Prioritising customer-focused KPIs for home furniture delivery and assembly service using AHP: A case study of a multinational company in Thailand
Main Article Content
Abstract
Nowadays, e-commerce is growing continuously. This has resulted in a significant demand for last-mile delivery services in various business sections to deliver goods to customer homes. For a retail home furnishings business, the last-mile delivery service for this business is specific and different from other parcels. Since furniture can be large, heavy and may require assembly services. Moreover, it is necessary to make an appointment with the customer to determine the exact date and time of service. Front desk staff, drivers, and assembly workers must communicate with customers directly in several stages of the service. Accordingly, customer dissatisfaction can occur with many service activities. This affects the business performance of the last-mile service provider. Thus, the objective of this article is to identify and prioritise customer-focused key performance indicators (KPIs) of last-mile delivery and assembly services for home furniture products. First, customer-focused performance measures were obtained from a literature review and derived from the Supply Chain Operations Reference (SCOR) model regarding reliability (RL) and responsiveness (RS). These measures were then filtered out identify the KPIs through in-depth interviews with experts in the field. Next, the set of customer-focused KPIs was applied to a multinational company (MNC) in Thailand that provides home furniture delivery and an assembly service. The weights were evaluated by their customers and the respondents who have sufficient experience in home furniture delivery and assembly service through the pairwise comparison method with the AHP technique. Finally, the priority-ranking list of KPIs was obtained which can be used as a tool to improve service performance and customer satisfaction and lead to specify a business strategy. Furthermore, the MNC can apply this approach to re-evaluate the priority weight of customer-focused KPIs for other countries where the company operates such service.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Pham HC, Nguyen D, Doan C, Thai Q, Nguyen N. Last mile delivery as a competitive logistics service-A case study. Proceedings of the International Conference on Operations and Supply Chain Management; 2019 Dec 15-18; Ho Chi Minh City, Vietnam. p. 1-8.
GlobeNewswire. Last mile delivery transportation market size to hit US$ 424.3 Bn by 2030 [Internet]. 2022 [cited 2022 Jun 11]. Available from: https://www.globenewswire.com/en/news-release/2022/03/24/2409950/0/en/Last-Mile-Delivery-Transportation-Market-Size-to-Hit-US-424-3-Bn-by-2030.html.
Chen Z, Dubinsky AJ. A conceptual model of perceived customer value in e-commerce: a preliminary investigation. Psychol Mark. 2003;20(4):323-47.
Tunyaplin S, Chanpuypetch W. A SCOR-based performance evaluation framework for last-mile delivery of DIY home furniture products. Int J Logist Syst Manag. 2021;38(3):277-306.
Tunyaplin S, Chanpuypetch W. Development of a performance measurement system for a home furniture delivery and assembly logistics provider in Thailand. Int J Bus Process Integr Manag. 2019;9(4):292-306.
Kritchanchai D, Hoeur S, Engelseth P. Develop a strategy for improving healthcare logistics performance. Supply Chain Forum Int J. 2018;19(1):55-69.
Lemghari R, Okar C, Sarsri D. Benefits and limitations of the SCOR® model in Automotive Industries. MATEC Web Conf. 2018;200:00019.
Saaty TL. Decision making with the analytic hierarchy process. Int J Serv Sci. 2008;1(1):83-98.
Darko A, Chan APC, Ameyaw EE, Owusu EK, Pärn E, Edwards DJ. Review of application of analytic hierarchy process (AHP) in construction. Int J Constr Manag 2019;19(5):436-52.
Milosevic D, Stanojević A, Milošević M. AHP method in the function of logistic in development of smart cities model. The sixth International Conference Transport and Logistics; 2017 May 25-26; University of Niš, Serbia. p. 1-8.
Amchang C, Song SH. Locational preference of last mile delivery centres: a case study of Thailand parcel delivery industry. Int J Ind Distrib Bus. 2018;9(3):7-17.
Ma P, Yao N, Yang X. Service quality evaluation of terminal express delivery based on an integrated SERVQUAL-AHP-TOPSIS approach. Math Probl Eng. 2021;2021:e8883370.
Teoman S. Achieving the customized “Rights” of logistics by adopting novel technologies: a conceptual approach and literature review. UTMS J Econ. 2020;11(2):231-42.
Paduloh P, Mitta DK, Sumanto, Rosihan RI. Analysis of reverse supply chain performance with the supply chain operation reference method in beef industry. Jurnal Teknologi Industri Pertanian. 2020;30(3):329-37.
Alessio A, Maisano DA. Analysis of key performance indicators for last mile logistics with an application to the fast-fashion industry [thesis]. Italy: Politecnico di Torino; 2018.
Meier H, Lagemann H, Morlock F, Rathmann C. Key performance indicators for assessing the planning and delivery of industrial services. Procedia CIRP. 2013;11:99-104.
FarEye. Last mile delivery KPI’s & metrics to track logistics successes [Internet]. 2021 [cited 2022 Mar 11]. Available from: https://www.getfareye.com/insights/blog/last-mile-kpi-metrics.
Accenture Insights. Optimizing last-mile delivery [Internet]. 2018 [cited 2022 Mar 11]. Available from: https://www. accenture.com/nl-en/blogs/insights/optimizing-last-mile-deliveries.
Lukinskiy VS, Pimonenko MM, Paajanen M, Shulzhenko TG. Development of methodology and tools for comparative assessment of operational efficiency of KPI-based logistical infrastructure facilities. Transp Telecommun. 2013;14(3):223-9.
Giret A, Julián V, Corchado JM, Fernández A, Salido MA, Tang D. How to choose the greenest delivery plan: a framework to measure key performance indicators for sustainable urban logistics. IFIP International Conference on Advances in Production Management Systems; 2018 Aug 26-30; Seoul, South Korea. p. 181-9.
Minhans A, Shahid S, Hassan SA. Assessment of bus service-quality using passengers' perceptions. Jurnal Teknologi. 2015;73(4):61-7.
Gutierrez-Franco E, Mejia-Argueta C, Rabelo L. Data-driven methodology to support long-lasting logistics and decision making for urban last-mile operations. Sustainability. 2021;13(11):6230.
Todorovic V, Maslaric M, Bojic S, Jokic M, Mircetic D, Nikolicic S. Solutions for more sustainable distribution in the short food supply chains. Sustainability. 2018;10(10):3481.
Bhat CR, Guo JY, Sen S, Weston L. Measuring access to public transportation services: review of customer-oriented transit performance measures and methods of transit submarket identification 2005. Austin: Center for Transportation Research; 2005. Report no. 0-5178-1.
Savsar M, Nadoom A, Al-Muraished D, Ibrahim R, Al-Debasi M. Analysis of delivery and assembly operations in a furniture com-pany using discrete event simulation. Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management; 2014 Jan 7-9; Bali, Indonesia. p. 842-51.
Widmark D, Axenram R. Development of key performance indicators for the product launch process at IKEA industry [thesis]. Sweden: Lund University; 2015.
Subramanian N, Ramanathan R. A review of applications of analytic hierarchy process in operations management. Int J Prod Econ. 2012;138(2):215-41.
Oliveira Neto GC de, Oliveira JC de, Librantz AFH. Selection of logistic service providers for the transportation of refrigerated goods. Prod Plan Control. 2017;28(10):813-28.