Peer-to-peer-travel: is Airbnb a friend or foe to hotels?

2019 ◽  
Vol 13 (4) ◽  
pp. 443-457 ◽  
Author(s):  
Oswald Mhlanga
Keyword(s):  
South Africa ◽  
Empirical Evidence ◽  
Time Series Data ◽  
Theoretical Perspective ◽  
Hotel Industry ◽  
Disruptive Innovation ◽  
Series Data ◽  
Bottom Line ◽  
Data Set ◽  
Content Type

Purpose The sharing economy has caught great attention from researchers and policymakers. However, due to the dearth of available data, not much empirical evidence has been provided. This paper aims to empirically assess the impacts of Airbnb on hotel performances in South Africa. Design/methodology/approach Using South Africa as a case study, the study measures the impacts of Airbnb on hotel performances on three key metrics, namely, room prices, occupancy and Revenue per available room (RevPAR). A difference-in-difference model is estimated using a population-based data set of 809 hotels from 2016 to 2018. Findings The results reveal that despite Airbnb significantly and negatively impacting on hotel occupancies it has a non-significant effect on hotel prices and RevPAR. Although from the theoretical perspective a disruptive innovation business model such as Airbnb can possibly have a negligible effect on hotel performances because it may attract a different group of customers and create a new market, the empirical findings of this study fail to support this theoretical hypothesis. Consequently, the findings diverge with newly developed knowledge in other markets and point to nuanced and contextual complementary effects. Research limitations/implications Although some interesting findings are revealed into his study, some caveats remain. For instance, the study relied on data from hotels not from Airbnb. If the data of Airbnb can become available, it would be interesting to further examine whether the aggregated RevPAR of Airbnb can compensate for the aggregated loss of hotel RevPAR. This type of analysis could provide a broader evaluation scope regarding the overall effect of Airbnb on hotel performances. Moreover, if a longer time series data set of hotels in the post-Airbnb time period could become available, it would be interesting to further investigate the time-varying dynamic effects of Airbnb on hotel performances. Practical implications While hotels have launched a campaign to portray Airbnb as being commercial operators looking to compete illegally with hotels for the same segment of customers, this study shows that the rhetoric has been exaggerated. Airbnb, and more broadly, vacation rentals do not represent a war with hotels. They represent an answer to a different need. Indeed, the study reveals that Airbnb’s offer is a mere supplement to the market contrary to media rhetoric that it is meant to substitute hotels. The study has several implications for practitioners. First, these results are important because they serve as evidence against news articles that claim Airbnb is driving hotels out of business. They also show that if current trends continue, employees in the hotel industry in South Africa do not need to be concerned about losing their jobs because of Airbnb’s emergence. It is also important information for investors who may be concerned that Airbnb is hurting the hotel industry’s bottom line. Second, as the share of Airbnb listings on the accommodation market varies dramatically between cities, it is likely that eventual regulations/restrictions should be introduced in the provincial levels, while most of the cities continue benefiting from the increasing number of Airbnb visitors. Originality/value To the best of the author’s knowledge, this study is the first in South Africa to provide empirical evidence that Airbnb is significantly changing consumption patterns in the hotel industry, as opposed to generating purely incremental economic activity.

Airbnb and hotels: friends, enemies or frenemies?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Oswald Mhlanga
Keyword(s):  
South Africa ◽  
Time Series Data ◽  
Sharing Economy ◽  
Disruptive Innovation ◽  
Series Data ◽  
Data Set ◽  
Content Type ◽  
Complementary Role ◽  
Triple Difference ◽  
The Impact

