Decision model innovation for competitive productivity (CP) in the airport industry

Abstract

Purpose The purpose of this paper is to explore the impact of decision model innovation (DMI), set on the decision-making support for the customers, on customer satisfaction and the firm’s competitive productivity (FCP). Design/methodology/approach This study operationalizes the concept of DMI by developing a decision support journey (DSJ) model for the airport industry, using the case of Zurich Airport and its ecosystem. This paper then explores how this DSJ impacts the FCP of Zurich Airport. Findings This study finds that applying DMI shows potential to improve talent management, resource management and corporate culture, leading to a higher FCP. By centralizing the decision-making process of its customer and decision support, executives gain essential insights into the actual needs of their customers. This enables firms to adapt their products and services to the actual needs of the customer, which leads to higher performance. Research limitations/implications This study explores the complementarity between DMI and FCP, exploring how operationalizing the concept through DSJ impacts FCP elements, including talent management, resource management and overall corporate culture. This extends extant work on improving non-aeronautical revenues in dynamic environments within airport ecosystems as a converging industry setting. Practical implications Existing airport digital applications providing minimal support should be expanded to provide an interaction and exchange platform for airport ecosystem players and customers. This paper finds that the firm adopting DMI in the airport/airline industry can set up a win-win situation to achieve competitive productivity by providing decision-making support and valuable insights to its customers. Originality/value This study is among the first to apply DMI toward improving FCP in the airport industry. It treats airports as an ecosystem of converging industries that can benefit by incorporating customer-focused digitally-enabled solutions to improve decision-making and customer satisfaction.

Assessing the application of multi-criteria decision making techniques in hospitality and tourism research: a bibliometric study

“…For instance, key components of high quality chat-bots at tourism attractions, museums and airports could be determined by MCDM techniques (Chung et al , 2020). According to Rengarajan et al (2021), innovation in decision models sets the ground for mutual benefit of the business and the customers. In light of the ascending digitalisation of H&T services with an increasing application of artificial intelligence (Lee et al , 2021) and Internet of Things (Elkhwesky and Elkhwesky, 2022), future research is called for to apply MCDM techniques to investigate the components as well as the quality dimensions of wining e-services/smart services in the H&T industries.…”

Decision Intelligence: Creating a Fit between Intelligence Requirements and Intelligence Processing Capacities

“…3. If required, assess the potential financial ramifications of any identified consequence for the resources Finally, being aware of the implications of their decisions, senior executives need to know how to turn them into actions and design plans to implement the strategic initiatives resulting from their decisions (Rengarajan, Moser, Tillessen, et al, 2021). For this, targets must be broken down into timely, digestible and definable goals, complemented by a roadmap to align the day-to-day activities of the organization with the overarching mandates of their strategy (Allio, 2005;Miller, Wilson, & Hickson, 2004;Saunders, Mann, & Smith, 2008).…”

“…Decision Proficiency is about understanding how to improve decision-making and increasing the capacity to deal with dynamic business environments (see Figure 9). It encourages the realization of the true value of decisions (Harrison & Pelletier, 1998) by translating them into concrete actions with implementation design and change management plans (Rengarajan, Moser, Tillessen, Narayanamurthy, & Jayanth, 2021).…”

Flying high with innovation

“…As such, airports have to focus on talent management, resource management, and work towards creating a customer-centric corporate culture, in order to improve firm competitive productivity (FCP) at a meso level. The work of Rengarajan et al (2021) has used decision model innovation (DMI) as a lens through which to assess strategic outlook of airport firms. DMI is a high-level approach for executives to evaluate the strategic outlook of a firm, and creates value for a firm's stakeholders based on transparency through advancements in the data value chain and information and communication technologies.…”