Proactive management in the context of construction supply chains

Abstract

Proactive management addresses problems in advance. It is advantageous over reactive management that does not respond to any issues until they grow to become obvious and critical problems. However, scarce studies to date investigate proactive management from the perspective of construction supply chains. To overcome the limitation within existing studies, this research explores the significance of proactive management in the context of construction supply chains through a thorough investigation. The investigation in this research adopts a mix of a literature review, a questionnaire survey and a series of interviews. This research provides clear evidence for an increasing prevalence of proactive management in today’s construction practice. Proactive management proves to significantly contribute to both problem avoidance/minimization and continuous improvement. Compared to supply chain integration, supply chain collaboration is found to have a closer linkage with proactive management. This research highlights the importance of developing a proactive and collaborative culture in construction.     

Supporting the collaborative decision-making process in an automotive supply chain with a multi-agent system

Collaborative initiatives such as collaborative design, collaborative planning and forecasting, and open collective innovation are increasingly accepted as approaches that can effectively support decision-making (DM) processes in a range of different industries. However, justifying and demonstrating the benefits of collaborative solutions remains a challenge and has been under-researched. Demonstrating the feasibility of implementing collaborative solutions as opposed to traditional, linear and transactional solutions is even less evident. The purpose of this paper is to conceive a collaborative solution that supports the multi-level DM process in a real, tree-based automotive supply chain environment. The hypothesis presented posits that by sharing information collaboratively, improvements in terms of the profit and service levels will be found within the supply chain and at every supply chain node.     

含交付时间不确定性的供应链协调策略研究

分析含有交付时间不确定性的季节性供应链管理问题.如果在供应链中共享供应商的交付时间不确定性信息,零售商可以调整订货量,减少销售损失,就有可能提高供应链的整体利润.分析指出,当交付时间不确定性程度大时,信息共享能提高改进供应链绩效的可能性,但不一定能提高供应链的整体绩效,因而,仅仅采用信息共享有应用价值,但有一定的局限性.进一步分析发现,存在能协调这种含有交付时间不确定性供应链策略,能使供应链达到整体绩效最大化,并且对供应链的利润进行分配,协调策略能有效地弥补信息共享的局限性.     

A decision support system for a third-party coordinator managing supply chain with demand uncertainty

Global supply chains reduce cost but increase lead times, complexities and uncertainties. Retailers in consumer products industry are getting shorter lead time to respond to market demand. To meet this challenge, many rely on third party supply chain managers (SCMs) for economically supplying required quantities of finished products quickly. However, due to shorter ‘time to market’, the SCM has to procure raw materials and start production process based on expected demand. Since SCM absorbs financial penalties associated with under- and over-estimation of demand from retailer, finding an optimal production lot size and product customisation strategy are essential to an SCM's operation. We develop a profit maximisation model and provide a close-form solution that allows an SCM to calculate optimal production lot size. The model is used to examine profitability of postponing product customisation. Finally, the effect of demand variation on SCM's profitability is explored.     

A knowledge chain management framework to support integrated decisions in global supply chains

Knowledge management has been identified as a key enabler to achieve organisation’s value chain competitiveness. It, however, has been facing fresh challenges in a global supply chain setting. This paper proposes a global knowledge chain management (GKCM) framework that identifies and prioritises critical knowledge that a global supply chain can focus on to support integrated decisions. The framework explores three types of global context knowledge, namely global market knowledge, global capacity knowledge and global supply network configuration knowledge. Empirical study has been undertaken within the manufacturing industry to evaluate the GKCM framework. Analytic network process has been explored as a key method to assess the importance of the global knowledge constructs from supply chain managers’ perspectives. A key contribution of the paper is that it advances existing knowledge chain management approaches within one organisation and its local supply chain to include the global context knowledge applicable to global manufacturing settings, and highlights how the GKCM framework can support global supply chain integrated decisions.     