Purpose The purpose of this paper is to explore the intricate relationship between the flagship of the sharing economy, Airbnb and hotel revenue per available room (RevPAR) in South Africa. Design/methodology/approach To identify the impact of Airbnb on hotel RevPAR, the paper used a triple difference-in-differences framework that compares changes in cities in South Africa where Airbnb started operating relative to areas without Airbnb. A total of 569 hotels were analysed. Findings While the study finds no evidence of adverse impacts of Airbnb on hotel RevPAR, the findings show that the entry of Airbnb led to a decrease in RevPAR of budget hotels. However, its impact is more pronounced during periods of peak demand, consequently, disrupting the pricing power of hotels. Research limitations/implications The research was based on the impact of Airbnb on hotel RevPAR in hotels situated in specific cities in South Africa. Caution is therefore required when generalising the findings of this study to other hotels in other geographic areas. Moreover, if a longer time series data set of hotels in the post-Airbnb time period could become available, it would be interesting to further investigate the time-varying dynamic effects of Airbnb on hotel RevPAR. However, the findings underscore the notion that innovations are not intrinsically disruptive but only relative to another product. In so doing, the study adds to the limited body of work in the field on disruptive innovation and to the academic discourse on innovation in tourism more broadly. Practical implications First, the findings suggest the impact on hotels tends towards Airbnb generally playing a largely complementary role rather than a diversionary one. However, to increase RevPAR, hotels should systematically change their pricing models to account for flexible capacity by rethinking the wisdom of seasonal pricing and reduce prices during peak seasons to avoid inviting more competition from Airbnb. Originality/value To the best of the author’s knowledge, this paper is the first to explore the relationship between Airbnb and hotel markets using a triple difference methodology.

The effects of political, economic and financial components of country risk on housing prices in South Africa

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Paul-Francois Muzindutsi ◽  
Sanelisiwe Jamile ◽  
Nqubeko Zibani ◽  
Adefemi A. Obalade
Keyword(s):  
Risk Factors ◽  
South Africa ◽  
Housing Market ◽  
Time Series Data ◽  
Housing Prices ◽  
Political Risk ◽  
Country Risk ◽  
Series Data ◽  
Content Type ◽  
Short Run

Purpose The housing market in South Africa has the potential to drive economic growth and attract foreign investment, but it can be affected by various risk factors. This paper aims to conduct an empirical analysis of the effect of country risk components on the housing market in South Africa. Design/methodology/approach Linear and nonlinear autoregressive distributed lag (ARDL) models were used to evaluate the effects of the economic, financial and political risk factors of country risk on the prices of different segments of houses based on 276 monthly time-series data from January1995 to December 2015. Findings First, the results established that the three housing indices were more sensitive to political risk in the long run. Second, short run results showed that the three housing indices were largely influenced by their own preceding adjustments in the short run albeit minimal influences from political risk. Third, large housing segments indicated a higher magnitude of the country risk effect in South Africa. Originality/value This paper concluded that the response of housing prices to changes in the country risk components differed across the three segments of the housing market in South Africa. Consequently, this study presented the first comparison of the reactions of different housing segments to different components country risk.

Investigating the non-linear Wagner’s hypothesis in South Africa

2017 ◽  
Vol 8 (4) ◽  
pp. 462-473 ◽  
Author(s):  
Temitope Lydia A. Leshoro
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Government Spending ◽  
Time Series Data ◽  
Series Data ◽  
Unique Contribution ◽  
Content Type ◽  
Non Linear ◽  
Regression Error ◽  
The Government

Purpose The commonly adopted view of the relationship between government spending and economic growth follows the Keynesian approach, in which government spending is considered to determine economic growth. However, there is another theory, which suggests that economic growth in fact determines government spending. This is Wagner’s hypothesis. The purpose of this paper is to investigate which of the two approaches applies to South Africa, and further observes the level of non-linearity between the two variables. Design/methodology/approach This study was carried out using quarterly time series data from 1980Q1 to 2015Q1. Granger causality technique was used to observe the direction of causality between the two variables, while regression error specification test (RESET) was employed to determine whether the variables exhibit linear or non-linear behaviour. This was followed by observing the threshold band, using two techniques, namely, sample splitting threshold regression and quadratic generalised method of moments. Findings The causality result shows that South Africa follows Wagner’s law, whereby government spending is determined by economic growth, supporting Odhiambo (2015). The RESET result shows that the variables depict a non-linear relationship, thus the government spending economic growth model is non-linear. It was found that if positive economic development is to be achieved, economic growth should preferably be kept within the −1.69 and 3.0 per cent band, and specifically above 1 per cent band. Originality/value The unique contribution of this study is that no previous study has attempted the non-linear government spending-economic growth nexus whether within the Keynesian or Wagner law for South Africa.

