory control policy. The case study involves an online retailer who sells predominantly food products. The improvement of the case company is shown via simulation in economic, social and environmental aspects. The findings indicate the role of supply chain risk as an obstacle in achieving supply chain sustainability, and the benefit of effective inventory control as a cost-advantageous and easy-to-implement waste reduction method

Artificial intelligence in supply chain decision-making: An environmental, social, and governance triggering and technological inhibiting protocol

Purpose Decision-making, reinforced by artificial intelligence (AI), is predicted to become potent tool within the domain of supply chain management. Considering the importance of this subject, the purpose of this study is to explore the triggers and technological inhibitors affecting the adoption of AI. This study also aims to identify three-dimensional triggers, notably those linked to environmental, social, and governance (ESG), as well as technological inhibitors. Design/methodology/approach Drawing upon a six-step systematic review following the preferred reporting items for systematic reviews and meta analysis (PRISMA) guidelines, a broad range of journal publications was recognized, with a thematic analysis under the lens of the ESG framework, offering a unique perspective on factors triggering and inhibiting AI adoption in the supply chain. Findings In the environmental dimension, triggers include product waste reduction and greenhouse gas emissions reduction, highlighting the potential of AI in promoting sustainability and environmental responsibility. In the social dimension, triggers encompass product security and quality, as well as social well-being, indicating how AI can contribute to ensuring safe and high-quality products and enhancing societal welfare. In the governance dimension, triggers involve agile and lean practices, cost reduction, sustainable supplier selection, circular economy initiatives, supply chain risk management, knowledge sharing and the synergy between supply and demand. The inhibitors in the technological category present challenges, encompassing the lack of regulations and rules, data security and privacy concerns, responsible and ethical AI considerations, performance and ethical assessment difficulties, poor data quality, group bias and the need to achieve synergy between AI and human decision-makers. Research limitations/implications Despite the use of PRISMA guidelines to ensure a comprehensive search and screening process, it is possible that some relevant studies in other databases and industry reports may have been missed. In light of this, the selected studies may not have fully captured the diversity of triggers and technological inhibitors. The extraction of themes from the selected papers is subjective in nature and relies on the interpretation of researchers, which may introduce bias. Originality/value The research contributes to the field by conducting a comprehensive analysis of the diverse factors that trigger or inhibit AI adoption, providing valuable insights into their impact. By incorporating the ESG protocol, the study offers a holistic evaluation of the dimensions associated with AI adoption in the supply chain, presenting valuable implications for both industry professionals and researchers. The originality lies in its in-depth examination of the multifaceted aspects of AI adoption, making it a valuable resource for advancing knowledge in this area

Isolation, characterization and virulence of bacteria from Ostrinia nubilalis (Lepidoptera: Pyralidae)

Demirbag, Zihni/0000-0001-5487-1977; SEVIM, ALI/0000-0003-2472-599XWOS: 000305840100020Isolation, characterization and virulence of the culturable bacteria from entire tissues of larval Ostrinia nubilalis (Hubner) (Lepidoptera: Pyralidae) were studied to obtain new microbes for biological control. A total of 16 bacteria were isolated from living and dead larvae collected from different maize fields in the Eastern Black Sea Region of Turkey. the bacterial microbiota of O. nubilalis were identified as Pseudomonas aeruginosa (On1), Brevundimonas aurantiaca (On2), Chryseobacterium formosense (On3), Acinetobacter sp. (On4), Microbacterium thalassium (On5), Bacillus megaterium (On6), Serratia sp. (On7), Ochrobactrum sp. (On8), Variovorax paradoxus (On9), Corynebacterium glutamicum (On10), Paenibacillus sp. (On11), Alcaligenes faecalis (On12), Microbacterium testaceum (On13), Leucobacter sp. (On14), Leucobacter sp. (On15) and Serratia marcescens (On16) based on their morphological and biochemical characteristics. A partial sequence of the 16S rRNA gene was also determined to confirm strain identification. the highest insecticidal activities were obtained from P. aeruginosa On1 (80%), Serratia sp. On7 (60%), V. paradoxus On9 (50%) and S. marcescens On16 (50%) against larvae 14 days after treatment (p < 0.05). Also, the highest activity from previously isolated Bacillus species was observed from Bacillus thuringiensis subsp. tenebrionis Xd3 with 80% mortality within the same period (p < 0.05). Our results indicate that P. aeruginosa On1, Serratia sp. On7, V. paradoxus On9, S. marcescens On16 and B. thuringiensis subsp. tenebrionis Xd3 show potential for biocontrol of O. nubilalis

