Competitive Model Research Articles

ANALYZING COMPANY’S COMPETITIVENESS: DEFINITIONS AND INFLUENCING FACTORS

The article is devoted to the study of the competitiveness of the enterprise as an economic concept and an object of assessment. Issues that remain unresolved, despite the significant level of development of this issue, are considered. In particular, the problems of the integration of digital technologies as one of the main factors of competitiveness are highlighted, the importance of the adaptability of cross-industry innovations is shown, and the relationship between the concepts of sustainable development and the competitiveness of the enterprise is explained. It was determined that today enterprises, forming competitive advantages, face new challenges in the context of globalization. Much of the existing research focuses on static models of competitiveness, while prospective studies should pay more attention to how corporations can maintain competitiveness in a dynamic global marketplace. The article identifies the main factors in the formation of sustainable competitive advantages of enterprises in the conditions of the digital economy and the intensive spread of technologies. The authors proposed a schematic visualization of the multifaceted meaningful interrelationship of competitiveness and the main business competencies of innovative enterprises. Based on the analysis of scientific sources and previous empirical studies of the authors, the list of competitiveness factors is summarized, which is based on a synthetic approach and includes external, internal, macroeconomic, environmental, social, technological, innovative and other factors. It is emphasized that one of the key levers of the mechanism of formation of sustainable competitive advantages of enterprises in modern conditions of uncertainty is market adaptability, which is subject to economic analysis and forecasting. Thus, the authors note that innovation potential has become a key element for maintaining competitiveness, especially in technology-driven industries, while corporate social responsibility and sustainable development are increasingly seen as integral components of long-term competitiveness; moreover, with the deepening of globalization, companies must possess the ability to adapt to the conditions of international markets in order to remain competitive in the long term. The priority direction of further research is the development of a model for evaluating the market adaptability of innovatively active enterprises operating in growing markets.

Proximity or Directional Model of Voting for the Turkish Voter?

Voting behavior is a very complex type of political behavior. Therefore, understanding why voters vote for a particular political party or a candidate requires developing complex models. In 1957, Anthony Downs, who built his model on Hottelings’ and Smithies’ models, argued that political parties’ and candidates’ ideological and issue positions can be expressed on a one-dimensional space. On one hand, it was highly reductionist to argue that political ideas on a particular issue can be expressed this way, on the other, it was highly practical from analytical point of view. Locating parties, candidates and voters on a one-dimensional space according to their ideological or issue positions was then a revolutionaly idea and helped comparing party, candidate and voter ideological and issue positions within and across countries. These models, which were called spatial models of party competition were further developed over time and helped understanding voting behavior. Currently, spatial models of party competition have two major competing models linking voter ideological positions with party ideological positions. Simply, while the proximity model proposes that voters vote for the parties or candidates that hold ideological positions in the political space that are closest to their own, the directional model suggests that the voters vote for the parties or candidates that are on their side of the two-dimensional political spectrum and more extreme than their own while being within the acceptability region. This research aims to test the applicability of these two voting models for the Turkish voter. Türkiye constitutes an interesting case study with its long-term PR electoral system as it was suggested in the extant literature that proximity model is a more appropriate tool to explain voting behavior in Proportional (PR) systems. Thus, we hypothesize that in Türkiye, where a PR electoral system is in effect for parliamentary elections, voter electoral preferences are better explained by the proximity model than the directional model. Our research analyzes Comparative Study of Electoral Systems (CSES) data for voters of the four major political parties in Türkiye, the Justice and Development Party (JDP), the Republican People’s Party (RPP), the National Action Party (NAP), and the People’s Democratic Party (PDP). A series of Multiple Linear Regression Analyses were conducted to reveal associations between the dependent and the independent variables. Voter embracement, as expressed as like-dislike of each political party for each voter, is seperately used as the dependent variable for each analysis. Issue distance and issue scalar product were used as key independent variables representing the formulas for the proximity and the directional models, respectively. Additionally, education, age, gender and income were recruited as classical control variables. Comparing explanatory powers of the statistical models showed that, contrary to the findings of MacDonald and his colleagues, the proximity model of voting is a more appropriate tool than the directional model to explain voting behavior in Türkiye. From a macro-political perspective, this finding supports Westholm’s (1997) argument that the PR provides a more appropriate tool to explain voting behavior in PR systems. Yet, it should be noted that further multi-country comperative analyses required for certain results.