Measuring electric energy efficiency in Portuguese households

2015 ◽  
Vol 26 (3) ◽  
pp. 407-422 ◽  
Author(s):  
Thomas Weyman-Jones ◽  
Júlia Mendonça Boucinha ◽  
Catarina Feteira Inácio
Keyword(s):  
Time Series ◽  
Energy Efficiency ◽  
Energy Demand ◽  
Energy Use ◽  
Time Series Data ◽  
Electric Energy ◽  
Electrical Energy ◽  
Series Data ◽  
Data Set ◽  
Content Type

Purpose – There is a great interest from the European Union in measuring the efficiency of energy use in households, and this is an area where EDP has done research in both data collection and methodology. This paper reports on a survey of electric energy use in Portuguese households, and reviews and extends the analysis of how efficiently households use electrical energy. The purpose of this paper is to evaluate household electrical energy efficiency in different regions using econometric analysis of the survey data. In addition, the same methodology was applied to a time-series data set, to evaluate recent developments in energy efficiency. Design/methodology/approach – The paper describes the application to Portuguese households of a new approach to evaluate energy efficiency, developed by Filippini and Hunt (2011, 2012) in which an econometric energy demand model was estimated to control for exogenous variables determining energy demand. The variation in energy efficiency over time and space could then be estimated by applying econometric efficiency analysis to determine the variation in energy efficiency. Findings – The results obtained allowed the identification of priority regions and consumer bands to reduce inefficiency in electricity consumption. The time-series data set shows that the expected electricity savings from the efficiency measures recently introduced by official authorities were fully realized. Research limitations/implications – This approach gives some guidance on how to introduce electricity saving measures in a more cost effective way. Originality/value – This paper outlines a new procedure for developing useful tools for modelling energy efficiency.

scholarly journals Negative equity in Ireland: estimates using loan-level data

2014 ◽  
Vol 7 (3) ◽  
pp. 327-344 ◽  
Author(s):  
David Duffy ◽  
Niall O’Hanlon
Keyword(s):  
Design Methodology ◽  
Time Series Data ◽  
House Prices ◽  
Age Groups ◽  
Series Data ◽  
Data Set ◽  
Content Type ◽  
Equity Analysis ◽  
Level Data ◽  
Younger Age

Purpose – This paper aims to, using a unique loan-level data set, show the extent to which negative equity in Ireland is concentrated in younger age groups. The sharp decline in house prices since 2007 has led to the emergence of widespread negative equity in Ireland. However, little is known about the type of borrower experiencing negative equity. Design/methodology/approach – This paper uses a unique data set that, for a large sample of mortgages, provides details on both the characteristics of the borrowers and their mortgages. Using this data set, the paper estimates the incidence of negative equity by analysing loans taken out to purchase a primary residence in the period 2005-2012. Findings – The analysis finds the situation in Ireland to be much more severe than that being experienced in other housing market downturns at present, with 64 per cent of borrowers in the period 2005-2012 experiencing negative equity. Analysis by age gives rise to concern, with the majority of those in negative equity aged under 40 years. The paper also points to the large wealth loss experienced by Irish households, in the order of 43 billion, as a result of the fall in property values. Originality/value – The paper is one of the first using loan-level time-series data in Ireland. It highlights the growth in negative equity during the crisis and the extent to which it is concentrated in the younger age groups. It also provides an estimate of the loss in wealth suffered by all households due to the fall in Irish house prices.

