Zooming into Airbnb listings of European cities: Further investigation of the sector’s competitiveness

2021 ◽  
pp. 135481662110448
Author(s):  
Bozana Zekan ◽  
Ulrich Gunter
Keyword(s):  
Sharing Economy ◽  
Tourism Industry ◽  
Data Envelopment ◽  
Cumulative Number ◽  
Past Performance ◽  
Related Data ◽  
European Cities ◽  
Interactive Data ◽  
Input Variables ◽  
Accommodation Sector

Airbnb has a major role to play in the competitiveness of the overall accommodation sector of individual destinations and it is rather unlikely that this role will diminish in the post-COVID-19 recovery of the tourism industry. Therefore, the present study motivates the Airbnb sector to look back at its past performance for insights that can be used in setting post-pandemic targets. In particular, this research assesses competitiveness of the Airbnb listings of 28 European cities by including hotel-related data as uncontrollable input variables within interactive data envelopment analysis modeling. The contribution lies in joining Airbnb listings and hotels into the benchmarking discussion and efficiency analysis, along with looking beyond the cumulative number of listings by dissecting the overall sector into commercial and private listings—something that has not been attempted as of yet, in spite of the ever-growing body of literature on the sharing economy.

scholarly journals Understanding the Implementation of Airbnb in Urban Contexts: Towards a Categorization of European Cities

Land ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 522
Author(s):  
Laura Serrano ◽  
Antonio Sianes ◽  
Antonio Ariza-Montes
Keyword(s):  
Business Model ◽  
Local Governments ◽  
Hierarchical Cluster ◽  
Sharing Economy ◽  
Tourism Industry ◽  
European Cities ◽  
Rural And Urban ◽  
Urban Contexts ◽  
Accommodation Sector ◽  
Tourist Accommodation

The sharing economy has experienced exponential growth in recent years, especially in the short-term rentals (STRs) tourist accommodation sector. This growth has caused disruptive effects in rural and urban contexts, especially in highly touristic cities. These effects can be both positive and negative, revitalizing certain areas and bringing about tension in the socioeconomic fabric. Today, Airbnb is considered the paradigm of this sharing economy model and the STR industry leader. However, as this study suggests, on many occasions the implementation of Airbnb exhibits more of a traditional economic business model than a collaborative economic business model. Through hierarchical cluster analysis, this study identifies different groups of European cities according to the degree of professionalization of Airbnb implementation in their territory. The goal is to find similar patterns in the Airbnbisation process in major European cities, as the social, economic, and spatial impacts of various typologies are very different and even contrary. By understanding and identifying such different models implemented in each territory, better policies can be informed, and more adapted strategies can be pursued by local governments and the tourism industry.

scholarly journals An investigation into the sharing economy phenomenon in the Greek tourism industry in the accommodation sector

2017 ◽  
pp. 25-35 ◽  
Author(s):  
Vicky Katsoni
Keyword(s):  
Hospitality Industry ◽  
Business Models ◽  
Distribution Channels ◽  
Legal Framework ◽  
Sharing Economy ◽  
Tourism Industry ◽  
Considerable Controversy ◽  
Accommodation Sector ◽  
Controversial Nature ◽  
State Regional

A phenomenon that has spread as rapidly as the sharing economy, bypassing traditional distribution channels and disrupting established business models, has naturally provoked considerable controversy. Users, providers, sharing economy sites, established businesses offering similar services to those being shared (or traded, exchanged, rented, swapped or otherwise) and governments at all levels (municipality, province, nation state, regional, and even international), have found themselves on different sides of a furious debate about the present and future shape of the sharing economy. This article explores the drivers and impacts of sharing economy in the Greek hospitality industry, presents the legal framework and discusses the challenging and at times controversial nature of it.

Benchmarking of Airbnb listings: How competitive is the sharing economy sector of European cities?

2018 ◽  
Vol 25 (7) ◽  
pp. 1029-1046 ◽  
Author(s):  
Bozana Zekan ◽  
Irem Önder ◽  
Ulrich Gunter
Keyword(s):  
Data Envelopment Analysis ◽  
Hospitality Industry ◽  
Sharing Economy ◽  
Data Envelopment ◽  
Demand And Supply ◽  
On Demand ◽  
European Cities ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality

Airbnb is arguably the world’s most popular accommodation sharing platform. Its impact on demand and supply within the tourism and hospitality industry is nowadays unquestionable. The present study delves into inspecting the efficiency of Airbnb listings of European cities, as, in spite of the success of Airbnb as a whole, it cannot be presupposed that all listings are equally successful. More specifically, data envelopment analysis (DEA) is employed in this first comprehensive benchmarking attempt within the domain of the sharing economy to date. This article also makes a contribution to robustness by introducing an interactivity note to the base model, thus, inspecting the results for corroboration/discrepancies and going beyond the static analyses that are common in DEA modeling. Ultimately, this is done with the goal of highlighting opportunities for inefficient Airbnb listings to properly utilize their inputs and therefore become more competitive.

scholarly journals Measuring Tourism Efficiency of European Countries by Using Data Envelopment Analysis

