Arshinder Kaur

A graph theoretic approach for supply chain coordination

Supply chain coordination is an effective approach to manage the dependencies among supply chain members. These members often try to achieve their respective objectives, disregarding the objective of the complete supply chain. This results in higher supply chain costs, greater lead times and a large variance between supply and demand. Supply chain coordination is defined as the joint effort of the supply chain members towards mutually defined goals. There are a number of mechanisms to achieve coordination. The existing literature lacks in presenting a comprehensive measure of supply chain coordination. In this paper, an attempt has been made to identify various mechanisms of coordination. A graph theoretic approach is used to model various mechanisms of coordination and their interdependencies. The digraph representing the supply chain coordination is converted to its adjacency matrix whose permanent function gives a composite index of coordination. This approach helps compare organisations in terms of their coordination capability.

Exploring the role of HR practices in supply chain

Purpose – The purpose of this study is to establish the importance of human resource (HR) practices in achieving high levels of supply chain (SC) integration through a conceptual framework (depicting the moderation effect of HR practices on the relationship between information sharing and SC integration) and validating the framework empirically to establish the proposed relationships.Design/methodology/approach – The conceptual framework is proposed based on gaps in extant literature. Data from 60 automobile component manufacturing organizations in India are used to analyse the relationship between the study variables. Regression analysis is used to find the relative impact of predictor variable (Information sharing) on SC integration and the moderation effect of HR practices (training, collaborative performance systems and reward alignment) on this relationship.Findings – The results indicate that information sharing has a significant effect on SC integration, and the relationship between these two varia...

Single-Period Inventory Models with multiple ordering opportunities: a review

Single-Period Inventory Models (SPIMs) or else referred as newsboy model are used to acquire optimal ordering decisions of short life-cycle products facing uncertain demand. Due to longer production and delivery lead-time, SPIM have single-ordering opportunity. To reduce the higher demand variability, the concept of SPIM with multiple ordering opportunities has been adopted in the recent literatures and has proved that the supply chain performance is better than SPIM. This paper broadly studies the literature discussing the SPIM with multiple ordering opportunities under three major classifications such as n nThis paper identifies several research gaps from the existing literatures and proposes a conceptual model based on those gaps. This study also suggests some potential scope for research.

A simulation study on strategy to mitigate leadtime uncertainty risk in the context of information sharing

Lead time is an inseparable factor of any supply chain. Lead time uncertainty is known as one of the types of supply side risks or uncertainty that affects ordering policies, inventory levels and cost, and product availability level. Information sharing between supply chain members provides opportunities to reduce the inventory levels held to face such uncertainty thereby improving the performance of the supply chain. In this context, we study the effect of sharing the information regarding replenishment leadtime on total inventory costs in a two-level supply chain. In this paper, we have proposed two-level supply chain model to analyse the effects of leadtime information and to quantify the value of the information about lead-times to the retailer. We assume that the replenishment leadtime of the supplier is random and following uniform distribution and we consider two replenishment policies the first one for the case without information sharing and the second one with information sharing. With information sharing in place the retailer exercise the strategy of employing an emergency supplier to mitigate the leadtime uncertainty. The system under consideration is formulated as a mixed integer linear programming (MILP) problem and the simulation exercise results indicate that the value of leadtime information can be significant.

Developing a Conceptual Relationship between Web Service Supply Chain Entities

The World Wide Web environment has made all kind of services available online be it a simple movie ticket booking or the most complex processes such as outsourcing and banking. The services that are offered offline and semi-online (in which case part of the service transactions are online and part of it offline) are the result of the collaboration of static entities resulting in static service supply chains. The advent of enablers like Service Oriented Architecture and development of web service applications has enabled online / dynamic service supply chain networks (SSCNs) formed by dynamic collaboration of many serving entities. The entities in web SSCNs are interdependent and the performance of one entity impacts the performance of other entities as well as overall performance of service network. It is important to study the relationship and dependency between each entity of web SSCNs. Once the relationship is identified, it will help in devising some composite performance indicator for the entire service supply chain considering the interests of service providers and clients. The globalization era demands all services to be online and useable everywhere while delivering best possible quality. The dynamic service supply chains are mostly pure online services. We take a scenario based illustration of two such online service supply chains to show the feasibility of the concept.

