A decision support tool for sustainable freight transportation
Creators: name: Qaiser, Fahham
Publisher: name: Loughborough University
Year: 2021
Subjects: subject: 150399 Business and Management not elsewhere classified
subject: FOS: Economics and business

description: Sustainability issues (including economy, environment and society) are increasingly a growing concern for road freight transportation (RFT) companies. These companies face manifold challenges for example reducing their greenhouse gases (GHG) emissions for environmental sustainability, promoting employee’s health and safety for societal sustainability and ensuring the profitability by operating on low margins for economic sustainability. However, balancing these three dimensions of sustainability is extremely challenging given their different performance objectives. This research aims to provide a decision support system to help RFT companies to effectively manage three dimensions of sustainability and its performance. A rigorous mixed-methods case study research is employed with abductive approach to address this problem. First, a list of Key Performance Indicators (KPIs) and a broad set of good practices are identified through semi-structured interviews, analysis of literature and sustainability reports of RFT companies. Secondly, a three-staged survey is used to collect data from experts in the UK. A novel multi-attribute decision making (MADM) method (Intuitionistic Fuzzy Analytical Hierarchy Process (IF-AHP)) integrated with data mining technique (K-means and K nearest neighbour (KNN)) are used to determine KPIs weights, evaluating sustainability performance and prioritise collaborative processes for the RFT companies. There are four main theoretical contributions of this research. First, a novel sustainability performance measurement framework of KPIs along with utilising advanced method i.e. IFAHP to calculate weights of KPIs is proposed. Second, a novel integrated data mining technique based on K means, K nearest neighbour (KNN) and case-based reasoning is applied to develop a sustainability maturity model for evaluating and improving sustainability performance of RFT companies. Third, a novel integrated decision support framework based on IF-AHP and Intuitionistic Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) is proposed and validated through unique application of prioritising collaborative processes for sustainability in RFT. Fourth, the research draws on theory of sustainability, decision theory, contingency theory and relational view theory and extends their scope of applications in the context of sustainable road freight transportation. The research provides practical implications to the managers of RFT companies by developing a decision support system (DSS) to manage their sustainability performance. This enables managers to identify the right set of KPIs, their prioritisation and evaluation of sustainability performance. This research provides a practical and user-friendly tool by recommending good practices based on the KPIs needing improvement and organisational needs. This research also provides a decision support framework (DSF) for RFT companies to prioritise their collaborative processes with their partners in horizontal collaboration to achieving sustainable collaborative advantage. Last, the limitations of this research along with the direction for future research are outlined for the area of sustainable freight transportation.