Closest Competitor Research Articles

Direct and indirect effects of regional and local climatic factors on trophic interactions in the Arctic tundra

Climate change can impact ecosystems by reshaping the dynamics of resource exploitation for predators and their prey. Alterations of these pathways could be especially intense in ecosystems characterized by a simple trophic structure and rapid warming trends, such as in the Arctic. However, quantifying the multiple direct and indirect pathways through which climate change is likely to alter trophic interactions and their relative strength remains a challenge. Here, we aim to identify direct and indirect causal mechanisms driven by climate affecting predator-prey interactions of species sharing a tundra food web. We based our study on relationships between one Arctic predator (Arctic fox) and its two main prey - lemmings (preferred prey) and snow geese (alternate prey) - which are exposed to variable local and regional climatic factors across years. We used a combination of models mapping multiple causal links among key variables derived from a long-term dataset (21years). We obtained several possible scenarios linking regional climate factors (Arctic oscillations) and local temperature and precipitation to the breeding of species. Our results suggest that both regional and local climate factors have direct and indirect impacts on the breeding of foxes and geese. Local climate showed a positive causal link with goose nesting success, while both regional and local climate displayed contrasted effects on the proportion of fox breeding. We found no impact of climate on lemming abundance. We observed positive relationships between lemming, fox and goose reproduction highlighting numerical and functional responses of fox to the variability of lemming abundance. Our study measures causal links and strength of interactions in a food web, quantifying both numerical response of a predator and apparent interactions between its two main prey. These results improve our understanding of the complex effects of climate on predator-prey interactions and our capacity to anticipate food web response to ongoing climate change.

Temporal partitioning of activity: rising and falling top‐predator abundance triggers community‐wide shifts in diel activity

Top predators cause avoidance behaviours in competitors and prey, which can lead to niche partitioning and facilitate coexistence. We investigate changes in partitioning of the temporal niche in a mammalian community in response to both the rapid decline in abundance of a top predator and its rapid increase, produced by two concurrent natural experiments: 1) the severe decline of the Tasmanian devil due to a transmissible cancer, and 2) the introduction of Tasmanian devils to an island, with subsequent population increase. We focus on devils, two mesopredators and three prey species, allowing us to examine niche partitioning in the context of intra‐ and inter‐specific competition, and predator–prey interactions. The most consistent shift in temporal activity occurred in devils themselves, which were active earlier in the night at high densities, presumably because of heightened intraspecific competition. When devils were rare, their closest competitor, the spotted‐tailed quoll, increased activity in the early part of the night, resulting in increased overlap with the devil's temporal niche and suggesting release from interference competition. The invasive feral cat, another mesopredator, did not shift its temporal activity in response to either decreasing or increasing devil densities. Shifts in temporal activity of the major prey species of devils were stronger in response to rising than to falling devil densities. We infer that the costs associated with not avoiding predators when their density is rising (i.e. death) are higher than the costs of continuing to adopt avoidance behaviours as predator densities fall (i.e. loss of foraging opportunity), so rising predator densities may trigger more rapid shifts. The rapid changes in devil abundance provide a unique framework to test how the non‐lethal effects of top predators affect community‐wide partitioning of temporal niches, revealing that this top predator has an important but varied influence on the diel activity of other species.

Shopping Hours and Entry - an Empirical Analysis of Aldi’s Opening Hours

Aldi, the biggest discounter in Germany, started to systematically extend shopping hours of its stores in 2016. We interpret the decision to extend opening hours of a specific Aldi store as entry into a new market. By using a novel data set containing the opening hours of nearly all German grocery retailers, we find the following interesting correlations: The probability that a given Aldi outlet extends its shopping hours past 8 p.m. (i) increases if nearby Aldi outlets already extended shopping hours and (ii) decreases if nearby stores run by Aldi’s close competitors did not expand shopping hours past 8 p.m.. These results seem surprising in conjunction with cannibalization and residual demand, but can be explained by consumer and firm learning or market expansion.

