Template-Type: ReDIF-Article 1.0 Author-Name: Maxim A. Bushuev Author-X-Name-First: Maxim A. Author-X-Name-Last: Bushuev Author-Name: Alfred L. Guiffrida Author-X-Name-First: Alfred L. Author-X-Name-Last: Guiffrida Title: Improving delivery performance for gamma distributed delivery time Abstract: This paper investigates strategies for improving delivery performance to the end customer in a two-stage supply chain. A cost-based analytical model is used to evaluate how the expected penalty cost resulting from early and late delivery can be reduced. The effects of the width of the delivery window and the shape and scale parameters of the gamma distributed delivery time distribution on the expected penalty cost are explored. The model can guide practitioners who are attempting to cost-justify a program to improve delivery performance. It can also be used to estimate cost reduction over several deliveries and compare cost savings with required investments into delivery performance improvement. The model overcomes the limitations of previous delivery improvement studies which did not used an optimally positioned delivery window and were limited to symmetric delivery time distributions. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 195-214 Issue: 3 Volume: 10 Year: 2019 Keywords: supply chain management; delivery window; gamma distribution; performance measures. File-URL: http://www.inderscience.com/link.php?id=100823 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:10:y:2019:i:3:p:195-214 Template-Type: ReDIF-Article 1.0 Author-Name: Parveen Farooquie Author-X-Name-First: Parveen Author-X-Name-Last: Farooquie Author-Name: Arif Suhail Author-X-Name-First: Arif Author-X-Name-Last: Suhail Author-Name: Mohd. Nishat Faisal Author-X-Name-First: Mohd. Nishat Author-X-Name-Last: Faisal Title: Uncertainty and contract flexibility in automotive supply chains: a simulation model Abstract: Supply chains are vulnerable to uncertainties in demand and supply. Such uncertainties are often responsible for failure of contracts between buyers and suppliers. Flexible provisions in contracts are likely to reduce the adverse effect of uncertainties on the supply chain effectiveness. The present paper proposes a framework for buyers and suppliers to introduce flexibility in their contracts to address uncertainty in demand and supply. The framework has been developed by simulating various demand and supply situations in the context of automotive supply chains. This framework also aims at identifying variables of a contract which the pair can negotiate and deliver seamlessly. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 215-235 Issue: 3 Volume: 10 Year: 2019 Keywords: automotive; contract; flexibility; performance; supply chain; simulation; uncertainty. File-URL: http://www.inderscience.com/link.php?id=100844 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:10:y:2019:i:3:p:215-235 Template-Type: ReDIF-Article 1.0 Author-Name: Mojtaba Ghiyasi Author-X-Name-First: Mojtaba Author-X-Name-Last: Ghiyasi Title: Full ranking of efficient and inefficient DMUs with the same measure of efficiency in DEA Abstract: Data envelopment analysis (DEA) is a mathematical programming approach for calculating the relative efficiency of a group of decision making units (DMUs). After efficiency measurement process some DMUs may have the same measure of efficiency, specifically some DMUs may be found efficient. The question is which DMU performs better within a group of DMUs with the same measure of efficiency. The current article aims to answer this question based the DMU's aid not only to the associated group but also its aid to the whole production system. This yields to two ranking indices. The first index is for ranking inefficient DMUs with the same measure of efficiency and the second index is for ranking efficient DMUs. A comparison between the proposed approaches and well-known ranking index in the literature is provided and proposed approaches are explained by many numerical examples and a real life data illustration. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 236-252 Issue: 3 Volume: 10 Year: 2019 Keywords: data envelopment analysis; DEA; ranking; returns to scale; semi-additive technology. File-URL: http://www.inderscience.com/link.php?id=100848 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:10:y:2019:i:3:p:236-252 Template-Type: ReDIF-Article 1.0 Author-Name: Sandhya Rai Author-X-Name-First: Sandhya Author-X-Name-Last: Rai Title: Big data - real time fact-based decision: the next big thing in supply chain Abstract: Big data has become the life blood of the organisations. Organisations are gaining an understanding that if all the data that streams into businesses are captured and analysed, then they may prove to be a valuable source of information. The thought of data creating value is not new; businesses have always wanted to derive insight from data for making real time, fact-based decisions. In the domain of supply chain, companies are using big data analytics to manage activities like warehousing, transportation, inventory management, delivery, demand forecasting and scheduling. For this they are applying various data analytics tools and techniques. The aim of this paper is to explore all these application in detail and identify the tools and techniques that are used across upstream and downstream supply chain and develop a theoretical framework of application of big data in supply chain management (SCM). Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 253-265 Issue: 3 Volume: 10 Year: 2019 Keywords: big data; big data analytics; BDA; data preparation; data discovery; data visualisation; data scientist; warehousing; transit; distribution; supply chain. File-URL: http://www.inderscience.com/link.php?id=100853 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:10:y:2019:i:3:p:253-265 Template-Type: ReDIF-Article 1.0 Author-Name: Suman Tiwari Author-X-Name-First: Suman Author-X-Name-Last: Tiwari Author-Name: Chan Shiau Wei Author-X-Name-First: Chan Shiau Author-X-Name-Last: Wei Author-Name: Muhammad Faraz Mubarak Author-X-Name-First: Muhammad Faraz Author-X-Name-Last: Mubarak Title: Sustainable procurement: a critical analysis of the research trend in supply chain management journals Abstract: Since the dawn of new millennium, sustainable procurement (SP) has captivated the attention of scholars worldwide. In this context, this paper provides a critical analysis of SP research trend in supply chain management (SCM) journals. The analysis has been carried out using existing literature of SP research contributed by the authors and institutions from assorted countries. Specifically, the research tendency of SP in SCM is identified through a systematic analysis of sustainable procurement research articles published in ten selected SCM journals from 1990 to 2016. The analysis revealed that SP research has an increasing trend in recent times, indicating its widely growing significance. The research topics covered in this paper to focus on the sustainability issues of procurement practices are sustainability issues on the network of supply chain, foundation, SP process, and enablers as well as the determinant of SP. This comprehensive study provides practical insights to researchers and industrialists on the nature and scope of SP in SCM. Journal: Int. J. of Business Performance and Supply Chain Modelling Pages: 266-282 Issue: 3 Volume: 10 Year: 2019 Keywords: sustainable procurement; supply chain management; SCM; sustainability issues. File-URL: http://www.inderscience.com/link.php?id=100855 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijbpsc:v:10:y:2019:i:3:p:266-282