scholarly journals Spatial-Temporal Pattern and Its Influencing Factors on Urban Tourism Competitiveness in City Agglomerations Across the Guanzhong Plain

2019 ◽  
Vol 11 (23) ◽  
pp. 6743
Author(s):  
Jia Wan ◽  
Junping Yan ◽  
Xiaomeng Wang ◽  
Ziqiang Liu ◽  
Hui Wang ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Influencing Factors ◽  
Temporal Pattern ◽  
Explanatory Power ◽  
Urban Tourism ◽  
Ecological Environment ◽  
Single Factor ◽  
Tourism Resources ◽  
High Level ◽  
Environment Condition

Strengthening research on urban tourism competitiveness is vital in evaluating the current situation and potential of urban tourism, maintaining the sustainable development of the tourism economy and assisting in the regional macro decision making. In this study, an index system evaluation of urban tourism competitiveness in city agglomerations across the Guanzhong Plain is established by collecting cross-section data from the years 2017 and 2010. The entropy value method is adopted to determine the index weight. Cluster analysis is performed and the spatial-temporal pattern and evolution laws of urban tourism competitiveness among city agglomerations in the Guanzhong Plain are analyzed and the geographic detector utilized to discuss the influencing factors. Results show that the spatial gradient difference of urban tourism competitiveness of agglomerations in the Guanzhong Plain is significant. In 2010, it presented the characteristic of ‘the high and middle levels having a zonal distribution from east to west, and the low level was distributed along the north and south wings’. In 2017, the characteristic of ‘polarization’ became highly prominent, that is, the scope of high-level and low-level cities expanded and the scope of medium-level cities decreased. Urban tourism competitiveness in city agglomerations across the Guanzhong Plain exhibited a trend of ‘strengthening in the east, weakening in the west’. The competitiveness of resources and management shifted aggressively and supporting factors competitiveness underwent a slight change. The urban tourism competitiveness of city agglomerations in the Guanzhong Plain is generally low, while the urban tourism competitiveness of Xi’an had an absolute advantage in city agglomerations of the Guanzhong Plain. According to the cluster analysis results, resources and management competitiveness, supporting factors competitiveness, demand conditions competitiveness, situational conditions competitiveness and urban tourism competitiveness of Xi’an in 2010 and 2017 were all at an extremely high level, which was relatively higher than the index values of other cities in the city agglomerations of the Guanzhong Plain. Tourism resources, service support capacity, infrastructure support capacity, tourism income scale, tourism reception scale and economic development power are the core influencing factors of urban tourism competitiveness among city agglomerations in the Guanzhong Plain. The single factor explanatory power of destination management indicates a downward trend while the single factor explanatory power of the ecological environment condition shows an upward trend. Tourism resources are the leading interactive factor of urban tourism competitiveness, and destination management and ecological environment condition are the most significant indicators for the collaborative effect.

scholarly journals Modeling and Empirical Analysis of Regional Tourism Competitiveness Based on Niche Theory

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yingjuan Yang ◽  
Yanxia Wu ◽  
Haiqing Hu
Keyword(s):  
Cluster Analysis ◽  
Empirical Analysis ◽  
Evaluation System ◽  
Niche Overlap ◽  
Entropy Method ◽  
Urban Tourism ◽  
Shaanxi Province ◽  
Niche Theory ◽  
Regional Tourism ◽  
Tourism Resources

The fierce competition in tourism has brought a string of problems, such as the homogeneous development of regional tourism resources and the escalation of regional competition. One key issue in urban tourism today is how to identify competitors, recognize own advantageous resources, and clarify the direction of development. This paper evaluates the competitiveness of regional tourism in three steps: setting up an evaluation system, calculating niche and niche overlap, and conducting synthesis and cluster analysis. Firstly, a comprehensive evaluation system of urban tourism niche was established, which includes such four dimensions as tourism resources, tourism market, social economy, and eco-environment, and the weight of each index was calculated by entropy method. Next, regional niche and niche overlap were computed by niche theory. Taking the mean of niche overlap and that of composite niche as the references, the authors drew an overall distribution map of regional tourism niche. After that, a cluster analysis was carried out with the four-dimensional niche and composite niche of regional tourism. Finally, an empirical analysis was performed on the tourism competitiveness in ten prefectures of Shaanxi Province, using the data in 2010–2018. The results show that the prefectures differed greatly in tourism development and competed fiercely against each other.