2017 ◽  
Vol 13 (10) ◽  
pp. 31 ◽  
Author(s):  
Halenur Soysal-Kurt
Keyword(s):  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Returns To Scale ◽  
Tourism Industry ◽  
European Countries ◽  
Data Envelopment ◽  
Micro Level ◽  
Input Variables ◽  
Using Data ◽  
Constant Returns To Scale

This study aims to measure relative efficiency of 29 European countries with the data of the year 2013 using input-oriented and constant returns to scale Data Envelopment Analysis and to offer improvement suggestions for the countries found inefficient based on their measured relative efficiency scores. Three input and three output variables are used to assess relative performances of the countries. In this study, tourism expenses, number of employees and number of beds are used as input variables; tourism receipts, tourist arrivals and number of nights spent are used as output variables. As the result of the analysis, 16 countries are found relatively efficient and 13 countries are found relatively inefficient. This study is one of the few publications within the scope of European countries based on data envelopment analysis. Unlike most researches evaluating the efficiency of tourism establishments at the micro level, this paper is thought to contribute to the related literature as it evaluates relative efficiency of the countries at the macro level for tourism industry. Considering the variables used in the analysis, it is expected to give ideas to relatively inefficient European countries on efficiency improvement.

scholarly journals Evaluation of the Impact of Sharing Economy on Hotel Business

2020 ◽  
Vol 11 (20) ◽  
pp. 150-169 ◽  
Author(s):  
Paulína Srovnalíková ◽  
Evelina Semionovaitė ◽  
Edita Baranskaitė ◽  
Daiva Labanauskaitė
Keyword(s):  
Management Strategy ◽  
Negative Impact ◽  
Hotel Industry ◽  
Sharing Economy ◽  
Tourism Industry ◽  
Strategy Formulation ◽  
Correlation And Regression Analysis ◽  
Customer Group ◽  
Accommodation Sector ◽  
The Impact

The sharing economy is growing in the hotel industry very fast. The study is important for the hotel’s management - strategy formulation. The aim of this research is to evaluate the sharing economy effect on hotels in Lithuania. Correlation and regression analysis methods were used for achieving the aim. The study analyses if the sharing economy has caused any impact on accommodating tourists at hotels, hotels income from accommodation services, and room occupancy rate. Results reveal a positive relationship between the sharing economy and all investigated indicators of hotel activities, thus indicating that the hotel business is growing together with the sharing economy. The hotels' sector in Lithuania has continued to grow while more and more hosts and consumers joined the sharing economy. Results imply that the sharing economy is not a competitor for the Lithuanian hotels business as the sharing economy targets different tourist segment, moreover the market is capacious for both segments. Sharing economy in the accommodation sector – a niche with its own customer group. The research results are important for making correct decisions in the Lithuanian tourism industry as other researches in other countries show a negative impact on the sharing economy on the hotels' sector. The rapid growth of the sharing economy in Lithuania may oblige hotels to focus on the sharing economy and consider further actions.

scholarly journals Efficiency Institution Baitul Maal Tamwill in The Westdistrict Bandung

2020 ◽  
Vol 1 (1) ◽  
pp. 18-24
Author(s):  
Annisa Nur Hakim ◽  
A Jajang W Mahri ◽  
Aas Nurasyiah
Keyword(s):  
Data Envelopment Analysis ◽  
Research Method ◽  
Secondary Data ◽  
Data Envelopment ◽  
Analysis Technique ◽  
Dea Analysis ◽  
Input Variables ◽  
Operational Activities ◽  
A Company ◽  
Descriptive Method

Abstract.     Baitul Maal Wat Tamwil has experienced development in recent years. However, based on BMT performance data in West Bandung regency is less optimal. It is known that there are one efficient BMTs in West Bandung Regency and three BMTs that are inefficient. The cause of BMT's less optimal performance is inefficiency in operational activities. This study aims to determine the level of efficiency of BMT in West Bandung 2011-2017 period and find out the causes of inefficiency. This study uses secondary data from four BMTs in West Bandung District which are sampled. The research method used is descriptive method with Data Envelopment Analysis (DEA) analysis technique which is to measure the level of efficiency of a company. Input variables used are operating expenses, total assets, and TPF. Furthermore, the output variables used are SHU, income, and financing. Based on the results of research conducted, the conditions of the BMT in West Bandung Regency have not been perfectly efficient. There are three BMTs that have experienced inefficiencies including BMT Dana Ukhuwah, BMT Mustama, and BMT Rabbani. Keywords.          Efficiency, Baitul Maal Wat Tamwil, Data Envelopment Analysis

A Study of the Role of Trust in Sharing Economy in the Tourism Industry

2021 ◽  
Vol 12 (4) ◽  
pp. 26-38
Author(s):  
Youngkeun Choi
Keyword(s):  
Personal Information ◽  
Sharing Economy ◽  
Purchase Intentions ◽  
Tourism Industry ◽  
Intention To Purchase

The purpose of this study is to examine the antecedents of trust in sharing economy in the tourism industry which influences consumers' purchase intentions. By presenting the concept of consumers' trust in suppliers, the author develops a model that explores the effects that explain the consumers' trust in suppliers and their intention to purchase in sharing economy. For this, this study surveys 332 Korean consumers using Airbnb and analyzes the data using AMOS 24. In the results, first, consumers' perceive responsiveness of suppliers, the degree to which consumers confide the personal information of suppliers, and consumers' disposition to trust increase their trust in suppliers. Second, consumers' trust in suppliers increases their intention to purchase. Finally, consumers' perceive the responsiveness of suppliers and consumers' disposition to trust among the antecedents of consumer's trust in suppliers increase their intention to purchase through their trust in suppliers.

