Contractor key competitiveness indicators: A China study

A proper method to assess contractor competitiveness is important both for assisting clients in the selection of proper contractors and for assisting contractors in the development of more competitive bidding strategies. Previous studies have identified various indicators for assessing contractor competitiveness, and several assessment methods have been introduced. Nevertheless, these studies are limited because they are unable to tell which indicators are more important in different market environments. This paper identifies the key competitiveness indicators �KCIs� for assessing contractor competitiveness in the Chinese construction market. An index value is used to indicate the relative significance of various competitiveness indicators based on which KCIs are identified. The data applied in this study are from a survey of the construction industry in mainland China. The research findings provide valuable information for both existing businesses and the construction professionals who plan to compete for construction works in the Chinese market. The study provides useful references for further studies that compare the KCIs used in the Chinese construction industry and those used in other construction industries.

Scoring rules and abnormally low bids criteria in construction tenders: a taxonomic review

In the global construction context, the best value or most economically advantageous tender is becoming a widespread approach for contractor selection, as an alternative to other traditional awarding criteria such as the lowest price. In these multi-attribute tenders, the owner or auctioneer solicits proposals containing both a price bid and additional technical features. Once the proposals are received, each bidder’s price bid is given an economic score according to a scoring rule, generally called an economic scoring formula (ESF) and a technical score according to pre-specified criteria. Eventually, the contract is awarded to the bidder with the highest weighted overall score (economic + technical). However, economic scoring formula selection by auctioneers is invariably and paradoxically a highly intuitive process in practice, involving few theoretical or empirical considerations, despite having been considered traditionally and mistakenly as objective, due to its mathematical nature. This paper provides a taxonomic classification of a wide variety of ESFs and abnormally low bids criteria (ALBC) gathered in several countries with different tendering approaches. Practical implications concern the optimal design of price scoring rules in construction contract tenders, as well as future analyses of the effects of the ESF and ALBC on competitive bidding behaviour.

Government initiatives to expand access to employer-based health insurance

Employer-based health insurance is declining at records rates, which leaves an increasing number of people without access to affordable health insurance. As a result, municipalities are experiencing financial difficulties to provide health care services for their growing uninsured population. In attempt to combat this issue, three health polices have emerged within the last ten years, called Living Wage with a health insurance provision, Pay or Play, and Health Care Preference. These policies are gaining popularity as civic leaders recognize their ability to promote a public health goal by leveraging the power of city and county contracts to include a health insurance component in the competitive bidding practice for government contracts. ^ This is the first paper to conduct a retrospective analysis on whether these three health policies have been able to increase access to employer-based health insurance and/or support the local health care safety net based on the experiences of six municipalities over a 5-year period from 2001-2006. Although there was variation between the effectiveness of the policies, all three demonstrated success in that a number of contractors extended existing health insurance to employees not previously covered and the increased cost of contracting for the local government was, on average, less than 1 percent of the total operating budget. ^

The EU power sector needs long-term price signals. CEPS Special Report No. 135/April 2016

By 2030, half of the EU’s electricity demand will be covered by renewables and will need to be accompanied by flexible conventional back-up resources. Due to the high upfront costs inherent to renewables and the progressively lower running times associated with back-up capacity, the cost of capital will have a proportionately greater impact on total costs than today. This report examines how electricity markets can be designed to provide long-term price signals, thereby reducing the cost of capital for these technologies and allowing for a more efficient transition. It finds that current market arrangements are unable to provide long-term price signals. To address this issue, we argue that a system for long-term contracts with a regulated counterparty could be implemented. A centralised system where capacity or energy or a combination of both is contracted, could be introduced for conventional and renewable capacity, based on a regional adequacy assessment and with a competitive bidding system in place to ensure cost-effectiveness. Member states face a number of legislative barriers while implementing these types of systems, however, which could be reduced by merging legislation and setting EU framework rules for the design of these contractual agreements.

Computer aided licence selection

A model of multiple criteria decision making is presented for selecting the “best” of a finite number of alternatives. Techniques of scoring the alternatives and weighting the criteria are combined with different evaluating procedures and amalgamated in an interactive algorithm. Application of this method for choosing the best tender in a competitive bidding is discussed and a case is presented in some detail.

Strategic bidding in electricity markets: an agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Strategic Bidding for Electricity Markets Negotiation Using Support Vector Machines

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which simulates the electricity markets environment. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated by being included in ALBidS and then compared with the application of an Artificial Neural Network, originating promising results. The proposed approach is tested and validated using real electricity markets data from MIBEL - Iberian market operator.

Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Modeling bidding competitiveness and position performance in multi-attribute construction auctions

Currently, multi-attribute auctions are becoming widespread awarding mechanisms for contracts in construction, and in these auctions, criteria other than price are taken into account for ranking bidder proposals. Therefore, being the lowest-price bidder is no longer a guarantee of being awarded, thus increasing the importance of measuring any bidder’s performance when not only the first position (lowest price) matters. Modeling position performance allows a tender manager to calculate the probability curves related to the more likely positions to be occupied by any bidder who enters a competitive auction irrespective of the actual number of future participating bidders. This paper details a practical methodology based on simple statistical calculations for modeling the performance of a single bidder or a group of bidders, constituting a useful resource for analyzing one’s own success while benchmarking potential bidding competitors.