Evaluation of locations for testing dry bean cultivars in western Canada using statistical procedures, biological interpretation and multiple traits

1993 ◽  
Vol 73 (4) ◽  
pp. 985-994 ◽  
Author(s):  
G. Saindon ◽  
G. B. Schaalje
Keyword(s):  
Cluster Analysis ◽  
Seed Yield ◽  
Seed Weight ◽  
Visual Assessment ◽  
Western Canada ◽  
Multiple Traits ◽  
Dry Bean ◽  
Biological Interpretation ◽  
Environmental Events ◽  
High Level

Genotype × environment (GE) effects in regional registration trials for dry beans in western Canada were studied to determine whether geographic distribution of sites could be rationalized. The structure of the GE effects on the maturity, seed weight and seed yield of seven dry bean check cultivars grown at eight locations during 4 yr was investigated using GE mean squares decomposition, cluster analysis and the additive main effect and multiplicative interaction (AMMI) method. The analyses revealed a high level of redundancy in the locations which suggested that most GE effects can be captured with fewer testing sites. The partition of the GE mean squares demonstrated the possibility of reproducing the GE structure of the entire data sets with as few as three sites; however, more locations may be needed to compensate for unpredictable environmental effects. Based on biological interpretation of groupings and visual assessment of the AMMI displays, a five-location set fully represented the GE effects on maturity, seed weight and seed yield and accounted for the inconsistent clustering of the Brooks site for the three traits. Also, the set should allow for site losses due to unpredictable environmental events. The dry bean industry in western Canada is expanding to non-traditional growing areas and the establishment of trials in these areas should be considered as they may create GE effects not considered to date. Key words: Phaseolus vulgaris L., genotype × environment interactions, cluster analysis, AMMI analysis

Strategic orientations, knowledge management (KM) and business performance

Kybernetes ◽  
2019 ◽  
Vol 48 (9) ◽  
pp. 1942-1964 ◽  
Author(s):  
Mona Jami Pour ◽  
Mohammad Asarian
Keyword(s):  
Cluster Analysis ◽  
Knowledge Management ◽  
Business Performance ◽  
High Performance ◽  
Strategic Orientation ◽  
Content Type ◽  
Strategic Orientations ◽  
Strategy Performance ◽  
High Level ◽  
The Relationship

Purpose Despite the huge amount of studies that have investigated the strategy–performance relationships and knowledge management (KM)–performance relationships, there is little consensus regarding the nature of these connections. By reviewing related literature, some notable limitations and inconsistent results are highlighted in extant studies. To address these challenges, this study aims to explore the effects of strategic orientation and KM mechanisms on business performance. Design/methodology/approach The study conducted an empirical investigation of 227 small- and medium-sized enterprises (SMEs) to explore the relationship between strategy−performance and KM−performance. Business strategy is conceptualized as a comparative construct with six dimensions, KM is conceptualized by two types of KM mechanisms of technical and non-technical KM mechanisms and business performance is measured by four dimensions of balanced scorecard (BSC). The cluster analysis was used to explore different aspects of these three constructs. Findings Using cluster analysis, the results indicate that firms with high level of analysis, defensiveness, futurity and proactiveness in strategic orientation have better performance and also the high level of both KM mechanisms another important finding shows that firms with more KM mechanisms have high performance and technical mechanisms have more predictor role on performance. Practical implications This research also has prescriptive implications for strategic managers and KM practitioners. The finding enhanced the understanding of the relationship between strategic orientations, KM and performance. The results assist managers to assess business performance regarding strategic orientations and KM mechanisms of the firms. Therefore, it helps firms to improve strategic resource allocation and exploit KM investment by considering ideal pattern of the performance. Originality/value By reviewing strategic management and KM literature, it is revealed that there are little studies about how the interaction of strategic orientation and KM influences business performance. The main contribution of the study is exploring the profile of the firms by considering their strategic orientation and KM mechanisms and their impact on business performance. This study provides an empirical evidence about interaction of strategic orientations, KM mechanisms and business performance in SME context, which is merely investigated in previous researches.

scholarly journals Economic Growth, Policies and Influencing Factors: The Case of Albania

2016 ◽  
Vol 4 (1) ◽  
pp. 107
Author(s):  
Eleni Vangjeli ◽  
Anila Mancka
Keyword(s):  
Economic Growth ◽  
Monetary Policy ◽  
Fiscal Policy ◽  
Interest Rates ◽  
Empirical Analysis ◽  
Influencing Factors ◽  
Fiscal Policies ◽  
The Government ◽  
High Level ◽  
The Empirical Analysis

Monetary and fiscal policies are two policies that the government could use to keep a high level of growth, with a low inflancion. Fiscal policy has its initial impact on the stock market, while monetary policy in market assets. But, given that the goods and active markets are closely interrelated, both policies, monetary as well as fiscal have impact on the economy, increasing the level of product through the reduction of interest rates. In our paper we will show how functioning monetary and fiscal policies. But also in our paper we will analyze the different factors which have affected the economic growth of the country. The focus of our study is the graphical and empirical analysis of economic growth, policies and influencing factors. For the empirical analysis we have used data on the economic growth in Albania for 1996– 2014.

scholarly journals Spatiotemporal Difference Characteristics and Influencing Factors of Tourism Urbanization in China’s Major Tourist Cities

