During the last decades, environmental crises through energy consumption and economic growth were noticed as a growing concern among researchers. The industrial sector is the main part of economic growth in each country using conservative energy and emitting carbon dioxide that causes global warming. The Paris agreement and Kyoto protocol were two agreements to prevent governments from emitting CO2 freely. Purpose of this research was to investigate the cement industry, steel industry, and automobile industry products’ effects on CO2 emissions in Iran and to rank them according to their measured effects on CO2 emissions. The methodology used in this study was to estimate equations with CO2 emissions as a dependent variable and cement, steel, and automobile industries’ products with ordinary least squares (OLS) and generalized moment method (GMM) approaches. Stationary, Johansen cointegration, Durbin-Watson, Breusch-Godfrey, Chow breakpoint, and normal residual tests were checked. In-sample forecasting was implemented to check the precision of the estimation and an updated ranking was reported as a final result to consider which industry has affected CO2 emissions more than the others per unit of production cost. In conclusion, the cement industry, steel industry, and automobile industry had the most positive effects on CO2 emissions, respectively. This result is suitable to prioritize the industries for enhancing green technology and optimizing industrial production for a more sustainable economy.

Food supply chain disruptions have of recent increased in terms of severity and frequency leading to viability problems for most businesses in related supply chain networks and hunger among millions of human beings. In the extant supply chain literature elements of responsive supply chain such as velocity, versatility, and visibility have been suggested as some of the possible strategies to build supply chain resilience. It has therefore been suggested in this study that these elements’ influence on supply chain resilience is moderated by contract farming as a special form of supplier development. Farming contracts are either production or marketing contracts. Data was collected from a conveniently selected sample of 200 restaurants that use supplier development in the form of contract farming for acquiring critical resources for their operations. A structural equation modelling was used to analyse data related to the direct effects and multi group structural equation modelling was used to assess the moderating effects. The results revealed that there is a statistically significant relationship between the three selected elements of responsive supply chain management and supply chain resilience, and all the hypothesised relationships were moderated by type of farming contracts, with the relationships being stronger under marketing contracts for supply chain velocity, and under production contracts than under marketing contracts for relationships involving versatility and visibility. Therefore, the study recommended that production contracts be used in the fast-food restaurant industry in order to reduce supply chain vulnerabilities, and marketing contracts to build supply chain capabilities. This is the first study that has sought to assess the differential utility of different farming contracts through assessing their moderating effects as a build-up on previous research that has already established that supplier development in the form of contract farming leads to supplier development.

Highway accident data analysis provides probability of occurrence of road accidents by associating different accident factors using data mining algorithms. Analysis can be improved by using advanced data mining algorithms that compute relationships with minimum processing time. As accident datasets are very heterogeneous in nature, it is difficult to identify the relationship between critical factors responsible for road accidents without data mining algorithms. In this study, K-modes for clustering and frequent pattern growth algorithms to extract relationships between critical accident factors have been used. The accomplished result concludes better relationships with better accuracy than earlier implemented data mining algorithms and has found meaningful hidden situations that would be beneficial for future work in decreasing the number of highway accidents.

As in today's era firms are looking to sustain while facing multiple challenges. Ultimately talented employees are the backbone of any firm that provides a sustainable competitive position at a global level. The major aspect is to make appropriate strategies to stay effective and efficient. Firms are focused on their strategies of recruitment and selection, training, and leadership capabilities to build up. A sample is collected from top-level management of the pharmaceutical sector sample data is of 320 Professionals from the different pharmaceutical sector of Karachi Pakistan. For Data collection Survey method is adopted with a close-ended Questionnaire. The study reveals the impact of artificial intelligence on competitive advantage. This research finds out certain strategies to be aligned with the mediation of Artificial intelligence to gain sustainable competitive advantage and serial mediation of the talent management process among the pharmaceutical sector of Karachi Pakistan. Talent management and Artificial Intelligence serial mediation aligned with HR practices to gain competitive advantage. As the study indicates that recruitment and selection are positively aligned with Artificial intelligence and serial mediation of talent management, further aspects of talent development and talent retention are directly linked with a competitive advantage as suitable components. This research merely focused on the pharmaceutical sector of Karachi Pakistan and the results generalized on the professionals of this particular sector, while new aspects of HR practices could be linked up with Artificial intelligence that will help to boost and find better insight into other industries.

