Airport technical efficiency and business model innovations: A case of local and regional airports in thailand

Abstract

The growth in demand for air transport as well as budget constraints have put pressure on airport development. Therefore, airports worldwide need to become financially self-reliant and obtain better managerial tools to improve airport efficiency. Business models and business model innovations have proven to have positive impacts on airport performance (Alfuah, 2019; Zott & Amitt, 2007). However, studies relating to airport business models are scarce and lack scholarly attention, especially in the context of small airports (Adler, Ülkü & Yazhemsky, 2013). Consequently, the goal of this dissertation is to design business models and propose business model innovations using a case study of local and regional airports in Thailand to fill up the paucity of knowledge in the literature. Objectives The research objectives are as follows: To analyse the situation of local and regional airports in Thailand at both the industry level and firm level To determine the factors affecting airport technical efficiency To develop a framework for designing local and regional airport business models To design airport business models and propose business model innovations for local and regional airports in Thailand Methodology The Political, Economic, Social, Technological, Environmental and Legal (PESTEL) Analysis and Analytical Hierarchy Process (AHP) were incorporated under the structure–conduct–performance paradigm to analyse the local and regional airport industry. Simultaneously, the output-oriented data development analysis (DEA) developed by Banker, Charnes and Cooper (1984) or the BCC-DEA model was employed to analyse the firm-level situation, reflecting the technical efficiency scores of 28 local and regional airports under the operations of the Department of Airports (DOA). The computed technical efficiency scores classified the airports into three strategic groups: the average group, below-average group and above-average group. Due to time and budget limitations, 3 of the 28 local and regional airports were selected based on the negative trends of their technical efficiency scores. In other words, Suratthani International Airport, Lampang Airport and Ubon Ratchathani International Airport were chosen to represent each strategic group of DOA airports: the average group, below-average group and above-average group, respectively. The Panel Least Square method was used to regress the secondary data during the 2014–2018 fiscal years, as this method is purposive for examining airport technical efficiency determinants. The airport ownership forms, service-relating policies and airport revenues acted as regressors, while the dependent variable was from the technical efficiency scores computed from the BCC-model in the first stage. The exploratory and documentary research were integrated to formulate the framework that would be useful in designing airport business models. Using the semi-structured questionnaire developed under the Business Model Canvas (BMC) of Osterwalder and Pigneur (2010), nine key informants of airport management were identified. For the documentary research, this study investigated the lessons learnt from the world’s best airport, Singapore Changi International Airport, and the world’s best regional airport, Chubu Centrair International Airport, according to Skytrax. Several related documents, such as annual reports and information from the airport newsroom, were collected.Qualitative analysis was employed in the final stage. Thirty-six key informants, both local and regional, from several airport stakeholders, including airlines, passengers, ramp operators and airport scholars, were questioned via in-depth interviews using a semi-structured questionnaire. The insightful information gleaned from stakeholders led to suggestions of proposed airport business models from which the innovation development concept was introduced. The discussions surrounding current local and regional airport business models and the lessons learnt from best practice airports provided the gap for innovating the business models. Results The PESTEL-AHP model revealed that the Air Navigation Act (No.14) BE 2562 was the strongest component, significantly impacting the overall industry by approximately 28% and shaping how DOA airports ran their businesses as a public agency. The other top 2 PESTEL elements were noted as the (1) National Strategy (2018–2037) and the (2) trend toward airport digitalisation with a pairwise estimate at 22% and 21%, respectively. For the firm-level situation analysis, the BCC-DEA model confirmed that 28 local and regional airports were technically inefficient, showing an average technical efficiency score equal to 0.188. To understand the source of technical inefficiency of local and regional airports, the econometric model reported that airport ownership patterns were found to be the most significant factors affecting technical efficiency; service-relating policies and total airport revenues also played a significant part in airport efficiency. The lessons learnt from the world’s best airports and the in-depth interviews from airport management suggest that the framework for designing business models should focus on the sustainability of an airport. Although the BMC gave a good depiction of overall airport operations, the issues relevant to sustainability should have greater awareness. Moreover, the lessons learnt revealed that a paradigm shift was undertaken by world airport business administrations to increase revenues, and best practice airports developed themselves as tourist destinations. Several key activities and value propositions were dedicated to various customer segments, not only for airlines and passengers but also for local residents, food lovers, shoppers, athletes and tourists. The study also found that organising more diverse projects and events in world airports was related to stronger, more strategic partnerships among airport stakeholders. By integrating the results from each research objective, the proposed airport business models for the 3 selected local and regional airports in Thailand were presented. Three models for innovating the current business model components were suggested to increase airport revenues and ultimately improve technical efficiency. The Airport-as-a-Tourism Platform Business Model, the Local Partner-andEngagement Business Model and the Value Proposition-Oriented Business Model were introduced, as they were the most feasible, practical and appropriate in the context of local and regional airports under DOA operations.