Strategic Competitive Advantages through Enterprise Systems: The Case of Exchange Systems

Enterprise Systems play a key role in securities trading. Exchange operators spend great effort in overhauling their IT-infrastructure to satisfy the needs of market participants who require faster and more resilient order management cycles. Previous studies have disregarded the question whether such specific IT-investments lead to competitive advantages. Against this background, we empirically analyze the impact of exchange system upgrades on the market share of the respective exchange. Using a benchmarking approach against the closest competitor, we find that exchange system overhauls significantly increase the attracted trading volume. We conclude that investments in enterprise systems provide benefits and lead to competitive advantages for the upgrading firm.

Retail Competition on Social Media: Insights from Analysis of Large-scale Twitter Data

Social media platforms have been used by firms for a variety of purposes including for attracting new customers, communicating with existing customers, building firms’ brand image, among others. However, there is very little research on the content strategies adopted by traditional rival firms competing on online social media platforms and what the effects of such content strategies are on related outcomes. Our paper seeks to fill this gap by examining whether retailers that are close competitors in the traditional context also adopt similar content strategies on Twitter. In doing so, our study proposes a new measure of online social media competition based on content similarity. We find that traditional close competitors that have a higher degree of similarity offline, show greater divergence in their content strategies online. We also find that firms whose online content strategies are less similar to their close traditional rivals have higher online engagement and acquire new followers faster. We then examine why divergence in online content strategies from close traditional rivals leads to better online outcomes for firms on Twitter. We find that their superior online performance is attributable to their ability to leverage the higher-level affordances of Twitter more effectively as compared to their rivals. Our findings have important implications for firms’ competitive strategies in online social media platforms.

Impact of Learning from Experience on the Selection of a Competitor as a Partner for Innovation

More and more firms collaborate with competitors to innovate. While coopetition provides significant benefits, it is also a risky strategy, especially when the partners are close competitors. Recen...

Comparative Analysis of Competitiveness of Shangai Cooperation Organization Members and Turkey

The Shanghai Cooperation Organization (SCO) is a regional integration that emerged in the Central Asian region about 20 years ago and has been on the agenda of Turkey for the last few years. In particular, disputes between Turkey-and EU in recent years have led the various segments to express the SCO as a possible alternative to the EU in the future. In this study, the export specialization and competition levels of the SCO region countries and Turkey are analysed in terms of products and Lall (2000) based technological categories. The comparative advantages of the SCO countries and Turkey are calculated using the Balassa index for the 1993-2016 interval. Analysis revealed that Turkey has a comparative advantage in especially low and medium technology and resource based products. It is evident that while the Russian Federation, Kazakhstan, and Kyrgyzstan have comparative advantage in primary and resource-based products, China has over-unity RCA in low and medium technology products, India in primary, resource-based and low-tech products, and Pakistan in low technology and primary products. In other words Turkey and SCO countries possess a similar comparative advantage pattern with respect to the technological classification. Besides, the ratio of advanced technology products with RCA over-unity is almost zero for all the countries in consideration. Additionally, in the case of products in which Turkey has a strong comparative advantage, it is shown that the closest competitors are China, India and Pakistan.

The Relationship between Competitive Pricing and Direct-to-Consumer Advertising

ABSTRACT The oligopolistic nature of the U.S. pharmaceutical industry presents its members with a unique opportunity to leverage the interaction between competitive pricing strategy and promotion strategy. Previous studies have examined the role of direct-to-consumer advertising in influencing demand and sales; this study emphasizes the impact of consumer advertising on a supply-side phenomenon, the setting of prices relative to those of close competitors.