Projection of technology using in agriculture of central anatolia region

Günümüz tarımsal üretiminde temel amaç, artan nüfusun ihtiyaçlarını karşılamak için birim alandan daha fazla ve kaliteli ürün almaktır. Mekanizasyonun yaygınlaşması ile tarım teknikleri ve teknolojileri kolay uygulanır olmuş, toprak işleme, ekim, dikim, gübreleme, kimyasal mücadele, hasat ve harman işlemlerindeki verimliliğe bağlı olarak da ürün kalitesi ve verim artmıştır. Bu çalışmada İç Anadolu Bölgesinin tarımda teknoloji kullanım projeksiyonunun belirlenmesi amaçlanmıştır. Tarımda kullanılan teknolojinin geçmiş on yıllık üretim ve kullanım miktarları baz alınarak projeksiyon katsayısı hesaplanmıştır. Projeksiyon katsayısının artışı veya azalışı doğrultusunda İç Anadolu Bölgesinin tarımda teknoloji kullanımına ait on yıllık projeksiyonları belirlenmiş ve Türkiye ile karşılaştırılmıştır. Projeksiyon katsayısı, diskli traktör pulluğu için %3.89, toprak frezesi için %3.57, traktörle çekilen çayır biçme makinesi için %6.61, ot tırmığı için %-2.84, hububat ekim makinesi için %5.50, üniversal ekim makinesi için %-2.63, pnömatik ekim makinesi için %-5.52 ve kimyevi gübre dağıtma makinesi için %1.79 hesaplanmıştır. Projeksiyon katsayısının pozitif elde edilmesi, mevcut alet ve makine sayısının artmasına, negatif elde edilmesi ise azalmasına neden olmuştur. İç Anadolu Bölgesinin diskli pulluk, traktörle çekilen çayır biçme makinesi ve hububat ekim makinesi için hesap edilen projeksiyon katsayısı, Türkiye için elde edilen değerlere göre yüksek bulunmuştur.The main aim of current agricultural production is to provide needs of increasing population by getting higher and qualified production from unit area. Thanks to improvements in mechanization, application of agricultural techniques and technologies has been simpler, and increased efficiency in soil tillage, sowing planting and fertilizing , chemical control, harvest, thus quality of production and yield increased. The aim of this study is to determinate of technology using projection in Central Anatolia Region. Projection coefficient was calculated by using last ten years production and consumption data of technology used in agriculture. Regarding to increase or decrease of projection coefficient, the projection of Central Anatolia Region were determined for last ten years and compared to Turkey. Projection coefficient were calculated as 3.89% for disc type tractor plough, 3.57% for rotary tiller , 6.61% for tractor drawn mower, -2.84% for hay rake, 5.50% for combined seed drill, -2.63% for universal drill, -5.52% for pneumatic sowing machine and 1.79% for fertilizer broadcaster. Positive projection coefficient numbers indicate that an increase in the number of current instrument and machine and decrease in otherwise with negative numbers. The numbers for disc type tractor plough, tractor drawn mower ve combined seed drill were found higher comparing the calculated data of Turkey

Hybrid simulation and optimization approach for green intermodal transportation problem with travel time uncertainty

