Search results

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).

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.

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.

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.

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.

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.

Drawing on a dynamic capability view, this study develops a decision support model that determines the most suitable configuration of strategies and challenges to adopt additive manufacturing (AM) to expedite digital transformation and performance improvement of the surgical and medical device (SMD) supply chain.

To investigate the research objective, a multi-method and multi-study research design was deployed using quality function deployment and fuzzy set qualitative comparative analysis.

The study finds that only resilience strategies or negation (i.e. minimisation) of challenges are not enough; instead, a configuration of resilience strategies and negation of challenges is highly significant in enhancing performance.

SMD supply chain decision-makers will find the decision support model presented in this study as beneficial to be resilient against various challenges in the digital transformation of service delivery process.

This study builds new knowledge of the adoption of AM technology in the SMD supply chain. The decision support model developed in this study is unique and highly effective for fostering digital transformation and enhancing SMD supply chain performance.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Airports need to look beyond airlines as their main source of revenue, utilizing customer data and other revenue streams in order to survive.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

This study aims to examine the interaction effects of chatbots’ language style and customers’ decision-making journey stage on customer’s service encounter satisfaction and the mediating role of customer perception of emotional support and informational support using the construal level theory and social support theory as conceptual frameworks.

This study used a scenario-based experiment with a 2 (chatbot’s language style: abstract language vs concrete language) × 2 (decision-making journey stage: informational stage vs transactional stage) between-subjects design.

Findings show that during the informational stage, chatbots that use abstract language style exert a strong influence on service encounter satisfaction through emotional support. During the transactional stage, chatbots that use concrete language style exert a strong impact on service encounter satisfaction through informational support.

Findings provide some suggestions for improving customer–chatbot interaction quality during online service encounters.

This study offers a novel perspective on customer interaction experience with chatbots by investigating the chatbot’s language styles at different decision-making journey stages.

Using the backdrop of an (apparently) extended visit to the West Indies, analogies with key concerns of internal audit are drawn. An unusual and refreshing way of exploring the main themes ‐ a discussion between Bill and Jack on tour in the islands ‐ forms the debate. Explores the concepts of control, necessary procedures, fraud and corruption, supporting systems, creativity and chaos, and building a corporate control facility.

Using the backdrop of an (apparently) extended visit to the West Indies, analogies with key concerns of internal audit are drawn. An unusual and refreshing way of exploring the main themes ‐ a discussion between Bill and Jack on tour in the islands ‐ forms the debate. Explores the concepts of control, necessary procedures, fraud and corruption, supporting systems, creativity and chaos, and building a corporate control facility.

The purpose of this paper is to examine the customer decision-making journey of high involvement female fashion consumers in the context of omnichannel fashion retailing.

The research is qualitative in nature, using a multi-method approach consisting of focus groups, semi-structured interviews, online diaries and follow-up interviews, with grounded theory applied to analyse the data.

The results of the study include a framework to outline the stages of the omnichannel customer decision-making journey for young high involvement female fashion consumers. The findings also reveal that an omnichannel decision-making journey is the one that predicated on risk and that consumers employ specific strategies to avoid such risks.

Due to the nature of this research, the sample size is limited and may not be generalised. Data collection was confined to Manchester, UK.

Customer journey mapping enables practitioners to view the entire shopping experience through the eyes of the customer and enables retailers' fault-find issues within the customer and brand experience.

The paper advances knowledge about fashion and consumer behaviour. The customer decision journey framework maps the emotional experiences, devices and channels encountered by high-involvement fashion consumers across each stage of the omnichannel journey.

The purpose of this research is to support responsible decision-making in Higher Education (HE) settings by understanding what type of learning journey satisfies students most in their HE experience and what they want from the learning.

This paper analyses the key tool used to assess satisfaction factors for UK students, the National Student Survey (NSS). It adopts peculiar regression statistical tests to identify the NSS items that influence “overall student satisfaction” by reviewing responses over 9 years from accountancy students at business schools located in England.

The findings of the study provide evidence that students are most satisfied with a learning journey where they are part of a course that is “well organised and running smoothly”, which provides “intellectual stimulation” that helps in developing their ability to “present themselves with confidence” and provides “academic advice and support”. The findings of the paper show that students are not satisfied so much by utilitarian aspects of learning but rather those that relate to who they are and where they are in their learning journey, the level of intellectual stimulation they have experienced, the self-confidence they have developed and the supportive relationship they have developed with academics. A factor that did not relate highly was “assessment and feedback” which has been the focus of much university resource. Results show the factors that impacted overall satisfaction are most related to students wanting to develop personal responsibility. These findings shape the key principles of responsible design and management of HE programmes and influence strategic decision-making.

Focussing on helping students experience, the type of learning journey that develops the virtue of responsibility emergent from the analysis will not only satisfy the student but will also have a knock-on effect of improving NSS scores, university league table ranking and accreditation under the Teaching Excellence Framework. The improved reputation aspects would then feed back into increased student satisfaction (Dean and Gibbs, 2015). The findings will also help HE managers and leaders to evaluate their decisions through three lenses: responsibility, students’ experience and students overall learning journey.

Much of the information published on the NSS have been predominantly descriptive and has resulted in decisions being made for students based on uninformed analysis of the survey’s results. This study uses advanced statistical modelling to evidence the relationship between factors of the NSS and overall student satisfaction providing key information regarding students’ importance to the type of learning journey they value and that this relates to a desire in wanting to develop responsibility. This study shows the link between factors of the NSS to provide useful lenses for HE managers and leaders to use to support responsible decision-making processes.

In the age of digital media, customers have access to vast digital information sources, within and outside a company's direct control. Yet managers lack a metric to capture customers' cross-media exposure and its ramifications for individual customer journeys. To solve this issue, this article introduces media entropy as a new metric for assessing cross-media exposure on the individual customer level and illustrates its effect on consumers' purchase decisions.

Building on information and signalling theory, this study proposes the entropy of company-controlled and peer-driven media sources as a measure of cross-media exposure. A probit model analyses individual-level customer journey data across more than 25,000 digital and traditional media touchpoints.

Cross-media exposure, measured as the entropy of information sources in a customer journey, drives purchase decisions. The positive effect is particularly pronounced for (1) digital (online) versus traditional (offline) media environments, (2) customers who currently do not own the brand and (3) brands that customers perceive as weak.

The proposed metric of cross-media exposure can help managers understand customers' information structures in pre-purchase phases. Assessing the consequences of customers' cross-media exposure is especially relevant for service companies that seek to support customers' information search efforts. Marketing agencies, consultancies and platform providers also need actionable customer journey metrics, particularly in early stages of the journey.

Service managers and marketers can integrate the media entropy metric into their marketing dashboards and use it to steer their investments in different media types. Researchers can include the metric in empirical models to explore customers' omni-channel journeys.