Analysing the impact of restructuring transportation, production and distribution on costs and environment – a case from the Thai Rubber industry

ABSTRACT Transportation and distribution are key elements to successful supply chains, however there is some disagreement regarding the impact of distribution and transportation restructuring on costs and the environment. This paper explores the use of an optimisation model of Thailand’s rubber industry supply chain, to assess the impact of distribution and transportation on costs and greenhouse gas emissions. It has previously been observed that there is a positive correlation between transportation cost reduction and environmental impact, nevertheless the correlation is not clearly established when the distribution system is restructured. This paper is divided into two parts: the first part examines the impact of transportation service capacity on distribution decisions; the second part of the paper aims to examine the impact of restructuring the distribution network considering multi-modal options on cost and greenhouse gas emissions. For both parts a scenario analysis is utilised in conjunction with an optimisation model to derive the best possible answer in terms of costs and GHG emissions. In this paper, the results obtained indicate that the impact on cost minimisation from the increase in rail freight service capacity is marginal, while the impact on GHG emission minimisation is more significant. In terms of short-sea shipping prices and service capacity, the scenario analysis shows a slight positive impact on cost minimisation but no positive or negative impact on GHG emission minimisation. Results also confirm that in terms of economic advantages, distribution network restructuring provides greater benefit to the industry than does capacity development for the transportation service.

Sensitivity Analysis of the i* Optimisation Model

Requirement elicitation is an important activity in early requirement engineering. Several well- known approaches and goal models have been developed to deal with requirement elicitation. The i* goal model is used to represent the socio-technical domains and can be used for analysis in early requirement analysis. The elicitation process is complicated by the incomplete and imprecise input data available for analysis. Imprecise and unavailable data can be captured by fuzzy logic and then it can be managed by the popular operation research techniques known as optimisation. This paper presents a formal multi- objective optimisation model, for the i* framework, with regard to requirement elicitation. The optimisation model has the capacity to handle large and complex systems. The optimisation model has been expanded to include sensitivity analysis, in order to facilitate useful information on input data for the requirement analyst. The proposed approach is explained using the London Ambulance System case study and is evaluated using a simulation based analysis.

Single stage closed loop manufacturing-remanufacturing system profitability with different combinations of internal and external return flows: an analytical study

External returns could be in the form of warranty, line returns, obsolescence and end of life in a manufacturing system. Internal returns are process rejections in the new product manufacturing line. External return, which is a fraction of the new product manufactured, is acquired from customers/third parties and processed in reverse supply chain repair centre only whereas internal returns could be repaired either in the manufacturing line or remanufacturing line. This study deals with joint decisions on pricing, internal and or external returns percentage to maximise profitability in a single stage closed-loop manufacturing-remanufacturing system for different combinations of internal and external returns flows. Results show that a model with zero manufacturing defects gives maximum profit and the one with both internal and external returns processed in the same repairing centre gives the next best solution.

Sustainability practices in tourism supply chain: Importance performance analysis

The purpose of this paper is to provide strategic recommendations for Indian hotel administrators for improving sustainability practices: environment, economic and social with respect to the supply chain members by analyzing performance dimensions and the importance attached to them.,Importance performance analysis is a tool to analyze the perception of top-level, middle-level and first-level managers in hotels. Questionnaire is developed to collect the hotel manager’s perceptions. The snowball sampling method is used for data collection.,The paper introduces specific sustainability practices, namely, environment, economic and social factors, at the interface of the tourism supply chain (TSC). This will allow the hotels to identify the importance and performance of various sustainability practices to achieve a long-term competitive advantage. The present work finds that the responding hotel managers have given highest importance to the sustainability practices within the organization and the hotel manager’s perception of sustainability practices in the TSC will vary with respect to the supply chain members.,The effort has been made to capture specific sustainability practices across the supply chain. The paper reinstates the fact that sustainability practices are not firm specific and should be practiced at the supply chain interface. The data for the study were taken from focal organizations perspective which is the hotels.,Results provide the hotel administrators to develop appropriate strategies to improve their practices and functions by analyzing their strengths and weakness regarding their tangible and intangible assets. The identified sustainability practice attributes can act as a benchmark and drive the hotel industry toward possible cost-saving conditions by prioritizing the allocation of the resources while taking care of overall performance.,Results will help the hotel administrators to identify the better sustainability practices which will reduce the negative effects and protect the Mother Nature.,The study included hotels/resorts from tourism locations: hill station, backwaters and coastal areas, specifically in the Indian context.

Optimal Reasoning of Goals in the i* Framework

Requirement analysis involves elicitation of suitable functions or operations and relevant data to support software. A requirement analyst examines different alternative options to decide on an optimal alternative option that benefits the stakeholders of the system. The decision making of alternative design option is complicated by the unavailable or incomplete and imprecise input data. Optimisation, an operation research technique, can be used as a method to solve this problem. The goal-oriented framework, such as i* is used to present social models for the analysis of a software system during the early phase of the requirements engineering process. This paper aims to develop an optimisation model for the i* goal models, using multi-objective optimisation. The optimisation model aims to fully automate the goal analysis and to handle large goal models. A simulation for the proposed approach was developed by integrating Visual C++ with Matlab and was evaluated with case studies from the existing literature. The evaluation results show that the proposed approach is feasible and offers guidance in the decision making of alternative options.