A Bayesian tensor ring decomposition model with automatic rank determination for spatiotemporal traffic data imputation

Recently, tensor factorization models have shown superiority in solving traffic data imputation problem. However, these approaches have a limited ability to learn traffic data correlations and are easy to overfit when the pre-defined rank is large and the available data is limited. In this paper, we propose a Bayesian tensor ring decomposition model, utilizing Variational Bayesian Inference to solve the model. Firstly, tensor ring decomposition with an enhanced representational capability is used to decompose partially observed data into factor tensors to capture the correlation in traffic data. Secondly, to address the issue of selecting large pre-defined rank when data availability is limited, an automatic determination mechanism of tensor ring ranks is proposed. This mechanism can be implemented by pruning the zero-component horizontal and frontal slices of the core factors in each iteration, reducing the dimensions of the core factors and consequently lowering the tensor ring ranks. Finally, extensive experiments on synthetic data and four diverse types of real-world traffic datasets demonstrate the superiority of the proposed model. In the Guangzhou dataset, the maximum improvement in Mean Absolute Percentage Error can reach 15 % compared to the most competitive baseline model.

Firm strategy, employee retention and organizational performance: a moderated mediation study of New Zealand SMEs

PurposeAn effective firm strategy is key to sustained financial performance, while interactions between strategy, employee retention and top talent retention have been seldom explored. We test hypotheses using New Zealand SMEs which are defined as having up to 250 employees. We initially explore firm strategy using Porters competitive advantage model predicting employee retention (including top talent), with study 1 (n = 208) using firm size as a moderator, finding a direct significant relationship from firm strategy toward employee retention. Next, we explore firm strategy predicting firm performance with employee retention mediating and include firm size as a moderator, testing a moderated mediation model in study 2 (n = 474) and study 3 (n = 300, with time-lagged performance).Design/methodology/approachThere are no open databases holding NZ firms’ performance data and thus data was sourced from a Qualtrics survey panel. Such panels have become more common (e.g. Haar et al., 2021a, b) and a recent meta-analysis by Walter et al. (2019) showed that this type of panel data was no different from data sourced through conventional means (i.e. mail survey). We focused on NZ private sector SMEs using senior managers across a range of industries and geographic locations. Because the influence of firm strategy on employee retention remains unknown in the literature, we conducted study 1 (n = 208) to test the initial part of our overall model. Study 2 (n = 474) and study 3 (n = 300) tested the full model (with organizational performance), with study 3 having organizational performance time-lagged by one month.FindingsAll direct effect hypotheses are supported, although firm size interacted significantly with firm strategy showing smaller not larger-sized firms leverage firm strategy to achieve superior retention benefits. This was against hypothesis 5a in all three studies. Studies 2 and 3 supported the moderated mediation hypothesis, with firms of larger size having a stronger indirect effect from firm strategy on firm performance while employee retention mediated the influence of firm strategy on firm performance. Finally, dominance analysis found that a quality differentiation strategy was the key strategy across all studies and outcomes. We discuss the implications for organizations.Practical implicationsThe first managerial implication from the study is that small and medium sized firms would benefit both from developing a deeper understanding of the strategic alternatives open to them and placing a greater emphasis on the implementation of their selected strategic approach. A second managerial implication relates to findings indicating that retention generally, and top talent retention specifically, is positively related to firm strategy and firm performance. Given the importance and challenges of staff retention, particularly in the current environment where there are significant skill shortages, these results suggest that small and medium sized business would benefit from considering how strategy can create an organizational environment that is attractive to employees and support stronger retention outcomes as a mechanism for driving both retention and performance.Originality/valueThe study makes three major contributions. First, it examines firm strategy and extends the focus on firm performance by including not only employee retention but also top talent retention, responding in part to the call to develop and refine performance measures (Lieberman, 2021). Second, beyond using retention as a mediator, firm size is included as a moderator and a moderated mediation model is ultimately tested. Third, we conduct dominance analysis to identify the key firm strategy that influences firm performance and retention. Ultimately, this paper asks: what is the role of firm strategy on New Zealand SME performance, and what influence does retention and relative firm-size play.