Questions that Have Arisen since the EU Decision on the Whatsapp Acquisition by Facebook

On October 3rd, 2014, the European Commission (EC) concluded the analysis of the transaction by which Facebook, Inc. (“Facebook”, USA) had acquired WhatsApp Inc. (“WhatsApp”, USA) by way of a purchase of shares for US$ 19 billion, which contributed to Facebook’s strategy of focusing its business on mobile development (Case no. COMP/M.7217). In its decision, the EC stated that the deal would raise no competition concerns and authorised the proposed acquisition of WhatsApp by Facebook concluding that Facebook Messenger and WhatsApp are not close competitors and that consumers would continue to have a wide choice of alternatives for consumer communication apps after the acquisition. The EC analysed potential data concentration issues only within the scope that the acquisition could weigh down competition in the online advertising market. Privacy-related concerns from the increased concentration of data within the control of Facebook because of the deal with WhatsApp are not an EU Competition Law matter. Notwithstanding, just some months after the decision two national competition authorities (Germany and Italy) opened procedures against Facebook. In Germany, the Bundeskartellamt initiated in March 2016 a proceeding against Facebook – Facebook Inc., USA, the Irish subsidiary of the company, and Facebook Germany GmbH, Hamburg – on suspicion that Facebook had abused its market power by infringing data protection rules with its specific terms of service on the use of user data. In Italy, in May 2017, the Autorità Garante della Concorrenza e del Mercato (AGCM) fined WhatsApp EUR 3 million for having forced its users to share their personal data with Facebook as a conclusion of two investigations opened in October 2016 concerning infringements of the Consumer Code. The present article proposes to answer three main questions concerning the EC decision on the WhatsApp acquisition by Facebook: (i) Did the EC apply the best tools to analyse the case?; (ii) Could the EC have addressed a decision that would somehow interfere in the privacy field?; and (iii) Could the procedures in Germany and Italy have been avoided?

How Product Attributes Affect Consumer Decision To Purchase A Premium Scooter Matic?

The automotive industry is one of the industries with the largest growth rate in Indonesia. The motorcycle is chosen as the most favorite means of transportation due to their superiority in affordability, maintenance costs, fuel costs and effectiveness of travel time. Among companies that compete fiercely for this market niche are PT. Astra Honda and PT. Yamaha Indonesia Motor Manufacturing. Both of them recently launched a new variant in the premium automatic scooter segment namely Yamaha NMax 155 cc and Honda PCX 150 cc. Although Honda dominates the scooter market segment in general, the AISI data in the early semester of 2018 shows that the achievement of sales of Honda PCX is far behind their closest competitor, Yamaha NMax in the range of 2:8. So that it becomes interesting for the researchers to know the perceptions of quality, features, style, and design of Honda PCX's attributes on consumer decisions in purchasing related products. Respondents involved in this study were 60 members of the HPCI (KAPURSUCI) community, Purwakarta, Subang and Cikarang using non-probability sampling techniques, which is accidental sampling on filling each questionnaire. The results of this study conclude that there is a positive influence between product attributes possessed by Honda PCX (quality, features, and product design) on the purchasing decisions.

Prospects of Oman as a Destination for Halal Tourism

Although a vast majority relates the concept of ‘halal’ or what is permissible in Islam to food only. However, halal industry covers many sectors such as food, fashion, transport, finance and even tourism. Halal tourism is not just about halal food, it is also about the overall experience, which is amenable with the Shariah (Islamic jurisprudence). Oman has a plethora of natural beauty and many places of interest for all types of tourists. It is one of the most secure and peaceful countries in the world. Having a well-developed Infrastructure, Oman is ready to take its tourism to new heights. The ever-hospitable Omanis are proud of their rich cultural and historical heritage. Thus, Oman appears to have all what it takes to become a prime destination for halal tourism. The objective of this study is to assess the prospects of Oman as a destination for halal tourism. Based on the interviews of experts like academicians, tourism professionals, officials and clerics, Oman’s competitiveness as a destination for halal tourism was assessed by developing a Strengths, Weaknesses, Opportunities and Threats (SWOT) profile. The findings of the SWOT were compared with the data from the Global Muslim Travel Index (GMTI) from the year 2014 to 2018. Based on the analysis, Oman is found to have the right mix of environment and enabling services for halal tourism. However, it is found lacking in public transport, communication and customer outreach. Oman is also found to be losing its rank among the top 10 destinations for halal tourism to close competitors like Qatar, Bahrain, Morocco, etc. The concerned authorities need to make conscious efforts to resolve these issues as it becomes imperative for Oman to revamp its tourism strategy.
 JEL codes: Z31, M31

