Search results

The interviews were conducted with the respondents (the founder and Manager of De Cyber Hotel). Other data were obtained through the websites of the relevant businesses.

Siti Alia and her friends established De Cyber Hotel in January 2019. It was incorporated as a Malaysian private limited company in Cyberjaya, Selangor. Siti Alia was appointed as the hotel manager and was responsible for managing the hotel’s day-to-day operations and financial matters. Being a new budget hotel, competing with other established hotels was quite difficult. De Cyber Hotel used brochures and word-of-mouth for its promotion activities and mainly depended on walk-in guests. Siti Alia knew she had to take immediate action to ensure the hotel’s survival and could no longer rely on walk-in guests. Hence, to increase the occupancy and revenue rate, on 27 March 2019, De Cyber Hotel management decided to accept an offer from ABC Digital Booking to implement a digital booking mechanism and form a partnership for at least a year. ABC Digital Booking provided an online system to enable the listing and booking of budget accommodations and partnered with hotels to provide similar guest experiences across countries. After working and collaborating for 10 months with ABC Digital Booking, Siti Alia had to decide whether De Cyber Hotel should continue its alliance with ABC Digital Booking. Hence, she had to think thoroughly and consider the advantages and disadvantages, as well as the impact of her decision on the business.

Undergraduate Integrated Case Studies, Seminar in Management, Risk Management and Corporate Governance, Management Accounting, Financial Accounting, Strategic Management. Postgraduate Organizational Behaviour, Management Accounting and Controls, Strategic Management Accounting, Marketing Management, Hospitality Strategic Management, Entrepreneurship Development.

Capsule hotels are a revolutionary Japanese concept of lodging that dates back over four decades. On the other hand, capsule hotels are a relatively new concept for most travelers outside of Japan. Organizations within this target segment are starting to recognize the critical role that an excellent customer experience management (CEM) strategy offers in improving competitiveness and organizational success. Thus, this research provides scholastic insight into the framework of CEM by evaluating the user-generated content at capsule hotels.

This study inspected 1,304 online user-generated content from the top 10 capsule hotels from Booking.com. Leximancer 4.5 was deployed to analyze the data.

The analyses revealed nine key themes to CEM of capsule hotels which are “staff,” “hotel,” “area,” “location,” “bed,” “capsule,” “check-in,” “noisy” and “luggage”.

This research encourages hospitality and tourism executives to develop specific strategies for capsule hotels.

This research differs from previous writings in that it attempts to fill a gap in the research by offering insight into the issue in the low-budget hotel industry and by identifying key indicators that influence customer experience.

This case studies the growth of OYO Hotels (OYO) to illustrate the operational processes necessary to succeed in the service sector. The case allows for a discussion of employee- and customer-management systems, tech-driven solutions, and profit drivers. The material unfolds OYO's growth and its solution for making economy hotels discoverable and bookable online.

The case raises a series of questions around OYO's business model, its ability to translate across global markets, and growth potential. It has been successfully taught in a second-year MBA class on the management of service operations.

The purpose of this paper is to consider three factors, namely, intra-week demand fluctuations, interrelationship between the number of robots and order scheduling and conflicting objectives (i.e. cost minimization and customer satisfaction maximization), to optimize the robot logistics system.

The number of robots and the sequence of delivery orders are first optimized using the heuristic algorithm NSGACoDEM, which is designed using genetic algorithm and composite difference evolution. The superiority of this method is then confirmed by a case study of a four-star grade hotel in South Korea and several comparative experiments.

Two performance metrics reveal the superior performance of the proposed approach compared to other baseline approaches. Results of comparative experiments found that the consideration of three influencing factors in the operation design of a robot logistic system can effectively balance cost and customer satisfaction over the course of a week in hotel operation and optimize robot scheduling flexibility.

The results of this study reveal that numerous factors (e.g. intra-week demand fluctuations) can optimize the performance efficiency of robots. The proposed algorithm can be used by hotels to overcome the influence of intra-week demand fluctuations on robot scheduling flexibility effectively and thereby enhance work efficiency.