The increasing volumes of road transportation contribute to congestion on road, which leads to delays and other negative impacts on the reliability of transportation. Moreover, transportation is one of the main contributors to the growth of carbon dioxide equivalent emissions, where the impact of road transportation is significant. Therefore, governmental organizations and private commercial companies are looking for greener transportation solutions to eliminate the negative externalities of road transportation. In this paper, we present a novel solution framework to support the operational-level decisions for intermodal transportation networks using a combination of an optimization model and simulation. The simulation model includes stochastic elements in form of uncertain travel times, whereas the optimization model represents a deterministic and linear multi-commodity service network design formulation. The intermodal transportation plan can be optimized according to different objectives, including costs, time and CO2e emissions. The proposed approach is successfully implemented to real-life scenarios where differences in transportation plans for alternative objectives are presented. The solutions for transportation networks with up to 250 services and 20 orders show that the approach is capable of delivering reliable solutions and identifying possible disruptions and alternatives for adapting the unreliable transportation plans

Green intermodal freight transportation: bi-objective modeling and analysis

Efficient planning of freight transportation requires a comprehensive look at wide range of factors in the operation and management of any transportation mode to achieve safe, fast, and environmentally suitable movement of goods. In this regard, a combination of transportation modes offers flexible and environmentally friendly alternatives to transport high volumes of goods over long distances. In order to reflect the advantages of each transportation mode, it is the challenge to develop models and algorithms in Transport Management System software packages. This paper discusses the principles of green logistics required in designing such models and algorithms which truly represent multiple modes and their characteristics. Thus, this research provides a unique practical contribution to green logistics literature by advancing our understanding of the multi-objective planning in intermodal freight transportation. Analysis based on a case study from hinterland intermodal transportation in Europe is therefore intended to make contributions to the literature about the potential benefits from combining economic and environmental criteria in transportation planning. An insight derived from the experiments conducted shows that there is no need to greatly compromise on transportation costs in order to achieve a significant reduction in carbon-related emissions

Metabolic syndrome in bipolar disorder: prevalence, demographics and clinical correlates in individuals with bipolar I, bipolar II, and healthy controls

Background: The metabolic syndrome is a growing global public health problem and highly prevalent in patiens with bipolar disorder. There are a few studies about relationship between metabolic syndrome and bipolar disorder subtypes. Objective: The aim of this study was to investigate the prevalence of metabolic syndrome (MS) and its individual components in subjects with bipolar I (BD I) and bipolar II (BD II) disorder compared with non-psychiatric controls, and to determine the variables affecting MS. Methods: A total of 210 individuals (mean age 42.5 ± 11.87, 58.1% female) of whom 70 had BD I, 70 BD II, and 70 controls, were included in this study. MS was diagnosed according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), the adapted ATP III (ATP III-A) and the International Diabetes Federation (IDF) criteria. Results: Participants with BD I had a significantly higher prevalence of MS when compared to individuals BD II and non-psychiatric controls according to the NCEP-ATP III, ATP III-A, and IDF criteria (ps &lt; 0.01). In individuals with MS, increased waist circumference was the most common abnormality. Logistic regression analysis revealed that the presence of physical illness, age and number of cigarettes smoked significantly predicted the presence of MS. Discussion: This study showed that MS was more prevalent among BD I individuals compared to BD II and controls, and highlighted the importance of regular screening for MS in individuals with BD

A* search algorithm for an optimal investment problem in vehicle-sharing systems

We study an optimal investment problem that arises in the context of the vehicle-sharing system. Given a set of locations to build stations, we need to determine i) the sequence of stations to be built and the number of vehicles to acquire in order to obtain the target state where all stations are built, and ii) the number of vehicles to acquire and their allocation in order to maximize the total profit returned by operating the system when some or all stations are open. The profitability associated with operating open stations, measured over a specific time period, is represented as a linear optimization problem applied to a collection of open stations. With operating capital, the owner of the system can open new stations. This property introduces a set-dependent aspect to the duration required for opening a new station, and the optimal investment problem can be viewed as a variant of the Traveling Salesman Problem (TSP) with set-dependent cost. We propose an A* search algorithm to address this particular variant of the TSP. Computational experiments highlight the benefits of the proposed algorithm in comparison to the widely recognized Dijkstra algorithm and propose future research to explore new possibilities and applications for both exact and approximate A* algorithms.Comment: Full version of the conference paper which is accepted to be appear in the proceeding of the The 12th International Conference on Computational Data and Social Networks - SCONET202