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The expected learning outcomes are to understand the complexities involved in the integration of two carriers with different business strategies and approaches, the merger of two brands with distinct personas and identities and the confluence of two different cultures; figure out the strategic options in front of the Tata Group and how it can deal with various macro- and micro-level business challenges, defy the financial hiccups and manoeuvre the operational complexities to accomplish mission Vihaan.AI; and develop a pragmatic approach to macro and micro business environmental scanning for making strategic business decisions.

In November 2022, Tata Group, the salt to software conglomerate, announced the merger of Air India (AI) and Vistara. This would lead to the formation of the full-service airline under the brand name “Air India”. The obvious reason behind this was the higher recognition, salience and recall of the brand AI as compared with Vistara in the global market. The Tata Group envisaged the brand AI to be a significant international aviation player with the heritage, persona and ethos of the brand Vistara in the renewed manifestation of AI. To realise these goals, Tata Group laid down an ambitious plan called “Vihaan.AI”, which was aimed at capturing a domestic market share of 30% by 2027.

This case study can be taught as part of undergraduate- and postgraduate-level management programmes.

Teaching notes are available for educators only.

CSS 11: Strategy.

Mobile travel apps (MTA) smart features were identified based on recent travel application (app) trends and a literature review of MTA smart features. Subsequently, the MTA features that could be prioritised to increase user interest in MTA were determined. The MTA smart feature development challenges that should be mitigated were also identified.

The app identification and selection were based on the one-stop solution characteristics containing the common function of travel apps and eight MTA smart features. A total of 193 Apple apps and 250 Google apps were identified, where 36 apps that met the inclusion and exclusion criteria based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart were selected for evaluation.

The high user ratings for apps from both app stores revealed the acceptance of smart technology in the tourism industry. Geolocation tracking services, travel itinerary generators, and real-time personalisation and recommendation were the three major features available in the included MTA. The challenges of MTA with smart features were highlighted from the tourism organisation, app developer and user perspectives.

The findings can guide tourism organisations and app developers on the smart features that MTA should offer for user engagement. Technological organisations could optimise their technology stack by considering the identified smart features. The findings are valuable for scholars in terms of MTA aesthetics and usability to gain acceptability. The development challenges included significant investment in technology, location accuracy and privacy concerns when implementing MTA smart features.

The previous literature mainly focused on evaluating app quality, assessing app functionality, and user ratings using the Mobile Application Rating Scale, and scoping reviews of MTA articles. Contrastingly, this study is among the first in which MTA smart features were examined from a developer-centric perspective. Moreover, it is suggested that MTA includes integrated smart features for better tourism services and market penetration in the tourism industry.

This study aims to identify the challenges faced by urban destinations in Spain in the current transitional stage towards a new reality of tourism, caused by the outbreak of COVID-19 and the ongoing global changes in the tourism industry.

An extensive literature review and an analysis of current debates were conducted to identify the different factors that have influenced the recent tourism phenomenon and the development of destinations on a global, regional-national and local-urban scale.

Four main challenges are identified, including the new mobility patterns of the population; information and communication technologies and the digitalisation process in urban and tourism management; sustainability, as a factor of the competitiveness, stability and viability of urban destinations; and governance in urban destinations.

The study’s findings provide valuable insights for urban destination managers to make informed decisions and adapt to the new reality of tourism.

The objective of this study is to systematically identify, categorize and assess the driving factors and interdependencies associated with various types of healthcare waste. The study specifically focuses on waste that has been managed or is recommended for treatment through the application of Lean Six Sigma (LSS) methodologies.

To accomplish the study’s objectives, interpretive structural modeling (ISM) was utilized. This analytical tool aided in quantifying the driving power and dependencies of each form of healthcare waste, referred to as “enablers,” as well as their related variables. As a result, these enablers were classified into four distinct categories: autonomous, dependent, linkage and drivers or independents.

In the healthcare sector, the “high cost” (HC) emerges as an autonomous variable, operating with substantial independence. Conversely, variables such as skill wastage, poor service quality and low patient satisfaction are identified as dependent variables. These are distinguished by their low driving power and high dependency. On the flip side, variables related to transportation, production, processing and defect waste manifest strong driving forces and minimal dependencies, categorizing them as independent factors. Notably, inventory waste (IW) is highlighted as a salient issue within the healthcare domain, given its propensity to engender additional forms of waste.

Employing the ISM model, along with comprehensive case study analyses, provides a detailed framework for examining the complex hierarchies of waste existing within the healthcare sector. This methodological approach equips healthcare leaders with the tools to accurately pinpoint and eliminate unnecessary expenditures, thereby optimizing operational efficiency and enhancing patient satisfaction. Of particular significance, the study calls attention to the key role of IW, which often acts as a trigger for other forms of waste in the sector, thus identifying a crucial area requiring focused intervention and improvement.

This research reveals new insights into how waste variables are structured in healthcare, offering a useful guide for managers looking to make their waste-reduction strategies more efficient. These insights are highly relevant not just for healthcare providers but also for the administrators and researchers who are helping to shape the industry. Using the classification and ranking model developed in this study, healthcare organizations can more easily spot and address common types of waste. In addition, the model serves as a useful tool for practitioners, helping them gain a deeper, more detailed understanding of how different factors are connected in efforts to reduce waste.