The design of a novel algorithm in this study entails enhancing the current robot logistics system. This algorithm can successfully manage cost and customer satisfaction during off-seasons and peak seasons in the hotel industry while offering diversified schemes to various types of hotels.

The paper intends to review academic research on peer to peer (P2P) accommodation sharing, notably Airbnb, for 2010–2022 and to identify the knowledge gaps for future research directions.

Numerous databases were searched using keywords. Based on the central theme of the research papers, the papers were divided into eight segments—consumer behavior, host behavior, host–guest relationship (HGR), trust in Airbnb, dominant theories in Airbnb, Airbnb regulation, Airbnb and hotels and macro impacts of Airbnb. In-depth content analysis resulted in the final 101 papers for inclusion.

The review advances comprehension of the Airbnb phenomenon by enriching the literature with new and most recent studies. Most existing Airbnb research has been conducted in Europe, USA/Canada, followed by Asian countries like China, Singapore, S. Korea and India. Future studies should include South America, Africa and other developing nations. More cross-cultural studies are required to understand consumer and host behavior in different cultural settings. Numerous proposals to fulfill the research gaps identified by the paper are discussed.

The study will give better insights into the spiraling P2P accommodation economy. The study will be useful to researchers, scholars, Airbnb, the hotel industry, vacation rental players and destination marketing organizations by relating the study findings to practical competition analysis. The study provides deeper insights into the decision-making process of both guests and hosts by examining the relevant motivators and constraints. It will also assist the Airbnb platform in identifying its strength over the traditional hotel industry and other vacation rentals. The findings will also assist policymakers in better controlling the Airbnb phenomena by providing a comprehensive view of the micro and macro environment.

The paper includes the most recent studies from Asian countries like India, Singapore, China, Korea and Taiwan, not covered by earlier reviews. Prior studies mainly focused on European and American countries. Also, the paper tried to cover the macro impacts of Airbnb in-depth and the effects of COVID-19.

This study aims to conceptualize the potential stimuli and consequences of perceived yuanfen in the accommodation service encounter by interpreting how Chinese customers perceive yuanfen during their stay in accommodations.

Online accommodation reviews containing yuanfen perception were interpreted using a grounded theory approach. Group interviews were conducted to verify the interpretations.

Positive outcome-generated emotional accommodation experiences (e.g. happiness) can elicit perceived yuanfen, which then evokes customers’ feelings of gratitude, emotional attachment to an accommodation and memorable accommodation experiences. Also, perceived yuanfen facilitates customers’ tolerance of service failures and promotes customers’ intention to stay longer at, recommend and revisit the accommodation.

This study contributes to the literature on accommodation experiences, loyalty, word-of-mouth and service recovery. Future research can explore the interventions that trigger Chinese customers’ perceived yuanfen during accommodation.

This study informs practitioners of the importance of perceived yuanfen in enhancing accommodation experiences and service recovery. Moreover, the conceptualized characteristics and stimuli of perceived yuanfen offer possible guidelines for practitioners on how to stimulate customers’ yuanfen perception.

This study fills the gap of how perceived yuanfen functions in the service encounters in accommodations.

This paper aims to investigate the links between daily review sentiment and the hotel performance measures of occupancy rate (OR), average daily rate (ADR) and revenue per available room (RevPAR).

The authors conducted review sentiment analyses in three moments (−1, −7 and −14 days) before arrival time using a data set of budget hotel performance and online reviews. The aim was to identify the effect of review sentiment in the budget hotel market on the three performance metrics.

Daily sentiment positively affects ADR and negatively affects OR and RevPAR, but only up to a certain threshold, after which the trend reverses. Prices increase with the level of sentiment, and high prices lead to low OR and RevPAR only when the sentiment scores are low. When they are high, they are associated with low rates, which lead to high OR and RevPAR.

Daily review sentiment can be viewed as a valuable “barometer” indicating a hotel’s daily operational effectiveness. Daily sentiment can thus allow hotel managers to adjust their dynamic pricing strategies more accurately.