The Impact and Implications of Integrating Competitions with Teaching on the Cultivation of Chengdu Artisans

In the current field of vocational education, the integration of competitions with teaching has become a crucial strategy for driving innovation in technical skill instruction. This paper systematically analyzes the implementation of this integrated model in the Chengdu region, exploring its application effects and profound impact on educational practices in artisan cultivation. The article first defines the integration model of competitions and teaching and details its specific implementation process, strategies adopted, and challenges faced in Chengdu. Through field research and data analysis, the study evaluates the specific contributions of this model to enhancing artisan skills and educational quality, and discusses its potential for nationwide promotion and the challenges that may arise. The research results indicate that the integration model significantly improves students' practical skills and innovative thinking, providing new directions for vocational education development.

Bureacractic costs and firm behavior

ABSTRACT This note sketches the theory of how bureaucratic costs can affect firm behaviour resulting in inefficiency and corruption. The canonical competitive model of the firm maximizing output subject to an input cost constraint is modified to include a second constraint capturing bureaucratic costs. That constraint imposes efficiency costs on firms which are explored for testable empirical hypotheses including willingness to make informal payments or pay bribes to bureaucrats.

Plant antagonistic facilitation across environmental gradients: a soil-resource ecosystem engineering model.

Theory questions the persistence of nonreciprocal interactions in which one plant has a positive net effect on a neighbor that, in return, has a negative net impact on its benefactor - a phenomenon known as antagonistic facilitation. We develop a spatially explicit consumer-resource model for belowground plant competition between ecosystem engineers, plants able to mine resources and make them available for any other plant in the community, and exploiters. We use the model to determine in what environmental conditions antagonistic facilitation via soil-resource engineering emerges as an optimal strategy. Antagonistic facilitation emerges in stressful environments where ecosystem engineers' self-benefits from mining resources outweigh the competition with opportunistic neighbors. Among all potential causes of stress considered in the model, the key environmental parameter driving changes in the interaction between plants is the proportion of the resource that becomes readily available for plant consumption in the absence of any mining activity. Our results align with theories of primary succession and the stress gradient hypothesis. However, we find that the total root biomass and its spatial allocation through the root system, often used to measure the sign of the interaction between plants, do not predict facilitation reliably.

Evolution of cooperation in a mixed cooperative–competitive structured population

Cooperation and competition are two pivotal topics in the literature on the evolutionary dynamics of individual behavior on social networks. This study provides a perspective of joint analysis of social dilemmas within groups and inter-group competition in a mixed cooperative–competitive structured population. Although specific mechanisms for interpreting the emergence and promotion of cooperation have been proposed, including reward, punishment, reputation, and environmental factors, little is known about how inter-group competition affects the cooperation level of groups, especially the intensity and structures of competitive games. Based on multi-games, a mixed cooperative–competitive game model is proposed that individuals within a group engage in a donation game and those from different groups participate in competitive games. The results of numerical simulations suggest that the reward of inter-group competition serves as an external incentive, fostering cooperation within groups. As the intensity of competitive games increases, cooperation within groups is prompted. Additionally, strategic inter-group connections based on degree heterogeneity significantly enhance within-group cooperation, particularly when hubs from one group engage in competitive games with marginal nodes from another group. This research contributes valuable insights into the dynamics of cooperation within groups considering the impact of inter-group competition on within-group cooperation.

Exploring tourism competitiveness in developing economies: residents’ perspective

Understanding the factors that contribute to tourism competitiveness in developing economies is essential for policymakers, industry stakeholders, and researchers, as these countries still struggle to fully capitalize on their tourism potential. The residents’ perspective, often overlooked in Tourism Destination Competitiveness (TDC) models, is crucial because they are the primary stakeholders who directly experience the consequences of tourism activities in their daily lives. Their positive attitudes can contribute to a welcoming and friendly environment, enhancing the competitiveness of the destination in the global tourism market. Up to now, there have been a few studies that relate residents’ attitudes to tourism destination competitiveness. However, none have focused on developing a tailor-made model for measuring residents’ perspectives on TDC. To develop such a specific model and contribute to the existing theory in this area, our research applied a multi-step approach, including a literature review of existing models, pilot testing for indicator selection, and model validation through CFA. The data were collected through a survey of residents in Serbia, chosen as an example of a developing country. The final model of the study consists of five factors: Natural and Cultural Resources, Quality of Tourist Offer and Infrastructure, Situational Framework of Tourism Development and Management, Destination Perception and Experience, and Pollution, containing 32 indicators. Practical applicability of the model and theoretical contributions are discussed in the paper, as well as the TDC evaluation for Serbia.

