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Since conducting agile strategies provides sustainable passenger satisfaction and revenue by replacing applied policies with more profitable ones rapidly, the focus of this study is to evaluate agile attributes for managing low-cost carriers (LCCs) operations by means of resources and competences based on dynamic capabilities built on resource-based view (RBV) theory and to achieve sustainable competitive advantage in a volatile and dynamic air transport environment. LCCs in Turkey are also evaluated in this study since the competition among LCCs is high to gain market share and they can adapt quickly to all kinds of circumstances.

Two well-known Multi-Criteria Decision-Making Methods (MCDM) named as the Stepwise Weight Assessment Ratio Analysis (SWARA) and multi-attributive border approximation area comparison (MABAC) methods by employing Picture fuzzy sets (PiFS) are employed to determine weight of agile attributes and superiority of LCCs based on agile attributes in the market, respectively. To check the consistency and robustness of the results for the proposed approach, comparative and sensitivity analysis are performed at the end of the study.

While the ranking orders of agile attributes are Strategic Responsiveness (AG1), Financial Management (AG4), Quality (AG2), Digital integration (AG3) and Reliability (AG5), respectively, LCC2 is selected as the best agile airline company in Turkey with respect to agile attributes. SWARA and MABAC method based on PiFS is appropriate and effective method to evaluate agile attributes that has important reference value for the airline companies in aviation industry.

The findings of this study will support managers in the airline industry to conduct airline operations more flexibly and effectively to take sustainable competitive advantage in unexpected and dynamic environment.

To the author' best knowledge, this study is the first developed to identify the attributes necessary to increase agility in LCCs. Thus, as a systematic tool, a framework is developed for the implementation of agile attributes to achieve sustainable competitive advantage in the airline industry and presented a roadmap for airline managers to deal with crises and challenging situations by satisfying customer and increasing competitiveness.

This study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

This article analyzes research on digital transformation in the tourism sector, providing insights into leading work, authors, journals, trends and future research opportunities. However, limited in-depth research exists on this topic, and the existing studies lack an understanding of its development, scope and relevant areas.

The study utilized the Scopus database to identify 61 articles on digital transformation in the tourism sector. The research employed VOSviewer software to analyze publication and citation structure, incorporating bibliometric variables like co-authorship, co-citation network, keywords co-occurrence network and bibliographic coupling.

The study yielded valuable insights from top-cited articles, revealing their contributions to digital transformation in tourism research. It also highlighted publication trends and the impact of authors, journals and studies and conducted co-occurrence, co-authorship and bibliographic analyses to identify key trends and issues in the tourism sector. The study calls for further examination of the digital revolution in tourism research and outlines future opportunities for researchers in this area.

To enhance the comprehensiveness of data collection, it is recommended that researchers consider including publications from databases such as WOS (Web of Science), Dimensions and PubMed in addition to the Scopus database. This broader inclusion of sources can provide different network structures and valuable insights from the field of digital transformation in the tourism sector.

The research provides substantial value to the study of digital transformation in tourism by focusing on bibliometric data from the Scopus database for the period from 2017 to 2022. By analyzing this data, it identifies significant trends in digital transformation within tourism research. Additionally, the study uncovers new areas of digitization in the tourism sector, further enhancing its value and relevance.

This study aims to offer an overview of hospitality and tourism research on artificial intelligence (AI) and its impact on the industry. More specifically, this study examines hospitality and tourism AI research trends in hospitality and tourism customer service experience creation and delivery, service failure and recovery, human resources and organizational behavior. Based on the review, this study identifies the challenges and opportunities and provides directions for future studies.

A narrative synthesis approach was used to review the hospitality and tourism research on AI and its impact on various aspects of the industry.

AI and AI applications in customer service experience creation and delivery and its possible effects on employees and organizations are viewed as a double-edged sword. Although the use of AI and AI applications offers various benefits, there are also serious concerns over the ethical use of AI, the replacement of human employees by AI-powered devices, discomfort among customers and employees and trust toward AI.

The paper offers an updated holistic overview of AI and its implications in different facets of the hospitality and tourism industry. Challenges and opportunities are discussed to foster future discussions on the use of AI among scholars and industry professionals.

The purpose of this study is to provide an overview of the research conducted on hospitality and tourism articles published in Q1 category journals from 1990 to 2023. This study also aims to measure the topic prevalence in selected journals throughout the years, their change over time and similarities of journals.

Latent dirichlet allocation algorithm is used as a topic modeling method to identify and analyze topics in hospitality and tourism research over the past 30 years.

The results of the study indicate that hospitality and tourism research has recently focused on topics such as employee behavior, customer satisfaction, online reviews, medical tourism and tourist experience. However, the results also indicate a negative trend in topics such as hotel management, sustainability, profession, economic growth and tourist destination.

This study can be used to examine the evolution of research patterns over time, find hot and cold themes and uncover untapped or understudied areas. This can aid academics in their investigations and practitioners in making sound strategic decisions.

This study contributes to the existing literature by providing a new approach and comprehensive analysis of hospitality and tourism research topics. It delineates an overview of the progression of hospitality and tourism research over the past 30 years, identifies the trending topics and explores the potential impacts that these identified topics may have on future studies.

Given the intensified competitiveness in the wine retail industry, partnering with quality suppliers becomes critical to ensure a steady supply of high-quality products and sustainable business growth. This study aims to explore how wine supplier quality attributes impact wine retail businesses and if such effects differ depending on wine retail types.