The concept of green inventory systems is very important for economic growth and development in the era of sustainable development. There is a special need for green inventory systems to identify and manage perishable products since spoilage and deterioration can lead to significant losses of items, which negatively affect the satisfaction of consumers. As perishable products decay continuously (such as vegetables, fruits, milk, juices, frozen foods, baked foods), their demand is adversely affected as well as customers' purchasing decisions. The more realistic assumption is a price-sensitive demand. As well as deterioration rates, perishable products have an expiration date-dependent deterioration rate. Further, inventory holding, and the deterioration of perishables contribute significantly to carbon emissions when operating the inventory system. A carbon tax policy is more flexible and effective when it comes to reducing carbon emissions due to its environmental conscious nature. We develop two sustainable inventory procedures for perishable items based on a practical scenario in which the buyer has a limited storeroom. So, to achieve sustainability goals, a model for inventory management for perishable products based on expiration dates is presented in this paper. We distinguish between two inventory schemes: (i) one that allows shortages and fractional backlogs, and (ii) one that does not allow shortage. In both schemes, both the decay rate and demand function show an upward trend against storage time. Since the decay rate increases with storage time, it is assumed that the cost of storing items is linearly related to storage time. numerical examples along with a real-life case study are presented to validate the inventory schemes after several decision-making findings have been derived.

Supply chains are changing due to changes in the global environment and to make the strategies effective most of the companies are striving towards the trends in the supply chain. Among the trends gamification is one of those that are creating an impact in the workspace with the techniques that are associated with it. Gamification in the supply chain had the least application and this study gave a road map for the decision makers like supply chain managers with the help of reviewing papers from the databases that are available. Findings say that giants like Amazon and Starbucks are applying gamification techniques to bring more transparency and visibility to reduce errors and to mitigate errors. This paper is providing evidence from the different activities like order management, warehousing activities with case applications are discussed. We conducted systematic literature review with 118 papers on gamification and 22 found relevant to the supply chain and its activities.

This article discusses the value of sustainable oil maintenance by using submicron high-tech offline filtration based on oil condition monitoring to reduce wear particles and improve system reliability. These activities incorporate broader goals of establishing a proactive maintenance approach, defined as continuous monitoring and controlling of the root causes of machine failure. Among these causes, contamination is the industry's most severe, popular, and most recognized failure cause. In order to ensure all necessary proactive maintenance activities, this paper uses practical analysis for oil contamination monitoring based on ISO 4405. The author applied a 0.1-micron high-tech offline filtration for lubrication systems of ball mills in the Sungun copper mine as an oil maintenance activity to control the system lubrication contamination as a root cause of failures.

Weevils are a type of insect with elongated snouts coming from superfamily of Curculionoidea with approximately 97,000 species. Most of them consider pest and cause environmental damages but some kinds like wheat weevil, maize weevil, and boll weevils are famous to cause huge damage on crops, especially cereal grains. This research proposes a novel swarm-based metaheuristics algorithm called Weevil Damage Optimization Algorithm (WDOA) which mimics weevils’ fly power, snout power, and damage power on crops or agricultural products. The proposed algorithm is tested with 12 benchmark unimodal and multimodal artificial landscapes or optimization test functions. Additionally, the proposed WDOA is employed in five engineering problems to check its robustness for problem solving. Problems are Travelling Salesman Problem (TSP), n-Queens problem, portfolio problem, Optimal Inventory Control (OIC) problem, and Bin Packing Problem (BPP). All tests’ functions are compared with widely used benchmark algorithms of Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Harmony Search (HS) algorithm, Imperialist Competitive Algorithm (ICA), Firefly Algorithm (FA), and Differential Evolution (DE) algorithm. Also, all problems are tested with DE, FA, and HS algorithms. The Proposed algorithm showed robustness and speed on all functions and problems by providing precision alongside with reasonable speed.

COVID-19 pandemic was one of the most severe sources of disruptions that recently threatened the supply chain networks. As such disruptions are inevitable in today's business world, learning lessons from the COVID-19 pandemic can significantly help supply chains prepare for future disruptions. This study aims to investigate how Australian supply chains were affected during the COVID-19 pandemic and provide some key resilience strategies to face disruptions. These strategies can assist SC managers in protecting their networks from possible disruption in future.

Epoxy material being a key in a wide range of applications has become a center of attraction for interdisciplinary research. However, the limitations so far reported in using this material has led to the development of some new pitches such as Polyacetal and Araldite. Polyacetal being currently employed in bushes, wipers, gears, etc. while Araldite composites with a potential of delivering some august properties can be an alternative approach to the former. In this work, a comparative study is carried out on the me-chanical attributes of Polyacetal and Araldite (Epoxy) material. Various ASTM standard specimens casted with these materials are subjected to some exploratory assessments such as Tensile Test, Izod Impact Test, Charpy Impact Test, Three-point Bending Test and Vicker’s Hardness Test in order to determine the respective properties.