Computer-Aided Diagnosis of Diabetic Retinopathy Lesions Based on Knowledge Distillation in Fundus Images

At present, the early diagnosis of diabetic retinopathy (DR), a possible complication of diabetes due to elevated glucose concentrations in the blood, is usually performed by specialists using a manual inspection of high-resolution fundus images based on lesion screening, leading to problems such as high work-intensity and accessibility only in specialized health centers. To support the diagnosis of DR, we propose a deep learning-based (DL) DR lesion classification method through a knowledge distillation (KD) strategy. First, we use the pre-trained DL architecture, Inception-v3, as a teacher model to distill the dataset. Then, a student model, also using the Inception-v3 model, is trained on the distilled dataset to match the performance of the teacher model. In addition, a new combination of Kullback–Leibler (KL) divergence and categorical cross-entropy (CCE) loss is used to measure the difference between the teacher and student models. This combined metric encourages the student model to mimic the predictions of the teacher model. Finally, the trained student model is evaluated on a validation dataset to assess its performance and compare it with both the teacher model and another competitive DL model. Experiments are conducted on the two datasets, corresponding to an imbalanced and a balanced dataset. Two baseline models (Inception-v3 and YOLOv8) are evaluated for reference, obtaining a maximum training accuracy of 66.75% and 90.90%, respectively, and a maximum validation accuracy of 35.94% and 81.52%, both for the imbalanced dataset. On the other hand, the proposed DR classification model achieves an average training accuracy of 99.01% and an average validation accuracy of 97.30%, overcoming the baseline models and other state-of-the-art works. Experimental results show that the proposed model achieves competitive results in DR lesion detection and classification tasks, assisting in the early diagnosis of diabetic retinopathy.

Strengthening AKIS for Sustainable Agricultural Features: Insights and Innovations from the European Union: A Literature Review

The Agricultural Knowledge and Innovation System (AKIS) and the Farm Advisory Service (FAS) are important elements of the current Programming Period of the Common Agricultural Policy (2023–2027), as it is now deemed necessary to transition the European agricultural model to more sustainable forms, through the dissemination of agricultural knowledge, while simultaneously promoting innovative methods. An Agricultural Knowledge and Innovation System must be able to propose and develop ideas for the transmission of agricultural knowledge, promoting innovation and the exchange of ideas. The present study includes a significant number of investigations on the effectiveness of the implementation of the AKIS and the FAS so that the conclusions are representative of the scope of the work. The object in question is now the cornerstone of the modernization of agricultural production and an important way out towards more competitive models of agriculture. The purpose of this paper is to give an extensive overview of the degree of implementation of Agricultural Knowledge and Innovation Systems in the countries of the European Union (including the United Kingdom until 2019) from 2014 until today, essentially during the implementation of the second period of Common Agricultural Policy. In the context of this article, the main results of the research carried out in the EU countries during the period under study and the proposed improvements by the researchers, where they are mentioned, are recorded epigrammatically. Finally, the countries are categorized according to the degree of implementation of the AKIS and the contribution of the Agricultural Advisory System to more sustainable forms of agricultural practices.