Firm-level correlates of emergent green supply chain management practices in the Chinese context

Greening the supply chain is increasingly a concern for many business enterprises and a challenge for logistics management in the 21st century. Of particular concern is how to arouse organizational environmental awareness and put environmental activities into practice in the logistics activities of their supply chains. This paper investigates the correlation of two major factors, organizational learning and management support, with the extent of adoption of green supply chain management (GSCM) practices in Chinese manufacturing firms, where their inbound and outbound logistics activities are potential polluters to the environment. Organizational and operational learning was derived from the firm's experience with programs such as total quality management and environmental management systems. Management support included support for GSCM ideas and practices from top and middle-level management and cooperation across organizational functions. We find significant positive relationships between organizational learning mechanisms, organizational support and the adoption of GSCM practices, after controlling for a number of other influences including regulations, marketing, supplier, cost pressures, industry levels of the relevant practice and organizational size. Implications of our findings on logistics management are discussed.     

A decision support system for modelling and implementing the supply network configuration and operations scheduling problem in the machine tool industry

This paper presents a decision support system to simultaneously solve the supply network configuration problem and the operations scheduling problem for the machine tool industry. A novel database structure, which is able to consider alternative operations and alternative bills of material, has been used. An algorithm for complete enumeration to determine all the feasible solutions using stroke graphs is introduced. A multiagent-based simulator evaluates the different key performance indicators that the supply network deals with for each alternative solution (e.g. workload, profits, delivery times, etc.) to determine that ‘satisficed’ by the collaborative decision-making among its members. A case study based on a Spanish company that assembles highly customised machines and tools in several European plants is considered. From the experiments results based on data linked to this industry, it will be demonstrated that the tool is potentially useful for stakeholders and for the central decision-maker to make decisions collaboratively in a multisite context case.     

A Structural model for the impact of supply chain relationship traits on project performance in construction

The objectives of this study are to discover the supply chain relationship traits in construction and their impact on the project performance. Using factor analysis technique, the supply chain relationship traits were determined to be collaboration in the supply chain, support and commitment to the supply chain, and sharing the benefits and risks. A two-step SEM model was then established to test the hypothesised relationship between the supply chain relationship traits and the project performance. The findings indicated that the supply chain relationship traits have a significant positive impact on the project performance. This study contributes to the body of knowledge relating to the construction supply chain management. The findings may help the parties to identify the attributes that may improve the relationships among them and result in better project performance.     

Systemic approach to supply chain management through the viable system model and the theory of constraints

In today’s environment, Supply Chain Management (SCM) takes a key role in business strategy. A major challenge is achieving high customer service level under a reasonable operating expense and investment. The traditional approach to SCM, based on local optimisation, is a proven cause of meaningful inefficiencies – e.g. the Bullwhip Effect – that obstruct the throughput. The systemic (holistic) approach, based on global optimisation, has been shown to perform significantly better. Nevertheless, it is not widely expanded, since the implementation of an efficient solution requires a suitable scheme. Under these circumstances, this paper proposes an integrative framework for supply chain collaboration aimed at increasing its efficiency. This is based on the combined application of the Beer’s Viable System Model (VSM) and the Goldratt’s Theory of Constraints (TOC). VSM defines the systemic structure of the supply chain and orchestrates the collaboration, while TOC implements the systemic behaviour – i.e. integrate processes – and define performance measures. To support this proposal, we detail its application to the widely used Beer Game scenario. In addition, we discuss its implementation in real supply chains, highlighting the key points that must be considered.     

Critical success factors of green supply chain management for achieving sustainability in Indian automobile industry

The aim of this study was to identify and analyse the key success factors behind successful achievement of environment sustainability in Indian automobile industry supply chains. Here, critical success factors (CSFs) and performance measures of green supply chain management (GSCM) have been identified through extensive literature review and discussions with experts from Indian automobile industry. Based on the literature review, a questionnaire was designed and 123 final responses were considered. Six CSFs to implement GSCM for achieving sustainability and four expected performance measures of GSCM practices implementation were extracted using factor analysis. interpretive ranking process (IRP) modelling approach is employed to examine the contextual relationships among CSFs and to rank them with respect to performance measures. The developed IRP model shows that the CSF ‘Competitiveness’ is the most important CSF for achieving sustainability in Indian automobile industry through GSCM practices. This study is one of the few that have considered the environmental sustainability practices in the automobile industry in India and their implications on sectoral economy. The results of this study may help the mangers/SC practitioners/Governments/Customers in making strategic and tactical decisions regarding successful implementation of GSCM practices in Indian automobile industry with a sustainability focus. The developed framework provides a comprehensive perspective for assessing the synergistic impact of CSFs on GSCM performances and can act as ready reckoner for the practitioners. As there is very limited work presented in literature using IRP, this piece of work would provide a better understanding of this relatively new ranking methodology.     