2021 ◽  
Vol 18 (19) ◽  
pp. 10414
Author(s):  
Xia Xie ◽  
Lei Zhang ◽  
Hui Sun ◽  
Feifei Chen ◽  
Chunshan Zhou
Keyword(s):  
Spatial Autocorrelation ◽  
Influencing Factors ◽  
Industrial Development ◽  
Tourism Industry ◽  
Three Dimensions ◽  
Ecological Environment ◽  
Upward Trend ◽  
Correlation Pattern ◽  
Resource Endowment ◽  
Tourism Urbanization

Tourism is crucial for promoting industrial development and is an important driver of China’s new type of urbanization. A tourism urbanization index system was constructed in three dimensions: the tourism industry, urbanization, and the ecological environment. The spatial–temporal differentiation characteristics and influencing factors of tourism urbanization in 35 major tourist cities in China from 2009 to 2018 were analyzed using the state space method, standard deviation ellipse, and spatial autocorrelation analysis. The results show the following. (1) Over time, the tourism industry index displays an upward trend, the urbanization index exhibits a more obvious upward trend, and the ecological environment index fluctuates strongly. Under the influence of all three factors, the tourism urbanization index shows a fluctuating rising trend. (2) Regarding the spatial distribution pattern, the development center of tourism urbanization shifts to the southeast, and the distribution direction is northeast-southwest. There is a significant agglomeration in global spatial autocorrelation. The local spatial correlation pattern is dominated by correlation characteristics and supplemented by different characteristics. (3) In terms of influencing factors, policy and regional development strategy, tourism resource endowment, economic development level, and traffic conditions are listed in descending order of influencing degree. Finally, we put forward some suggestions.

scholarly journals Variability of Phytochemicals by Breeding Year, Usage and Seed Size of Korean Soybean (Glycine max (L.) Merrill) Varieties

Agriculture ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 100
Author(s):  
Tae-Young Hwang ◽  
Byoung-Deok Park ◽  
Jwakyung Sung ◽  
Hong-Sig Kim
Keyword(s):  
Cluster Analysis ◽  
Seed Weight ◽  
Group Iv ◽  
Group Iii ◽  
Group I ◽  
Glycine Max L ◽  
Main Components ◽  
High Level ◽  
Different Origins ◽  
100 Seed Weight

The interest in phytochemicals from crops has grown in recent years, with soybean, as a functional crop, having great potential for providing a high level of nutrition. Therefore, the aim of this study was to evaluate phytochemicals from Korean soybean varieties, and to provide the basic information necessary for targeted breeding of soybean. The seeds of 172 soybean varieties were collected from various domestic institutes, and their phytochemicals were analyzed and compared based on agronomic characteristics (color, size, usage, etc.) using cluster analysis. We found that the soybean varieties contained relatively higher levels of the following phytochemicals: lutein (3 var., >7.0 μg g−1 seed), tocopherols (26 var., >300 μg g−1 seed), and phytosterols (33 var., >1000 μg g−1 seed). Overall, phytochemical levels were higher in varieties released since 2000 and with small-sized seeds (<12 g, 100-seed weight). The distribution of phytochemicals varied according to the usage (cooking, sauce, sprouts, etc.), even though the highest levels of each phytochemical were mainly observed in sprouts. The cluster analysis using three main components classified the varieties into five groups. Of them, group III showed relatively higher tocopherols, group IV had relatively higher lutein, and group I had relatively higher phytosterols. Jonam and Manpoong (group I) were observed in varieties high in phytochemicals. Overall, some Korean soybean varieties were found to have relatively higher levels of phytochemicals compared to those reported in previous studies of other origins. In conclusion, our findings suggest that some varieties might provide suitable breeding material for target-centered improvement of soybean varieties, and a comparison between different origins is necessary for providing better knowledge for soybean breeding.

scholarly journals Checking Heterogeneity and its Relationships with Action Identification Level

2017 ◽  
Vol 8 (3) ◽  
pp. 214-240
Author(s):  
S. Belayachi ◽  
M. Van Der Linden
Keyword(s):  
Cluster Analysis ◽  
Action Identification ◽  
Dysfunctional Beliefs ◽  
Low Level ◽  
Action Processing ◽  
Behavioral Dysregulation ◽  
Identification Theory ◽  
High Level

Consistent with the action identification theory proposal that some people identify their actions at a low-level (action processing regarding motor parameters) while others generally identify actions at a high-level (regarding goal features), and that a low-level of action identification leads to behavioral dysregulation (repetition, doubts about completion), checking proneness was found to be related to low-level action identification. Nevertheless, checking can be motivated by several factors (dysfunctional beliefs, incompleteness feelings). In the present research, we reexamine the level at which actions are identified by distinct subtypes of checking-prone participants. In Study 1, cluster analysis leads to the identification of four checking subtypes based on two dysfunctional beliefs domains (responsibility and perfectionism); our main results suggest that a low-level of action identification may characterize a checking subtype that is not motivated by responsibility related dysfunctional beliefs. Study 2 further reveals that anxiety features may characterize the checking subtype related to a low-level action identification.

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