COVID-19 and Hotel Productivity Changes: An Empirical Analysis Using Malmquist Productivity Index

2021 ◽  
Author(s):  
Changhee Kim ◽  
Hee Jay Kang ◽  
Kyunghwa Chung ◽  
Kanghwa Choi
Keyword(s):  
Empirical Evidence ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Organizational Level ◽  
Productivity Change ◽  
Efficiency Change ◽  
Technological Advances ◽  
Productivity Management ◽  
Pay Cuts ◽  
The Impact

This research investigates the impact of COVID-19 on hotel productivity change using the Malmquist Productivity Index (MPI). For 26 U.S. hotel brands, productivity changes over 10 quarters from the first quarter of 2018 to the second quarter of 2020 were analyzed. After the COVID-19 outbreak, the investigated hotels’ productivity deteriorated. Decomposition revealed that, whereas technical efficiency change (EC) improved, technological change (TC) regressed, resulting in deterioration of the MPI. The investigated hotels’ EC-related practices included enhanced cleaning operations, partnering with a hygiene brand, cutting the workforce, and pay cuts. Practices related to TC included the adoption of new hygiene technology and setting a new standard at the organizational level through the formation of a global council and accreditation related to disinfection and hygiene. Our results show that though U.S. hotels are trying to improve their productivity by efficiently utilizing resources, frontier technology’s regress is decreasing productivity. Our results support the importance of investment in technology for productivity management. This research provides empirical evidence for the need for hotels to pursue technological advances to overcome the pandemic.

scholarly journals Evaluating the Performance of Agricultural Bank Management: The Impact of State Regulatory Policies

1999 ◽  
Vol 31 (3) ◽  
pp. 437-448 ◽  
Author(s):  
Bernard K.N. Armah ◽  
Timothy A. Park ◽  
C.A. Knox Lovell
Keyword(s):  
Technological Change ◽  
Scale Economies ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Efficiency Change ◽  
Regulatory Policies ◽  
Bank Management ◽  
Interstate Banking ◽  
The Impact

AbstractWe evaluate agricultural bank management performance, focusing on the impacts of interstate banking laws on productivity change. The generalized Malmquist productivity index decomposes productivity change into technological change, technical efficiency change, and change in scale economies. While managerial productivity rose from 1982 to 1991, states that adopted the most liberal interstate banking laws experienced the greatest improvement in productivity. Large agricultural banks were more efficient in states that had more liberalized interstate banking laws while small agricultural banks fared better in states with more restrictive laws.

scholarly journals MEASURING EFFICIENCY CHANGE IN TIME APPLYING MALMQUIST PRODUCTIVITY INDEX: A CASE OF DISTRIBUTION CENTRES IN SERBIA

2021 ◽  
Vol 19 (3) ◽  
pp. 499
Author(s):  
Milan Andrejić ◽  
Milorad Kilibarda ◽  
Vukašin Pajić
Keyword(s):  
Decision Making ◽  
Environmental Changes ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Decision Making Process ◽  
Distribution Centers ◽  
Efficiency Change ◽  
Selection Of Variables ◽  
Measuring Efficiency ◽  
The Impact

In the last decade, more and more attention has been paid to the efficiency of logistics systems not only in the literature but also in practice. The reason is the huge savings that can be achieved. In a very dynamic market with environmental changes distribution centers have to realize their activities and processes in an efficient way. Distribution centers connect producers with other participants in the supply chain, including end-users. The main objective of this paper is to develop a DEA model for measuring distribution centers’ efficiency change in time. The paper investigates the impact of input and output variables selection on the resulting efficiency in the context of measuring the change in efficiency over time. The selection of variables on the one hand is a basic step in applying the DEA method. On the other hand, the number of basic and derived indicators that are monitored in real systems is increasing, while the percentage of those used in the decision-making process is decreasing (less than 20%). The developed model was tested on the example of a retail chain operating in Serbia. The main factors changing the efficiency have been identified, as well as the corresponding corrective actions. For measuring efficiency change in time Malmquist productivity index is used. The developed approach could help managers in the decision-making process and also represents a good basis for further research.

scholarly journals Productivity of Estonian dairy farms decline after the accession to the European Union

