Characteristics of the Construction Industry from the Marketing Viewpoint: Challenges and Solutions

Marketing management plays a crucial role in successful companies. However, marketing has been either misunderstood or entirely neglected in numerous construction companies because it is difficult to apply conventional marketing strategies due to specific characteristics of the industry. This study systematically investigates the characteristics of the construction industry and their effects on marketing management. A systematic literature review covering scientific papers from 1995 to 2015 (556 scientific papers) identifies 16 characteristics, which are organized into two main categories—the construction industry and construction product-related industry. 'Fragmentation' was the most highlighted characteristic.A total of 10 identified characteristics, according to the experts' opinions gathered through the questionnaire, may affect the construction marketing, of which "competitive bidding mechanism" and "project-based nature of the industry" have the greatest effect. Through a combination of literature review and focus group study, the challenges resulting from each of these 10 particularities regarding various dimensions of marketing are examined and practical solutions are suggested for overcoming these challenges. The main suggestion is the modification of the traditional marketing mix (4Ps) by eliminating “place” and adding four elements—profile, pooling, phase, and presenter. Therefore, a tailored marketing mix for construction companies is developed, with seven elements (7Ps). Moreover, marketing research and marketing intelligence systems are vital marketing tools for construction companies and should allocate adequate resources and responsible staffing levels for these activities

Designing a Supply Chain Network under the Risk of Disruptions

This paper studies a supply chain design problem with the risk of disruptions at facilities. At any point of time, the facilities are subject to various types of disruptions caused by natural disasters, man-made defections, and equipment breakdowns. We formulate the problem as a mixed-integer nonlinear program which maximizes the total profit for the whole system. The model simultaneously determines the number and location of facilities, the subset of customers to serve, the assignment of customers to facilities, and the cycle-order quantities at facilities. In order to obtain near-optimal solutions with reasonable computational requirements for large problem instances, two solution methods based on Lagrangian relaxation and genetic algorithm are developed. The effectiveness of the proposed solution approaches is shown using numerical experiments. The computational results, in addition, demonstrate that the benefits of considering disruptions in the supply chain design model can be significant

A HIERARCHICAL BAYESIAN NETWORK TO COMPARE MAINTENANCE STRATEGIES BASED ON COST AND RELIABILITY: A CASE OF ONSHORE WIND TURBINES

Today we encounter systems which consist of several vital components interacting with environment, and organizational factors. This necessitates an approach which is enabled to consider various aspects of systems and underlying interactions. To clearly illustrate this concept, we develop a Bayesian network (BN). The model enables decision makers to trace the impacts of applying different maintenance strategies on subsystems reliabilities. The model is applied to evaluate various maintenance strategies impacts on the reliability of a wind turbine. A low reliable wind turbine suffers from high turbine failure rate leading to a high Cost of Energy (CoE) due to high Operating and Maintenance (O&M) costs, as well as lost revenue from electricity sales. The most effective means of minimizing O&M costs is to improve reliability. This paper examines the consequences of applying maintenance strategies on O&M costs. Applying this integrated approach in reliability analysis can contribute to costs and revenues trade-off.&nbsp

Construction Marketing: Developing a Reference Framework

Successful companies are strongly committed to marketing management. However, marketing is either misunderstood or completely neglected in many construction companies, mainly due to the difficulty of applying conventional marketing in the industry, accompanied by the lack of sufficient research on the nature of marketing and tailored marketing theories and strategies for the construction. This study attempts to fill a part of this gap by examining the nature of the construction industry from the marketing viewpoint and developing a comprehensive framework. A systematic investigation into the nature via a combination of Kotler’s product classification system and Lovelock’s classification criteria reveals that construction is an “industrial, project-based, and primarily service-oriented” (IPS) product with specific characteristics from the marketing perspective. Based on this nature, a reference framework for strategic marketing planning is developed through a literature review based on grounded theory and using the focus group discussion as a refinement tool. The framework indicates that construction companies are involved in and should plan for three working fields—project-based activities, relationship marketing, and marketing mix-related functions. The findings provide a fundamental basis that helps researchers and practitioners gain a true understanding of the concepts and scope of construction marketing and draw a clear and practical roadmap for future work

A competitive facility location in a closed form supply chain

This paper studies capacitated facility location problem by considering green management perspectives. The proposed study considers reverse logistic problem as an alternative strategy for facility location in an attempt to take care of environmental characteristics. The resulted problem is formulated as mixed integer programming and it is classified as an NP-Hard problem. Therefore, a Lagrangian relaxation methodology is presented to reduce the complexity of the proposed problem and the solution has been implemented for some instances to examine the performance of the proposed study

A LAGRANGIAN-BASED SOLUTION ALGORITHM FOR STRATEGIC SUPPLY CHAIN DISTRIBUTION DESIGN IN UNCERTAIN ENVIRONMENT

In this paper a multi-product, multi-echelon location–allocation model for the optimization of a supply chain design is proposed. This model integrated inventory decisions into distribution network design with stochastic market demands. The goal is to select the optimum numbers, locations, and capacities of the opening warehouses so that all customer demands to be satisfied at minimum total costs of the distribution network. We develop a nonlinear mixed-integer model and propose an efficient heuristic solution procedure for the problem. The solution approach is based on Lagrangian relaxation, improved with efficient heuristic to solve complex sub-problems. Computational results indicate that the proposed method yields good solutions with high quality within a reasonable computational time for various real-size problems.Mathematical programming, supply chain management, distribution planning decisions, inventory control policy, Lagrangian relaxation

Designing a Supply Chain Network under the Risk of Disruptions

This paper studies a supply chain design problem with the risk of disruptions at facilities. At any point of time, the facilities are subject to various types of disruptions caused by natural disasters, man-made defections, and equipment breakdowns. We formulate the problem as a mixed-integer nonlinear program which maximizes the total profit for the whole system. The model simultaneously determines the number and location of facilities, the subset of customers to serve, the assignment of customers to facilities, and the cycle-order quantities at facilities. In order to obtain near-optimal solutions with reasonable computational requirements for large problem instances, two solution methods based on Lagrangian relaxation and genetic algorithm are developed. The effectiveness of the proposed solution approaches is shown using numerical experiments. The computational results, in addition, demonstrate that the benefits of considering disruptions in the supply chain design model can be significant