Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: 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.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)