Efficient Subgraph Matching on Large RDF Graphs Using MapReduce

With the popularity of knowledge graphs growing rapidly, large amounts of RDF graphs have been released, which raises the need for addressing the challenge of distributed subgraph matching queries. In this paper, we propose an efficient distributed method to answer subgraph matching queries on big RDF graphs using MapReduce. In our method, query graphs are decomposed into a set of stars that utilize the semantic and structural information embedded RDF graphs as heuristics. Two optimization techniques are proposed to further improve the efficiency of our algorithms. One algorithm, called RDF property filtering, filters out invalid input data to reduce intermediate results; the other is to improve the query performance by postponing the Cartesian product operations. The extensive experiments on both synthetic and real-world datasets show that our method outperforms the close competitors S2X and SHARD by an order of magnitude on average.

Competitive B2 and B33 Nucleation during Solidification of Ni50Zr50 Alloy: Molecular Dynamics Simulation and Classical Nucleation Theory

We investigated the homogenous nucleation of the stoichiometric B2 and B33 phases in the Ni50Zr50 alloy using the persistent embryo method and the classical nucleation theory. The two phases become very close competitors at large supercoolings, which is consistent with the experimental observations. In the case of the B2 phase, the linear temperature dependence of the solid-liquid interface (SLI) free energy extrapolated to the melting temperature leads to the same value as the one obtained from the capillarity fluctuation method (CFM). In the case of the B33 phases, the SLI free energy is also a linear function of temperature at large supercoolings but the extrapolation to the melting temperature leads to a value which is considerably different from the CFM value. This is consistent with the large anisotropy of the SLI properties of the B33 phase nearby the melting temperature observed in the simulation of the nominally flat interface migration.

AB143. 9. Comparison of functional outcomes of the ATTUNE total knee arthroplasty system versus its five closest competitors

Background: Total knee arthroplasty (TKA) system success is guided by validated patient reported outcome measures (PROMs). It is essential to continually innovate TKA to ensure an excellence of care for the vast numbers of prospective patients. Techniques and implant designs have evolved as a result of the strong evidence behind them. The primary outcome of this study is to analyse differences in PROMs after TKA comparing the ATTUNE knee system to its 5 closest competitors. Secondary outcome measures were to analyse rates of venous thromboembolic events (VTE), periprosthetic infection (PJI) and noninfective reoperation rates.

Economics of digital mergers

The article reveals the main problems of antitrust law caused by the widespread use of digital technologies. The greatest challenge brought by the proliferation of digital technology and data is the emergence of new forms of pricing, which do not fit well with our traditional approach to the market definition or with our traditional assessment of the likely effect of mergers on prices. Digital sellers have the ability not only to recognize previous buyers more effectively but also to collect, store and exploit information about this buyer’s past behaviour in order to display products and prices aimed at maximising the seller’s profits given the available buyer profile. Individualised pricing enabled by digitalisation raises issues relative to market definition. In a world where digital sales enable customised pricing, the market is much more liable to segmentation. As a result, one must pay close attention to whether the merging parties are or not “especially close competitors” not only in terms of products but also in terms of consumer information. The authors conclude that AI-based algorithms could be used to facilitate tacit collusion between rivals. Coordination between independent parties is easier to achieve and maintain if the parties can agree on a common price, can detect any deviation from this agreement quickly and precisely and can react to such deviations quickly. Establishing this type of infringement would likely require expertise not currently available to most competition authorities. The article identifies several mechanisms through which the emergence of digital conglomerates, and hence the approval of digital conglomerate mergers, can affect competition adversely. The platform’s “market power” now depends on its ability to retain users within its own ecology and to use this to restrict the supply of advertising, leading to higher prices for both advertising and the corresponding products. This ability is increased by any acquisition which helps populate this ecology. Traditional measures of concentration can therefore easily understate, or even miss entirely, this type of merger-specific increase in market power.

