Development of Competitive–Cooperative Relationships among Mediterranean Cruise Ports since 2000

Cruise shipping has been extremely popular in recent years, and one of the fastest-growing areas has been the Mediterranean. In the paper, we examine the evaluation of possible competitive–cooperative relationships among Mediterranean cruise ports for the period 2000–2017. To this end, we use three models: the dynamic shift-share model, the Lotka–Volterra model (LVM), and the logistic model (LM). The evaluation of basic market indices is included for completeness. The analysis shows that cruise traffic is in a saturation phase. The shift-share and LVM models reveal that interaction among ports is not significant for the large ports, but could be essential for the small ones.

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Weighted spatial dynamic shift‐share model as a forecasting tool for a regional economy: The case of South Korea

Growth and Change ◽

10.1111/grow.12377 ◽

2020 ◽

Vol 51 (2) ◽

pp. 734-748

Author(s):

Hyun‐kyung Lee ◽

Hong‐bae Kim

Keyword(s):

South Korea ◽

Regional Economy ◽

Spatial Dynamic ◽

Share Model ◽

Dynamic Shift

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Shift-Share Analysis in Tourism: Examination of Tourism Employment Change in a Region

Tourism Economics ◽

10.5367/000000002101298142 ◽

2002 ◽

Vol 8 (3) ◽

pp. 303-324 ◽

Cited By ~ 19

Author(s):

Ercan Sirakaya ◽

Hwan-Suk Choi ◽

Turgut Var

Keyword(s):

Time Series ◽

Tourism Industry ◽

Static Method ◽

Theoretical Problem ◽

Employment Change ◽

Share Model ◽

The Us ◽

The Usa ◽

Employment Data ◽

Dynamic Shift

The purpose of this paper is to present and demonstrate the usefulness of the dynamic shift-share method in examining the performance of the tourism industry using time-series employment data for the State of Texas and the USA, and to compare its results with those of the traditional accounting based shift-share analysis. The findings show that, compared to the US average, the change in employment in Texas was mainly due to the strong national economy and not to the region's competitiveness or sectoral make-up. According to the findings, the use of a dynamic shift-share model eliminated one theoretical problem inherent in the classical static method.

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Investigating the development and interaction of bus-metro based on Lotka–Volterra models: Evidence from seven central cities in China

Modern Physics Letters B ◽

10.1142/s0217984921502079 ◽

2021 ◽

pp. 2150207

Author(s):

Xinyu Liang ◽

Xianghai Meng

Keyword(s):

Public Transport ◽

Logistic Model ◽

Volterra Model ◽

Volume Data ◽

Central Cities ◽

Guangzhou City ◽

Nanjing City ◽

Passenger Volume ◽

Shanghai City ◽

Transport Modes

Bus and metro are the two most important public transport modes in many metropolises in China, and they both have experienced rapid growth and meanwhile coexisted for decades. However, little is known on how the metro and bus interacted with each other during their rapid growths. This study was proposed to investigate the growth and interaction of bus-metro from the macro perspective. The passenger volume data for metro and bus were collected from seven central cities to represent the development of the two public transport modes, and the Logistic model and Lotka–Volterra model were employed to model the growth as well as the interaction of bus-metro, respectively. The modeling results show that the development of bus conforms to the Logistic model (i.e. S-shaped curve), while the bus-metro interaction conforms to the Lotka–Volterra model with interaction modes of competition (Shanghai city from 2000–2009, Shanghai city from 2009–2018, Guangzhou city from 2009–2017, Nanjing city from 2008–2018), and mutualism (Guangzhou city from 2000–2009). The further analysis indicates that urban characteristics and policies determine the interaction, and the parameters of the Lotka–Volterra model could be used to judge the bus-metro interaction type.

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The Port Service Ecosystem Research Based on the Lotka-Volterra Model

Polish Maritime Research ◽

10.1515/pomr-2017-0109 ◽

2017 ◽

Vol 24 (s3) ◽

pp. 86-94 ◽

Cited By ~ 2

Author(s):

Wenjuan Li ◽

Wei Liu ◽

Xu Xu ◽

Zhijun Gao

Keyword(s):

Logistic Model ◽

Volterra Model ◽

Mutual Benefit ◽

Ecosystem Research ◽

Industry Chain ◽

Competition Coefficient ◽

The Core Competence ◽

Service Ecosystem ◽

Matlab Programming ◽

China’S Economy

Abstract Under the new normal of China’s economy, the competition among the port enterprises is not only the competition of the core competence of the port, the port industry chain or the port supply chain, but also the competition of the port service ecosystem. In this paper, the concept and characteristics of the port service ecosystem is discussed, a hierarchical model of the port service ecosystem is constructed. As an extended logistic model, Lotka-Volterra model is applied to study the competitive co-evolution and mutually beneficial co-evolution of enterprises in the port service ecosystem. This paper simulates the co-evolution of enterprises in the port service ecosystem by using MATLAB programming. The simulation results show that the breadth of the niche of the enterprises is changing with the change of the competition coefficient and the coefficient of mutual benefit in the port service ecosystem. Based on that, some proposals are put forward to ensure the healthy and orderly development of the port service ecosystem.

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Parameter Estimation of Lotka-Volterra Model : A Two-Step Model

Jurnal Teknologi ◽

10.11113/jt.v63.1907 ◽

2013 ◽

Vol 63 (2) ◽

Author(s):

Haliza Abd. Rahman ◽

Arifah Bahar ◽

Norhayati Rosli

Keyword(s):

Parameter Estimation ◽

Power Law ◽

Logistic Model ◽

Structural Parameters ◽

Volterra Model ◽

Second Step ◽

Regression Spline ◽

Step Model ◽

Nonparametric Criterion ◽

The Bayesian Approach

The deterministic power law logistic model is used to describe density-dependent population growth for cases when ordinary logistic model is found to be insufficient. This paper estimates the parameters of stochastic power law logistic model specifically the Lotka-Volterra model by employing the two-step approach. The Bayesian approach is implemented in the first step of estimating the regression spline parameters. Combining the existing and proposed nonparametric criterion, the structural parameters of SDE are estimated in the second step. Results indicate high percentage of accuracy of the estimated diffusion parameter of Lotka-Volterra model supporting the adequacy of the proposed criterion as an alternative to the classical methods.

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Forecasting and Analyzing Internet Users of China with Lotka–Volterra Model

Asia Pacific Journal of Operational Research ◽

10.1142/s0217595917400061 ◽

2017 ◽

Vol 34 (01) ◽

pp. 1740006 ◽

Cited By ~ 3

Author(s):

Xiaoxia Fu ◽

Ping Zhang ◽

Juzhi Zhang

Keyword(s):

Prediction Accuracy ◽

Logistic Model ◽

Gompertz Model ◽

Absolute Error ◽

Volterra Model ◽

Percentage Error ◽

The Internet ◽

Internet Users ◽

The Mean ◽

The Relationship

In the background of big data era, the ability to accurately forecast the number of the Internet users has considerable implications for evaluating the growing trend of a newly-developed business. In this paper, we use four models, the Gompertz model, the Logistic model, the Bass model, and the Lotka–Volterra model, to forecast the Internet population in China with the historical data during 2007 to 2014. We compare the prediction accuracy of the four models using the criterions such as the mean absolute percentage error (MAPE), the mean absolute error (MAE) and the root mean square error (RMSE). We find that the Lotka–Volterra model has the highest prediction accuracy. Moreover, we use the Lotka–Volterra model to investigate the relationship between the rural Internet users and the urban Internet users in China. The estimation results show that the relationship is commensalism.

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