2011 ◽  
Vol 57 (No. 9) ◽  
pp. 457-463 ◽  
Author(s):  
N. Vasiliev ◽  
E. Suuster ◽  
H. Luik ◽  
R. Värnik ◽  
E. Matveev ◽  
...  
Keyword(s):  
European Union ◽  
Dairy Farms ◽  
Efficiency Score ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Annual Growth Rate ◽  
The European Union ◽  
Efficiency Change ◽  
Significant Deterioration

The aim of the study was to analyze the productivity change of Estonian dairy farms before and after the accession to the European Union. The Malmquist productivity index was measured and separated into the technical and efficiency change using the data envelopment analysis for the pre-accession period (years 2001–2003) and the post-accession period (2004–2006). Second-stage regression was applied to estimate the possible variables determining the productivity and efficiency change. Productivity growth of Estonian dairy farms was negative for both observed periods; the mean annual growth rate of the Malmquist productivity index was –0.7% in 2001–2003 and –2.6% in 2004–2006. The share of farms with declining productivity increased from 36% to 50% after the accession to the EU and is induced mainly by a significant deterioration in the efficiency change. Remarkable changes in the line-up of most efficient dairy farms occurred between 2000 and 2006, producers with greater initial efficiency have experienced significant regress, with efficiency score decreasing from 0.842 in 2000 to 0.608 in 2006 and the new front-runners, forming the efficiency frontier, have emerged. Capitalization was positively related with the cumulative technical change. Nevertheless, increasing investments and assets have not affected efficiency change and investments have often not been harnessed in the best possible way.  

scholarly journals The Impact of International Trade on Central Bank Efficiency: An Application of DEA and Tobit Regression Analysis

2021 ◽  
Vol 9 (1) ◽  
pp. 223-240
Author(s):  
Qaiser Farooq Dar ◽  
Young-Hyo Ahn ◽  
Gulbadin Farooq Dar
Keyword(s):  
Regression Analysis ◽  
International Trade ◽  
Central Bank ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Tobit Regression ◽  
Bank Efficiency ◽  
Tobit Regression Analysis ◽  
The Impact

The purpose of this study is to introduce a novel methodology to measure the central bank efficiency. The data envelopment analysis (DEA) applies in the combination of three input and two output variables characterizing the economic balance in international trade.  Super-efficiency DEA model is applied for ranking & comparing the efficiency of different central banks. In contrast, the Malmquist productivity index (MPI) is used to measure the productivity change over the period of time. Further, the study is extended to quantify the impact of international trade dimension on the efficiency of the central bank by using Tobit regression analysis. Finally, based on our data analysis, we reported that the efficiency changes over the period of time and the total productivity changes significantly due to the technology shift as compared to efficiency change. Additionally, it is also observed that the central bank efficiency is impacted dramatically by the export level of the country as compared to import level, average exchange rate and GDP. It implies that the export level of the country significantly influences the performances of the central bank.

Productivity Analysis of Coal-fired Thermal Power Plants in India Using Malmquist Index Approach

2019 ◽  
Vol 21 (6) ◽  
pp. 1338-1353
Author(s):  
Amritpal Singh Dhillon ◽  
Hardik Vachharajani
Keyword(s):  
Total Factor Productivity ◽  
Power Plants ◽  
Thermal Power ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Tfp Growth

The sustainable socio-economic growth of any country depends on the availability of adequate and reliable power at reasonable rates. This is even true in case of a rapidly developing country like India where coal-based power plants account for the majority of electricity generation. Making use of data envelopment analysis (DEA) and Malmquist productivity index (MPI), this study analyses the productivity change of coal-fired power plants during 2002–2012. Productivity change is further decomposed into technical efficiency change (EFFCH), technological change (TECHCH), scale efficiency change (SECH), pure technical change (PECH) and total factor productivity change (TFPCH). The study revealed that 0.70 per cent of average annual total factor productivity (TFP) growth was witnessed from 2002–2003 to 2011–2012 indicating overall progress. The contribution of TECHCH in TFP growth is positive, that is, 1.3 per cent per annum. It demonstrates that expansion of the efficient frontier. However, there was a decrease in technical EFFCH of −0.6 per cent per year, indicating the adverse sign of progress. Plants in the central sector achieved maximum growth of 4.6 per cent annually. A total of 54.05 per cent of plants have recorded negative TFP growth. Power plants between 500 and 999 MW achieved the highest operational performances in all indices except SECH.