'Examining the Impact of Health Care Consolidation' Statement before the Committee on Energy and Commerce, Oversight and Investigations Subcommittee, U.S. House of Representatives

• The U.S. health care system is based on markets. The system will work only as well as the markets that underpin it. • These markets do not function as well as they could, or should. Prices are high and rising, there are incomprehensible and egregious pricing practices, quality is sub-optimal, and the sector is sluggish and unresponsive, in contrast to the innovation and dynamism which characterize much of the rest of our economy. • Lack of competition has a lot to do with these problems. • There has been a great deal of consolidation in health care. There have been 1,519 hospital mergers in the past twenty years, with 680 since 2010. The result is that many local areas are now dominated by one large, powerful health system, e.g., Boston (Partners), Pittsburgh (UPMC), and San Francisco (Sutter). • Insurance markets are also highly consolidated. The two largest insurers have 70 percent of the market or more in one-half of all local insurance markets. • Physician services markets have also become increasingly more concentrated. Two-thirds of specialist physician markets are highly concentrated, and 29 percent for primary care physicians. There have been a very large number of acquisitions of physician practices by hospitals, so much so that 33 percent of all physicians, and 44 percent of primary physicians are now employed by hospitals. • Extensive research evidence shows that consolidation between close competitors leads to substantial price increases for hospitals, insurers, and physicians, without offsetting gains in improved quality or enhanced efficiency. Further, recent evidence shows that mergers between hospitals not in the same geographic area can also lead to increases in price. Just as seriously, if not more, evidence shows that patient quality of care suffers from lack of competition. • This is causing serious harm to patients and to the health care system as a whole. • Policies are needed to support and promote competition in health care markets. This includes policies to strengthen choice and competition, and ending distortions that unintentionally incentivize consolidation. • These include: – Focus and strengthen antitrust enforcement. – End policies that unintentionally incentivize consolidation. – End policies that hamper new competitors and impede competition. – Promote transparency, so employers, policymakers, and consumers have access to information about health care costs and quality.

An Empirical Analysis of Export-Led Growth of Vietnam: Trade in Value Added (TiVA) Approach

This paper examines the long-run relationship between domestic value added exports and economic growth of Vietnam using ARDL bounds test of cointegration on annual data covering the period of 1995-2014.The bounds test establishes existence of both short-run and long-run relationship between exports and GDP of Vietnam and shows a substantial contribution of exports in the real GDP (0.73 percent for one percent changes in the domestic value added exports). The exports pattern of Vietnam portrays it following the footsteps of export-led growth model of Mexico, whereby it has turned itself into export production platforms for MNCs by suppressing the wages, rather than developing own indigenous industrial capacity. In such scenario, it seems challenging for Vietnam to sustain its export-led growth which it has achieved so far based on its cheap labour. With the rising living standards, ultimately the comparative advantages of cheap labour force would vanish in the future, which will cause a wave of assembly jobs to flow out of Vietnam. Moreover, two other low-cost countries in the region, Cambodia and Myanmar are likely to rise as close competitors of Vietnam in the low-cost assembly works in the near future. By that time, in case Vietnam fails to enter into higher value added activities, it will drag itself into the ‘middle income trap’. Therefore, the ‘assembly strategy’ shall be bonded with strategy to develop own indigenous industrial capacity, and national technological base. These will help Vietnam to upgrade its activities along value chains in forms of product upgrading, process upgrading, functional upgrading, and sectoral upgrading so that it can switch its role of ‘assembling agent’ to ‘indigenous producer’.