Universal supplier selection via multi-dimensional auction mechanisms for two-way competition in oligopoly market of supply chain

Allocation of the tasks in competitive market conditions at each echelon of the supply chain is an important activity in the supply chain. The task allocation problem, referred to as supply chain formation process, normally faces information asymmetry in the supply chain. The information asymmetry is caused by rational and intelligent players trying to maximize their own profit rather than opt for the supply chain profit as a whole. Thus, the process of allocating tasks in such situations becomes difficult and will result in externalities in the supply chain trades. These externalities can be internalized with present methodologies in the literature. In this paper, the major internalization methods in different contexts are considered. Lagrange relaxation and Vickery Clarke Groves (VCG) auction mechanism are explored in order to form a supply chain. This paper proposes the multi-stage auction mechanism analyzing two-way competitions, a Bertrand and Cournot competition where price per unit and quantity are the underlying two parameters in a utility analysis. To analyze the problem in real life, the industry example of Indian Railway Catering and Tourism Corporation Ltd. (IRCTC) procurement process has been taken which demonstrates the usability of the proposed framework.     

Quantifying the effectiveness of VMI and integrated inventory management in a supply chain with uncertain lead-times and uncertain demands

This article considers the inventory management problem in a supply chain with uncertain replenishment lead-times and uncertain demands. The optimal integrated inventory management (IIM) policy is developed using stochastic dynamic programming theory. The IIM policy is contrasted with two pull-type vendor-managed inventory policies (VMI-1 and VMI-2) and a traditional retailer-managed inventory policy (RMI). Computational results show that in such stochastic supply chains, IIM performs about 23, 15, and 3% better than the optimised RMI, VMI-1 and VMI-2 policies, respectively, while two VMI policies are about 8 and 20% better than the best RMI. The basestock-based VMI-2 is a very good form of VMI. The ANOVA analysis reveals that the replenishment lead-times have the largest effect on the relative performance between IIM and other policies. Numerical examples demonstrated that the IIM policy has good structural properties and can be characterised by a set of switching curves.     

Risk analysis of estimates for cost of quality in supply chain: a case study

Risk analysis for Cost of Quality (CoQ) in supply chain has not been adequately researched as evidenced in the literature. This paper attempts to analyse risk involved in estimating elements of CoQ in the internal supply chain of an integrated aluminium manufacturing company. We have applied grounded theory methodology on accounting codes of the case company primarily to bring out various elements of CoQ in its internal supply chain. They are categorized as ‘cost of prevention’, ‘cost of defective inputs’, ‘cost of defect in process’, and ‘cost of defect in output’. These elements are considered to be risky due to availability of partial information in past records of accounts while applying grounded theory methodology. In order to estimate the range and probabilities of all possible outcomes of various categories CoQ in the supply chain, Monte Carlo simulation has been used. The results have facilitated decision makers in strategic total quality management.     

A linear programming based heuristic algorithm for charge and discharge scheduling of electric vehicles in a building energy management system

Electric vehicles (EVs) are becoming an attractive alternative to gasoline vehicles owing to the increase of greenhouse gas emissions and gasoline prices. EVs are also expected to function as battery storages for stabilizing large fluctuations in the power grid through the vehicle-to-grid power system, which requires smart charge and discharge scheduling algorithms. In this paper, we develop a linear programming based heuristic algorithm on a time–space network model for charge and discharge scheduling of EVs. We also develop an improved two-stage heuristic algorithm to cope with uncertain demands and departure times of EVs, and evaluate the effect of the smart charge and discharge scheduling of EVs on a peak load reduction in a building energy management system.