This study identifies daily sentiment as an alternative predictor of hotel performance. In addition to the roles of valence and volume in the decision-making process, the authors found that daily review sentiment can be an “in-the-moment” factor with a high impact, encouraging consumers to complete their transactions. This study suggests that aggregated measures such as the total number of reviews and overall ratings of the hotel should not be the sole consideration in reputation management.

Cost overruns remain a persistent problem in the construction industry. Although various cost management strategies have been implemented, innovative approaches are still required. Therefore, the authors attempted to introduce and test a new cost management strategy for the construction industry.

Zero-based budgeting (ZBB) is one such method whose effectiveness has been proven in different industries over many years. Therefore, the authors initially developed two different frameworks related to the integration of ZBB into a multinational construction contractor and the application process of ZBB for a construction project in this study. Then, the effectiveness and feasibility of the proposed frameworks are tested via an actual field study in a mega construction project.

The results show savings of 0.81% of the total project budget and 4.74% of the focused cost items by following the ZBB framework compared to the traditionally estimated project budget. The feedback received from the employees in the construction company shows that ZBB could be efficiently implemented during ongoing construction projects.

The authors believe that implementing new cost management strategies such as ZBB will open doors to deal with the complex cost overrun issues and improve construction cost performances.

This manuscript is the first actual application of the ZBB cost management approach in the construction industry.

Hotels are considered one of the keys to tourism industry, without which it is impossible to visualize this industry. Setting the proper price for hotels has always been a nuisance for the decision makers because of its direct relationship with the demand for hotels. Thus, in the current study a Stackelberg game between the government (leader) and the hotels (follower) has been presented to determine the optimal price under competitive conditions. The selected hotels are different with respect to energy consumption and the environmental impact. Thus, the government makes efforts to control their prices with incentives and tariffs.

The fuzzy inference system (FIS) has also been applied to forecast the hotel demand. Therefore, first off, the demand forecast criteria have been chosen by the experts and in the continuation, it has been screened by fuzzy Delphi approach. Finally, the quantity of hotel demand is computed by the Mamdani inference system. A mathematical model has been presented for determining the optimal sequencing of hotels and minimizing the searches to find a hotel.

A case study based on the data extracted from online travel agencies (OTAs) has been presented to validate the proposed model. The results demonstrate that by the ranking position increase, the number of the tourists decreases and the higher the star number of a hotel, the lower its ranking position.

Considering the energy saving and environmental impacts in hotel pricing and considering the government's intervention in hotel revenues regarding the incentives and tariffs are the innovations of the present study.

The purpose of this paper is to be the first empirical article to provide necessary standard deviation inputs for adoption in probabilistic prognostications of hotel revenues and expenses, i.e. prognostications that consider risk. Commonly accepted methodologies to develop hotel financial projections resulting in point estimates of upcoming performance have been perceived as egregiously insufficient because they do not consider risk in lodging investments. Previous research has recommended the use of probabilistic methodologies to address this concern, and it has been recommended that analysts use Monte Carlo simulation. This methodology requires the estimation of standard deviations of specific, future hotel revenue and expense items, and this paper provides such inputs based on a large sample of actual, recent data.

This study provides actual standard deviations using a sample of recent hotel profit and loss (P&L) statements for over 3,000 hotels (Over 19,000 P&L statements) to provide analysts with empirically-supported standard deviations that may be applied to Uniform System of Accounts for the Lodging Industry (USALI) hotel revenues and expenses in hotel financial (revenue and expense) prognostications.

Findings are presented for standard deviations based on typical line items as defined in the USALI, and these findings may be used by practitioners as inputs for hotel financial projections. Findings also include that hotel revenue items generally have higher standard deviations than expense items. Findings are presented in detail in the manuscript, including overall findings, as well as findings based on hotel class.

Rather than practitioners adopting standard deviations of hotel revenue and expense line items based on guesswork or judgment, which is the current “state of the art” in hotel financial projections, this paper provides practitioners with actual standard deviations which may be adopted in probabilistic prognostications of hotel revenues and expenses.

This paper may be the first to provide practitioners with actual standard deviations, based on typical USALI line items, for adoption in probabilistic prognostications of hotel revenues and expenses.