A novel multi-frame image super-resolution model based on regularized nonlinear diffusion with Caputo time fractional derivative

In this work, we introduce an innovative fractional nonlinear parabolic model using a time-fractional order derivative, specifically employing the Caputo sense for fractional differentiation. This model aims to enhance traditional super-resolution models, particularly in the context of multi-frame image super-resolution. Additionally, we incorporate a regularized Perona–Malik diffusion mechanism to control the speed and direction of diffusion at each image location. We begin our study by exploring the theoretical solvability of our proposed model. Firstly, we employ the Faedo–Galerkin approach to establish the existence and uniqueness of a weak solution for an auxiliary fractional super-resolution model. Subsequently, we use the Schauder fixed point method to demonstrate the existence and uniqueness of a weak solution for our model. To validate the effectiveness of our model in the multi-frame super-resolution (SR) context, we conduct numerical experiments on images featuring diverse characteristics, including corners and edges, while applying various warping, decimation, and blurring matrices to the low-resolution (LR) images. We start the evaluation by introducing an adaptive discrete scheme tailored to the proposed model. To prove the robustness of our approach, we subject our images to varying levels of noise. Additionally, we perform simulations on real data (videos). The obtained high-resolution (HR) results demonstrate notable efficiency and robustness against noise, outperforming competitive models both visually and quantitatively.

COMPETITION BETWEEN PLASMID-BEARING AND PLASMID-FREE ORGANISMS IN A CHEMOSTAT WITH DISTINCT REMOVAL RATES AND AN EXTERNAL INHIBITOR

A mathematical model of competition between plasmid-bearing and plasmid-free organisms for a single limiting resource in a chemostat with distinct removal rates and in the presence of an external inhibitor is analyzed. This model was previously introduced in the special case where the growth rate functions and the absorption rate of the inhibitor follow the Monod kinetics and the removal rates are the same as the dilution rate. Here, we consider the general case of monotonic growth and absorption functions, and distinct removal rates. Through the three operating parameters of the model, represented by the dilution rate, the input concentrations of the substrate and the inhibitor, we give necessary and sufficient conditions for existence and stability of all equilibria. To better understand the richness of the model’s behavior with respect to those operating parameters, we determine the operating diagram theoretically and numerically. This diagram is very useful to understand the model from both the mathematical and biological points of view.

Do existing competitiveness models comprehensively assess the competitiveness context of the contemporary agribusiness sector? A systematic review

Do existing competitiveness models comprehensively assess the competitiveness context of the contemporary agribusiness sector? A systematic review

A business model framework for nature tourism entrepreneurs

ABSTRACT Small-scale tourism entrepreneurs play an important role in the development of nature tourism destinations, and building competitive business models can be crucial for the success of both these entrepreneurs and the nature destinations they inhabit. However, traditional business model frameworks do not adequately capture the unique characteristics of nature tourism and its entrepreneurs, such as their non-economic and nature-based values. Thus, developing knowledge about business models for nature tourism entrepreneurs calls for an alternative theoretical approach. This paper aims to develop such a novel approach by integrating existing knowledge about the unique characteristics of nature tourism and its entrepreneurs with a Service Dominant Logic theory, which incorporates both human and non-human actors such as nature. To illustrate the analytical relevance of the framework, it is applied in a case study of nature tourism entrepreneurs that identifies internal incongruences within the entrepreneurs’ existing business models. The case study also demonstrates how the entrepreneurs attempt to address these incongruences. The framework is relevant also to other small scale tourism entrepreneurs operating in other contexts.

Advance-selling strategies under platform competition

With the competition between e-commerce platforms intensifying, advance-selling has gradually become a mainstream marketing strategy. This article establishes a mathematical model of competition between two platforms and retailers, considering four scenarios: spot-sale only, advance-selling only, spot-sale with coupons, advance-selling with coupons. The study explores the impact mechanism of platform competition on advance-selling strategies. The results show that when the advantage of product evaluation is large, the unit transaction cost is small or the product cost is low, the retailers should actively adopt the advance-selling scheme with discount pricing. Compared with low-value products, high-value products are priced higher and have greater demand, which can bring higher revenue to the retailers and the platforms. The benefits of the advance-selling scheme are limited, but the issuance of coupons could increase the revenue of both platforms and retailers, and the value of platform coupons in the spot-sale market is higher. JEL Classification: L81, C79

Video Salient Object Detection Via Multi-level Spatiotemporal Bidirectional Network Using Multi-scale Transfer Learning