Insurance market development and economic growth

2016 ◽  
Vol 43 (3) ◽  
pp. 321-339 ◽  
Author(s):  
Abdul Latif Alhassan
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Causal Relationship ◽  
Time Series Data ◽  
Insurance Market ◽  
Market Development ◽  
Series Data ◽  
African Countries ◽  
Content Type ◽  
Bound Test

Purpose – The purpose of this paper is to examine the causal relationship between insurance penetration and economic growth in eight selected African countries. Design/methodology/approach – The auto-regressive distributed lags bounds approach to cointegration is employed on annual time-series data from 1990 to 2010 to test the causal relationship between insurance and economic growth in Algeria, Gabon, Kenya, Madagascar, Mauritius, Morocco, Nigeria and South Africa. The ratio of life and non-life insurance premiums to gross domestic product are employed as proxies for insurance market development. Findings – The results of the bound test shows a long-run relationship between insurance market activities and economic growth for Kenya, Mauritius, Morocco, Nigeria and South Africa. Causality analysis within the vector error correction model indicates a uni-directional causality from insurance market development to economic growth except for Morocco where there is evidence of a bi-directional causality. Causality within the vector autoregressive framework also provides evidence of a uni-directional causality for Algeria and Madagascar to support the “supply-leading” hypothesis while mixed causality was found for Gabon. Practical implications – This findings provides policy direction for governments and regulatory authorities for developing insurance market in the sample countries. Originality/value – This is the first study to examine the finance-growth relationship from the perspective of insurance markets in a cross-section of African countries.

A novel study on OFDI and home country exports: implications for the ASEAN region

2016 ◽  
Vol 9 (2) ◽  
pp. 131-145 ◽  
Author(s):  
Fayyaz Ahmad ◽  
Muhammad Umar Draz ◽  
Su-Chang Yang
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
Time Series Data ◽  
Home Country ◽  
Series Data ◽  
Substitution Effects ◽  
Correlation Technique ◽  
Data Set ◽  
Content Type ◽  
Asean Countries

Purpose This study aims to examine the effects of outward foreign direct investment (OFDI) on the home country exports for selected ASEAN countries during 1981-2013. Design/methodology/approach The authors have used OLS regression based on the unit root analysis, correlation technique and a series of specification tests applied to annual time series data. Findings The results reveal that the complementary effects of OFDI on exports of the home country outweigh the substitution effects for four ASEAN countries. Furthermore, trade openness, currency fluctuations and inward foreign direct investment (FDI) are also important factors for progressive home country exports. Originality/value This study provides a thorough analysis of the links between OFDI and exports of the home country on a macro level. With a data set of more than three decades from the ASEAN region, this study is the first attempt of its kind to analyze the relationship of these two variables on the aggregate level.

scholarly journals Food security and trade policies: evidence from the milk sector case study

2021 ◽  
Vol 123 (13) ◽  
pp. 59-72
Author(s):  
Maria Bruna Zolin ◽  
Danilo Cavapozzi ◽  
Martina Mazzarolo
Keyword(s):  
Food Security ◽  
Empirical Evidence ◽  
Rural Areas ◽  
Time Series Data ◽  
Income Elasticity ◽  
Series Data ◽  
National Bureau ◽  
Content Type ◽  
Trade Opening ◽  
Urban And Rural Areas

PurposeMilk is one of the most produced, consumed and protected agricultural commodities worldwide. The purpose of this paper is to assess how trade-opening policies can foster food security in the Chinese milk sector.Design/methodology/approachThe empirical evidence proposed in our paper is based on time series data from the National Bureau of Statistics of China (2019) and FAOSTAT (2020). Differences in income elasticity between urban and rural areas are estimated by OLS regressions. The data also provide empirical evidence to assess to what extent and to which countries China is resorting to meet its growing demand.FindingsPer-capita milk consumption of Chinese is rising. The authors’ estimates show that milk income elasticity is higher in rural areas. China is also progressively increasing its dependence on imports. Producers who benefit the most are those from countries implementing trade-opening policies.Research limitations/implicationsOther methods could be applied, by way of example, the gravitational model.Practical implicationsTrade agreements and the removal of barriers could be effective responses to protectionist pressures and to food security concerns.Social implicationsThe case examined is of particular interest as it intervenes on food security and safety.Originality/valueThe paper adds value and evidence to the effects of trade on food security in a country with limited and exploited natural resources addressing a health emergency and environmental concerns.