Health system productivity in China: a comparison of pre- and post-2009 healthcare reform

2019 ◽  
Vol 35 (3) ◽  
pp. 257-266
Author(s):  
Peipei Chai ◽  
Yuhui Zhang ◽  
Maigeng Zhou ◽  
Shiwei Liu ◽  
Yohannes Kinfu
Keyword(s):  
Health System ◽  
Capital Investment ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
System Productivity ◽  
Life Years ◽  
Hospital Beds ◽  
The Impact

Abstract In 2009, China launched an ambitious health system reform that combined extending social health insurance scheme with improving efficiency, access and quality of care in the country. To assess the impact of the policy on efficiency and productivity change, we investigated the country’s health system performance at provincial levels during pre- and post-reform period. Outputs were measured using multiple health outcomes (namely, non-communicable diseases free healthy life years and infant and maternal survival rates), while health expenditure, number of medical personnel and hospital beds per 1000 residents were used as proxy measures for health inputs. Changes in productivity were quantified using a bootstrap Malmquist productivity index (MPI). The analysis focused on the period between 2004 and 2015. This was to capture pre- and post-policy implementation experience and to ensure that enough time was allowed for the policy to work through. Finally, a bootstrap Tobit regression model for panel data was applied to examine the potential effects of contextual factors on productivity change. The result showed that the reform has had negative effects on productivity. Only scale efficiency had improved steadily, but the decline in the scale of technological change observed during the same period meant that the progress in scale efficiency had been masked. Better economic performance (as measured by per capita Gross Domestic Product (GDP)) and higher human resource to capital investment ratio (as measured by density of medical staff per hospital beds) tended to boost productivity growth, while population aging, low educational attainment and higher percentage of out-of-pocket (OOP) payments had adverse effects. Improving health system productivity in China requires improving financial risk protection and maintaining proper balance between human and capital investment in the country.

scholarly journals EFFICIENCY AND PRODUCTIVITY CHANGE ACROSS THE ECONOMIC SECTORS IN LITHUANIA (2000–2010): THE DEA–MULTIMOORA APPROACH

2014 ◽  
Vol 19 (Supplement_1) ◽  
pp. S191-S213 ◽  
Author(s):  
Tomas Baležentis ◽  
Algimantas Misiūnas ◽  
Alvydas Baležentis
Keyword(s):  
Value Added ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Economic Sectors ◽  
Services Sector ◽  
Intermediate Consumption ◽  
The Impact ◽  
Efficiency And Productivity

Reasonable strategic management requires the complex assessment of the regulated area. This study, thus, presents a multi-criteria framework for frontier assessment of efficiency and productivity across the Lithuanian economic sectors throughout 2000–2010. The data envelopment analysis was employed to estimate efficiency in terms of an output indicator (value added) and input indicators (intermediate consumption, capital consumption, and remunerations). Furthermore, the decomposition of the Malmquist productivity index enabled to describe the impact of frontier shifts and catch-up effect on the overall change in efficiency. The multi-criteria decision making method MULTIMOORA aggregated different indicators of efficiency and productivity and thus resulted in the ranking of the economic sectors. The analysis suggests that services sector was the most efficient one, whereas manufacturing was second best. Certain branches of manufacturing, namely pharmaceutical, wood, food, and furniture industry, were rather efficient.

scholarly journals ANALISIS TINGKAT EFISIENSI SEKTOR PARIWISATA DI JAWA TENGAH TAHUN 2017 DAN 2019

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Yennie Glorya Panjaitan ◽  
Edy Yusuf Agung Gunanto
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change