Measuring productivity of dairy industry companies: an approach with data envelopment analysis

2021 ◽  
Vol 11 (2) ◽  
pp. 160-177
Author(s):  
Bertha Viviana Ruales Guzmán ◽  
Gloria Isabel Rodríguez Lozano ◽  
Oscar Fernando Castellanos Domínguez
Keyword(s):  
Data Envelopment Analysis ◽  
Case Studies ◽  
Dairy Industry ◽  
Data Envelopment ◽  
Food Sector ◽  
Content Type ◽  
Financial Variables ◽  
Current State ◽  
Input Variables ◽  
Future Case

PurposeThis research had two main objectives: To measure the productivity of companies in the Colombian dairy industry and to identify efficient decision-making units (DMUs) that can be used as work sample in future case studies.Design/methodology/approachIn the measurement of productivity, financial variables were considered for a sample of 19 DMUs. Efficient companies were identified through the data envelopment analysis (DEAs) methodology with the VRS model oriented to inputs and outputs. The input variables analyzed were “current asset,” “property, plant and equipment,” “non-current liability” and “equity,” while the output variables were “revenue” and “profit.”FindingsFindings revealed that seven DMUs are efficient in the input and output orientation and that companies of different sizes and with or without quality certifications are efficient in the sample analyzed. Additionally, the benchmark efficient DMUs were identified for each of the non-efficient DMUs.Research limitations/implicationsThe implications for the research include the contribution to the theory, on the one hand, with the analysis of the current state of the literature on the use of DEA in the food sector, and on the other, with the use of DEA to measure the productivity of Colombian dairy industry companies and with the identification of a sample of efficient units that can be analyzed in future case studies.Originality/valueThis article is novel and pioneering because it measures for the first time the productivity of DMUs of the Colombian dairy industry, in addition to including the current state of the literature on the application of the DEA methodology in the food sector. These findings contribute to the consolidation of the theory and also provide inputs for researchers, practitioners, managers, and policy makers.

The Challenges and Opportunities in Addressing the Needs of Middle Eastern Tourists

2015 ◽  
pp. 136-159
Author(s):  
Nael M. Sarhan ◽  
Adela McMurray ◽  
Foula Kopanidis
Keyword(s):  
Content Analysis ◽  
Middle Eastern ◽  
Developed Countries ◽  
Tourism Industry ◽  
Gold Coast ◽  
Lack Of Information ◽  
Challenges And Opportunities ◽  
Percent Response ◽  
Accommodation Sector ◽  
Percent Response Rate

This chapter identifies and discusses the specific needs of Middle Eastern tourists visiting the Gold Coast, Queensland Australia. Based on empirical data collected through a qualitative study, self-administered questionnaires (N = 500) were distributed to Middle Eastern tourists who visited the Gold Coast and stayed at Gold Coast accommodation for at least one night. The 305 responses (61 percent response rate), generated a total number of 461 multiple responses. Content Analysis identified key themes and sub-themes associated with Islamic religious beliefs. The findings showed that the management of the Gold Coast accommodation sector had a distinct lack of information and understanding of Middle Eastern tourists' needs. This chapter provides useful managerial and marketing recommendations, including suggested best practices, to hoteliers who provide accommodation services to international tourists, such as Middle Eastern tourists, and contributes to the limited knowledge on Islamic marketing. This in turn potentially contributes to the increased success of the tourism industry in developed countries such as Australia.

scholarly journals Evaluation of Car Performances Using Data Envelopment Analysis

2018 ◽  
Vol 22 ◽  
pp. 01051
Author(s):  
Yunus GÜRAL ◽  
Ayşe Turan BUĞATEKİN
Keyword(s):  
Data Envelopment Analysis ◽  
Maximum Speed ◽  
Data Envelopment ◽  
Automotive Sector ◽  
Nonparametric Method ◽  
Maximum Torque ◽  
Acceleration Time ◽  
Input Variables ◽  
Using Data ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a nonparametric method used to examine the relative efficiencies of Decision Making Units (DMUs) on conditions where there are multiple inputs and multiple outputs. As in all sectors, it is very important for the automotive sector to operate effectively. Therefore, it is also important to measure the efficiency and find the source of the inefficiency. In this study, the performances of the DMU of the automobiles will examine using Data Envelopment Analysis. In this direction, it is aimed to assist consumers in purchasing by calculating the relative efficiencies of automobile models, determining effective and ineffective DMUs according to the wishes of the consumers. Sales price and fuel consumption are determined as input variables; maximum speed, cylinder volume, horsepower, maximum torque, luggage volume, acceleration time from 0 to 100 km are determined as output variables.

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