Does immiserizing growth exist? Evidence from world’s top trading nations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Syed Tehseen Jawaid ◽  
Mariya Ahmad Qureshi ◽  
Samra Ali
Keyword(s):  
Logistic Regression ◽  
Time Series Data ◽  
Real Data ◽  
Terms Of Trade ◽  
Series Data ◽  
Revealed Preferences ◽  
Data Set ◽  
Content Type ◽  
Quantity Index ◽  
The Impact

Purpose This study aims to motivate the reality that experiential investigation of immiserizing growth has not been performed at large. The key objective of the study is to analyse the empirical existence of immiserizing growth in the real world. Design/methodology/approach Theory of revealed preferences has been implemented for welfare movement by using Laspeyres and Paasche quantity index and for empirical estimations, logistic regression has been applied. The study established panel data of the world’s largest trading nations, including the USA, China, France, Germany, UK, Italy, Japan, the Netherland and Canada. Annual time series data for an extensive time period covering from 1981 till 2017 have been used. Findings Findings of the Laspeyres and Paasche index reveal that out of nine countries immiserizing growth prevails in five nations and those are Italy, Canada, the Netherland, UK and Japan. The results of panel logistic regression verify the significance of terms of trade on immiserizing growth in all included countries. Separate logistic regression has also been performed on all the five countries from which Italy, Canada, the Netherland exhibit significant results. Originality/value This study is a pioneer attempt towards the concept of immiserizing growth. Considering the fact that immiserizing growth is viewed by the majority of the scholars as a theoretical notion, this study attempts to investigate analytically the existence of immiserizing growth with real data set. The impact of terms of trade deterioration on the welfare of the world’s largest trading nations has been focused on the research which is in compliance with the concept of Bhagwati (1958).

scholarly journals Pre-COVID-19 evaluation of external debt, corruption and economic growth in South Africa

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ebenezer Gbenga Olamide ◽  
Andrew Maredza
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Time Series ◽  
Time Series Data ◽  
External Debt ◽  
Public Institutions ◽  
Series Data ◽  
Content Type ◽  
Long Run ◽  
Short Run

PurposeThis study is a pre-COVID-19 exposition of the existing situation about external debt-GDP relationship, incorporating corruption into the hypothesis, making South Africa the object of the study. The aim is to examine the causal relationship between corruption, economic growth and external debt, and in the end proffer solutions to the problems arising therefrom.Design/methodology/approachThe study employed ARDL technique on time series data running from 1990 to 2019 with real gross domestic product as the dependent variable and external debt, external debt servicing, corruption, inflation and capital formation as regressors. Necessary tests that include unit root, cointegration, CUSUM and CUSUMSq, normality, serial correlation and heteroscedasticity were performed on the model.FindingsThe study shows that corruption, inflation and external debt servicing exert negative influences on economic growth while the effect of investment on growth was positive. External debt's effect in the short run was positive while its long-run effect on growth was negative. Among other things, the need to improve and strengthen public institutions in addition to targeting tax evaders and avoiders for increased government revenue were emphasized.Originality/valueThe study incorporates corruption into the country specific debt-GDP debate as against earlier studies that excluded corruption in their time series analysis or that were cross-country based. The authors also exposit the existing knowledge of the debt-GDP hypothesis before the outbreak of COVID 19 pandemic. This is expected to serve as a precursor to subsequent studies on the rising debt of South Africa during and after the pandemic.

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