Video saliency prediction aims to resemble human visual attention by identifying the most relevant and significant elements in a video frame or sequence. This task becomes notably intricate in scenarios characterized by dynamic elements such as rapid motion, occlusions, blur, background variations, and nonrigid deformations. Therefore, the inherent complexity of human visual attention behavior during dynamic scenes necessitates the assessment of both temporal and spatial data. Existing video saliency frameworks often falter under such conditions, and relying solely on image saliency models neglects crucial temporal information in videos. This study presents a new Video Salient Object Detection via Multi-level Spatiotemporal Bidirectional Network using Multi-scale Transfer Learning (MSB-Net) to address the problem of identifying significant objects in videos. The proposed MSB-Net achieves notable results for a given sequence of frames by employing multi-scale transfer learning with an encoder and decoder approach to acquire knowledge and saliency map attributes spatially and temporally. The proposed MSB-Net model has bidirectional LSTM (Long Short-Term Memory) and CNN (Convolutional Neural Network) components. The VGG16 (Video Geometry Group) and VGG19 architectures extract multi-scale features from the input video frames. Evaluation of diverse datasets, namely DAVIS-T, SegTrack-V2, ViSal, VOS-T, and DAVSOD-T, demonstrates the model's effectiveness, outperforming other competitive models based on parameters such as MAE, F-measure, and S-measure.

A citizen-candidate model of party formation

There are multiple models of party formation in the political economy literature. However, most of these works consider individuals as parties and do not model parties as a group of candidates. In this paper, we follow the latter approach and assume that parties form as a result of mutually agreeable links between candidates. We consider a citizen-candidate model of electoral competition where candidates decide whether they want to participate in election alone or offer links to adjacently placed candidates on a one-dimensional policy space. We characterize one-party and two-party equilibrium and show that no multi-party equilibrium exists with three or more parties. We provide conditions on the rents of winning with respect to the cost of participating in election which also depend on the number of candidates. We provide new insights which explain party formation from the perspective of group formation. Our results confirm the Duverger’s law and are consistent with empirical evidence on plurality voting systems.

Discovery of Curcuminoids as Pancreatic Lipase Inhibitors from Medicine-and-Food Homology Plants.

Researchers are increasingly interested in discovering new pancreatic lipase inhibitors as anti-obesity ingredients. Medicine-and-food homology plants contain a diverse set of natural bioactive compounds with promising development potential. This study screened and identified potent pancreatic lipase inhibitors from 20 commonly consumed medicine-and-food homology plants using affinity ultrafiltration combined with spectroscopy and docking simulations. The results showed that turmeric exhibited the highest pancreatic lipase-inhibitory activity, and curcumin, demethoxycurcumin, and bisdemethoxycurcumin were discovered to be potent pancreatic lipase inhibitors within the turmeric extract, with IC50 values of 0.52 ± 0.04, 1.12 ± 0.05, and 3.30 ± 0.08 mg/mL, respectively. In addition, the enzymatic kinetics analyses demonstrated that the inhibition type of the three curcuminoids was the reversible competitive model, and curcumin exhibited a higher binding affinity and greater impact on the secondary structure of pancreatic lipase than found with demethoxycurcumin or bisdemethoxycurcumin, as observed through fluorescence spectroscopy and circular dichroism. Furthermore, docking simulations supported the above experimental findings, and revealed that the three curcuminoids might interact with amino acid residues in the binding pocket of pancreatic lipase through non-covalent actions, such as hydrogen bonding and π-π stacking, thereby inhibiting the pancreatic lipase. Collectively, these findings suggest that the bioactive compounds of turmeric, in particular curcumin, can be promising dietary pancreatic lipase inhibitors for the prevention and management of obesity.

Interspecific competition models and resource inequality between individuals.

Most classical discrete-time population models of interspecific competition have emerged as population-level phenomenological models with no evident basis at the individual level. This study shows that the Hassell-Comins model, a widely used discrete-time model of interspecific competition, can be derived in a bottom-up manner from a simple model of random resource competition between individuals of two species as an expression of expected population sizes in the next generation. The random competition leads to inequalities in resource allocation between individuals, which are related to the key parameters of the Hassell-Comins model that determine the density dependence of each species. The relationship between population-level parameters, such as intra- and interspecific competition coefficients, and individual-level parameters is discussed in detail, as is how the derived competition equations depend on the degree of inequality within each species. By considering limits of maximum or minimum resource inequality within each species, the derived model can describe interspecific competition for various combinations of two species exhibiting ideal scramble or ideal contest intraspecific competition.