DeepCrystal: a deep learning framework for sequence-based protein crystallization prediction.

Protein structure determination has primarily been performed using X-ray crystallography. To overcome the expensive cost, high attrition rate and series of trial-and-error settings, many in-silico methods have been developed to predict crystallization propensities of proteins based on their sequences. However, the majority of these methods build their predictors by extracting features from protein sequences, which is computationally expensive and can explode the feature space. We propose DeepCrystal, a deep learning framework for sequence-based protein crystallization prediction. It uses deep learning to identify proteins which can produce diffraction-quality crystals without the need to manually engineer additional biochemical and structural features from sequence. Our model is based on convolutional neural networks, which can exploit frequently occurring k-mers and sets of k-mers from the protein sequences to distinguish proteins that will result in diffraction-quality crystals from those that will not. Our model surpasses previous sequence-based protein crystallization predictors in terms of recall, F-score, accuracy and Matthew's correlation coefficient (MCC) on three independent test sets. DeepCrystal achieves an average improvement of 1.4, 12.1% in recall, when compared to its closest competitors, Crysalis II and Crysf, respectively. In addition, DeepCrystal attains an average improvement of 2.1, 6.0% for F-score, 1.9, 3.9% for accuracy and 3.8, 7.0% for MCC w.r.t. Crysalis II and Crysf on independent test sets. The standalone source code and models are available at https://github.com/elbasir/DeepCrystal and a web-server is also available at https://deeplearning-protein.qcri.org. Supplementary data are available at Bioinformatics online.

Under the radar: How firms manage competitive uncertainty by appointing friends of other chief executive officers to their boards

Research SummaryIn this study, we reveal a previously unstudied type of board tie that may help firms manage competitive uncertainty. While firms face regulatory barriers to the use of board interlock ties as a strategy for reducing competition, we suggest that firms can circumvent these barriers by appointing the friends of competitors' chief executive officers (CEOs) to their boards. Our theoretical framework addresses the antecedents, maintenance, and performance consequences of such “board‐friendship ties” to rivals. Our theory explains (a) why firms form and maintain board‐friendship ties, where maintenance involves the reconstitution of broken ties and (b) how firms form and maintain these ties, by revealing the role of search firms in identifying the friends of rivals' CEOs. Empirical analyses of large‐sample, longitudinal survey and archival data provide substantial support for our theory. Managerial SummaryFirms can and do reduce competition and increase performance by appointing the friends of competitors' CEOs to their boards, and search firms (headhunters) play a key role in forming and maintaining these “board‐friendship” ties to competitors. While board interlock ties between close competitors are illegal and direct friendship ties between CEOs of competitors are relatively rare, board‐friendship ties are common, and yet largely unknown to antitrust regulators and external stakeholders.

Trajectory optimized NUFFT: Faster non-Cartesian MRI reconstruction through prior knowledge and parallel architectures.

PurposeThe non‐uniform fast Fourier transform (NUFFT) involves interpolation of non‐uniformly sampled Fourier data onto a Cartesian grid, an interpolation that is slowed by complex, non‐local data access patterns. A faster NUFFT would increase the clinical relevance of the plethora of advanced non‐Cartesian acquisition methods.MethodsHere we customize the NUFFT procedure for a radial trajectory and GPU architecture to eliminate the bottlenecks encountered when allowing for arbitrary trajectories and hardware. We call the result TRON, for TRajectory Optimized NUFFT. We benchmark the speed and accuracy TRON on a Shepp‐Logan phantom and on whole‐body continuous golden‐angle radial MRI.ResultsTRON was 6–30× faster than the closest competitor, depending on test data set, and was the most accurate code tested.ConclusionsSpecialization of the NUFFT algorithm for a particular trajectory yielded significant speed gains. TRON can be easily extended to other trajectories, such as spiral and PROPELLER. TRON can be downloaded at http://github.com/davidssmith/TRON.