Sektor pariwisata sebagai salah satu sektor yang diandalkan bagi penerimaan daerah maka pemerintah Provinsi Jawa Tengah dituntut untuk dapat menggali dan mengelola potensi wisata yang dimiliki. Penelitian ini bertujuan untuk menganilisis tingkat efisiensi dan produktivitas pada sektor pariwisata di Jawa Tengah antara tahun 2017 dan 2019 dengan sampel 35 Kabupaten/Kota. Analisis dilakukan dengan menggunakan konsep efisiensi yang didasarkan pada teori produksi, pengukuran nilai efisiensi dan produktivitas diperoleh menggunakan metode analisis Data Envelopment Analysis (DEA) dan Malmquist Productivity Index (MPI). Asumsi yang digunakan adalah variable return to scale (VRTS) dan model orientasi output (output oriented). Dengan variable input objek wisata, restoran dan rumah makan, biro perjalanan wisata dan jumlah hotel bintang serta melati. Variabel output dalam penelitian ini adalah wisatawan dan pendapatan sektor pariwisata. Hasil akhir penelitian menunjukkan bahwa terdapat 16 Kabupaten/Kota (45,8%) di tahun 2017, 18 Kabupaten/Kota (51,4%) di tahun 2019 yang mencapai efisiensi teknis penuh. Total Factor productivity change mengindikasikan bahwa 22 Kabupaten/Kota (62,8%) mendekati frontier baik pada frontier produksi maupun frontier efisiensi dan dari scale efficiency change mengindikasikan bahwa terdapat 17 Kabupaten/Kota (48,57%) mengalami perbaikan efisiensi teknis selama periode 2017 ke 2019.

scholarly journals Measurement of Total Factor Productivity in Commercial Airlines Sector using Malmquist Index and Data Envelopment Model

2020 ◽  
Vol 8 (6) ◽  
pp. 2168-2173
Keyword(s):  
Panel Data ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Year 2013

This study attempts to measure productivity change of Airlines companies in private and public sector in India for a period of four years (2011-2016). In this study the nature and productivity change is probed using the Malmquist Productivity Index. This index has the constituents which are used to measure the performance in terms of change in Scale Efficiency, change in Technical Efficiency, change in Technological Change and Total Factor Productivity. The paper compares efficiencies for the companies in public and private commercial airlines sector in India. Five Airlines companies are included in the study. The research includes Total Annual Income as an output variable and Total Expenditure, Employee Compensation, Sales & Distribution Expenditure and Marketing expenses as Input variables. A panel data with 30 observations has been used for analysis. The panel data is used to arrive to MPI estimates, with a total of five commercial airlines companies in India. The Total Factor Productivity change in the airlines sector depends upon the change in the efficiency and productivity of the companies. From the study it is evident that the Total Factor Productivity change has not changed significantly over the last six years for all the companies under study. The Technical Efficiency was the highest in the year 2013-14 which then dropped in the subsequent year. The Total Factor Productivity change is mainly due to change in scale efficiency of the companies since the pure efficiency has shown no significant change during the period under study. The Total Factor Efficiency dropped by almost 50% in the case of Air India in the year 2015-16. This drop is attributed to the deterioration in the technical efficiency of the company. The overall Total Factor Productivity of Air India is the highest. This can be attributed to positive change in the company’s Technical Efficiency especially in the year 2013-14. It is evident that all the airlines companies under study have not emphasized on improving scale efficiency as well as pure efficiency. These companies can improve their overall productivity by bringing in efficiency in the scale of operations as well as focus on improving efficiency on factors other than scale of operations. The commercial airlines companies in India need to improve their scale efficiency and pure efficiency to improve their total factor productivity.

Postcrisis REIT performance using financial ratios: A DEA approach

2020 ◽  
pp. 135481662096266
Author(s):  
Apostolos Ampountolas
Keyword(s):  
Financial Ratios ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Moderate Degree ◽  
Efficiency Change ◽  
Real Estate Investment ◽  
Operational Strategies ◽  
Performance Determinants

This study examines the performance of public lodging real estate investment trusts (REITs) following the financial crisis period from 2013 to 2017. We employed data envelopment analysis, a nonparametric technique based on linear programming, to measure performance. Determinants of efficiency were assessed by a set of financial ratios predicting each REIT’s efficiency against its peers. Consequently, a Malmquist productivity index (MPI) evaluated the efficiency change in several periods. The empirical results revealed that the REITs generally performed well despite the moderate degree of volatility in the financial ratios. Results showed a wide variation in performance consistency, with a limited number of REITs—that is, 5 out of 20—consistently performing well during the study period. Additionally, the MPI indicated a decline in efficiency, while the productivity change showed a mixture of reflections. The decomposition components of the productivity index and efficiency changes are also provided. This study sheds light on understanding inefficient REITs and provides some guidance on the critical indicators that would help such REITs restructure their operational strategies to improve efficiency.

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