Data were obtained from wine purchasing managers in Korea. To validate the proposed relationships, structural equation modeling was used. A multigroup analysis was conducted to test distinct roles of on/off-premise wine retail types within this research framework.

Results support the significance of supplier quality attributes in shaping the landscape of wine retail businesses. Operational and strategic benefits exhibited a positive effect on both financial performance and suppliers’ relationship satisfaction, thereby improving the intent to continue working with suppliers. This study revealed noteworthy distinctions in the effects of supplier quality attributes on operational and strategic benefits between on-premise and off-premise wine retailers.

Findings provide valuable insights to wine suppliers and buyers concerning the establishment of a mutually beneficial long-term interdependent relationship. The approach sheds light on the unique dynamics of wine retail types, contributing to a more comprehensive understanding of the distinct roles of supplier quality attributes on on-premise and off-premise retailers.

This study developed an integrative framework, emphasizing the importance of supplier quality attributes in the wine retail industry. This model offers valuable insights into creating favorable buyer–supplier relationships that result in mutual benefits for both wine retailers and suppliers.

The trend toward subscription economy accelerated the rise of access-based consumption models for durable consumer goods, replacing individual ownership with subscription contracts. At the same time, disruptive platform businesses have arisen in several consumer markets, bypassing traditional value chains while growing through network effects. In a conceptual approach, the authors address the future market for durable consumer goods in light of developments toward access-based consumption, subscription models and platform business models.

In a conceptual approach, the authors apply a scenario analysis following the Framework Foresight method and address trends, constants, plans and projections shaping the future market of subscriptions for durable goods. The authors create a baseline scenario and two alternative scenarios for the future of consumer durables and thereby discuss platform growth stages and implications for manufacturer brands.

The rising market power of platform companies leads to a baseline scenario where these platforms enter the market of subscriptions for durable goods. Alternative scenario 1 addresses the successful market entry of new platform businesses. In contrast, alternative scenario 2 describes the rise of manufacturer brand platforms.

This conceptual research enriches the discussion of access-based business models by creating scenarios depicting possible future developments. Moreover, it adds to the increasing focus on platform business models and thereby addresses the role of traditional manufacturer brands in markets for durable consumer goods subscriptions.

Most of the previous studies agree about the significance of user satisfaction in ensuring the endurance of information systems (ISs). Accordingly, it is crucial to investigate the effect of e-Government systems on individual end-user satisfaction as more and more countries adopt and deploy such Government Financial Management Information Systems (GFMIS) in the era of digital transformation. Because of this, the purpose of this study is to investigate the factors that contribute to the success of GFMIS in Jordan and ultimately the satisfaction of its users.

The IS success model developed by DeLone and McLean (2003) serves as the theoretical underpinning for the current research. Adding training quality as a new variable to the proposed model has been found to further increase the satisfaction of GFMIS users. A total of 104 GFMIS users in Jordan provided the data used to verify the model. The partial least squares-structural equation modelling was used to test the hypotheses.

The empirical findings indicated that GFMIS user satisfaction is significantly affected by information quality, service quality and perceived usefulness; meanwhile, system quality is only partially supported. The research also showed that the level of satisfaction among Jordanian GFMIS users was related to the quality of training they received.

This study fills a crucial literature gap by developing a research model that can help improve GFMIS usage towards attaining greater performance amongst government agencies in Jordan.

This study aims to investigate earnings management practice of classification shifting of revenues in Chinese-listed firms.

The study employs a dataset of 2,920 A-listed firms from Chinese stock exchanges of Shanghai and Shenzhen for the period of 2003–2019. We apply both univariate and panel regression analysis by using fixed effect estimation with robust standard errors.

Our findings reveal that firms misclassify revenues by taking advantage of the flexibility provided by applicable financial reporting standards. The empirical evidence obtained through regression analysis suggest that managers reclassify non-operating revenues as operating revenue to alter the economic reality while seeking the advantage of financial reports users’ vulnerability for valuing the upper half of income statement items more as compared to lower part. The results further indicate that international financial reporting standards adoption inhibits the earnings management practices using classification shifting of revenues. It is also concluded that firms, which are suffering losses or having low growth, are more persistently involved in misclassification of revenues.

The study is unique from the point of view that it investigates earnings management from the prospective of revenue’s classification in an emerging market characterized by various market imperfections such as lower investor protection and higher information asymmetry.

The purpose of this study is to provide an optimal joint strategy of multi-period pricing and sales effort for a retailer with a logit choice demand in an integrated channel.

Customer demand is characterized by a logit choice model, it varies over time and is influenced by price and sales effort. The multi-period decision model for the retailer is constructed using a discrete-time dynamic programming method to determine the optimal price and sales effort in each period.

When the inventory level does not exceed a certain threshold, decreasing price and increasing sales effort over time or as inventory level increases are the optimal strategies. However, once the inventory level exceeds the threshold, the optimal strategy is to maintain both price and sales effort constant as the inventory level changes or to increase price and decrease sales effort over time. Additionally, the greater the influence of sales effort on demand or the higher the arrival rate of customers, the higher the optimal price and the greater the optimal sales effort level.

This study contributes to the existing research on dynamic pricing and sales effort in integrated channels by incorporating a logit choice model. Furthermore, it provides valuable management insights for retailers operating in an integrated channel to make pricing and sales effort decisions based on inventory level and time period.