Scoring rules and competitive behavior in best value construction auctions

This paper examines the extent to which engineers can influence the competitive behavior of bidders in Best Value or multi-attribute construction auctions, where both the (dollar) bid and technical non-price criteria are scored according to a scoring rule. From a sample of Spanish construction auctions with a variety of bid scoring rules, it is found that bidders are influenced by the auction rules in significant and predictable ways. The bid score weighting, bid scoring formula and abnormally low bid criterion are variables likely to influence the competitiveness of bidders in terms of both their aggressive/conservative bidding and concentration/dispersion of bids. Revealing the influence of the bid scoring rules and their magnitude on bidders’ competitive behavior opens the door for the engineer to condition bidder competitive behavior in such a way as to provide the balance needed to achieve the owner’s desired strategic outcomes.

Biased Random-key Genetic Algorithms For The Winner Determination Problem In Combinatorial Auctions.

Abstract In this paper, we address the problem of picking a subset of bids in a general combinatorial auction so as to maximize the overall profit using the first-price model. This winner determination problem assumes that a single bidding round is held to determine both the winners and prices to be paid. We introduce six variants of biased random-key genetic algorithms for this problem. Three of them use a novel initialization technique that makes use of solutions of intermediate linear programming relaxations of an exact mixed integer-linear programming model as initial chromosomes of the population. An experimental evaluation compares the effectiveness of the proposed algorithms with the standard mixed linear integer programming formulation, a specialized exact algorithm, and the best-performing heuristics proposed for this problem. The proposed algorithms are competitive and offer strong results, mainly for large-scale auctions.

Tracking 10-year competitive winning performance of judo athletes across age groups

Little information is available concerning early specialization and competitive success in judo across the early training years. Thus, the present objective was to verify the stability of individual competitive performance of a state-level championship for judo athletes who had been previously successful. For this, 406 athletes from six age groups (9 to 20+ years old) of each sex were followed for 10 years. Using recorded data from the Sao Paulo State Judo Federation beginning in 1999, the scores and standings for these judo players were analyzed. The proportion of medal winners during this period was not constant, differing from the grand mean in all groups of both 204 males and 202 females. At the end of this period, only 7% of the male and 5% of the female athletes had maintained their competitive levels. Successful competitive performance in early judo competition was not associated with success later in adulthood.

Competitive artistic gymnastics: reflections about gymnasts` development

The current study is a piece from the original project entitled ""Diagnosis of the Developing Program of Artistic Gymnastics in Brazil"". Among other issues discussed in this main project, our objective was to investigate the development of the gymnast who are entering the intensive training and are potential to be representative to national teams. We interviewed 46 coaches from 29 sports institutions in Brazil. Regarding methodology, we used a semi-structured interview and for data treatment we adopted the content analysis proposed by Bardin (2004). We could evidence that coaches have concern regarding many aspects of the children development, and have been trying to equate sports demands with gymnasts characteristics and needs.

Subtype-selective noncompetitive or competitive inhibition of human alpha(1)-adrenergic receptors by rho-TIA

The 19-amino acid conopeptide (rho-TIA) was shown previously to antagonize noncompetitively alpha(1B)-adrenergic receptors (ARs). Because this is the first peptide ligand for these receptors, we compared its interactions with the three recombinant human alpha(1)-AR subtypes (alpha(1A), alpha(1B), and alpha(1D)). Radioligand binding assays showed that rho-TIA was 10-fold selective for human alpha(1B)- over alpha(1A)- and alpha(1D)-ARs. As observed with hamster alpha(1B)-ARs, rho-TIA decreased the number of binding sites (B-max) for human alpha(1B)-ARs without changing affinity (K-D), and this inhibition was unaffected by the length of incubation but was reversed by washing. However, rho-TIA had opposite effects at human alpha(1A)-ARs and alpha(1D)-ARs, decreasing KD without changing Bmax, suggesting it acts competitively at these subtypes. rho-TIA reduced maximal NE-stimulated [H-3] inositol phosphate formation in HEK293 cells expressing human alpha(1B)-ARs but competitively inhibited responses in cells expressing alpha(1A)- or alpha(1D)-ARs. Truncation mutants showed that the amino-terminal domains of alpha(1B)- or alpha(1D)-ARs are not involved in interaction with rho-TIA. Alanine-scanning mutagenesis of rho-TIA showed F18A had an increased selectivity for alpha(1B)-ARs, and F18N also increased subtype selectivity. I8A had a slightly reduced potency at alpha(1B)-ARs and was found to be a competitive, rather than noncompetitive, inhibitor in both radioligand and functional assays. Thus rho-TIA noncompetitively inhibits alpha(1B)-ARs but competitively inhibits the other two subtypes, and this selectivity can be increased by mutation. These differential interactions do not involve the receptor amino termini and are not because of the charged nature of the peptide, and isoleucine 8 is critical for its noncompetitive inhibition at alpha(1B)-ARs.

Effects of carbohydrate supplementation on competitive runners undergoing overload training followed by a session of intermittent exercise

This study evaluated the effects of a micro cycle of overload training (1st-8th day) on metabolic and hormonal responses in male runners with or without carbohydrate supplementation and investigated the cumulative effects of this period on a session of intermittent high-intensity running and maximum-performance-test (9th day). The participants were 24 male runners divided into two groups, receiving 61% of their energy intake as CHO (carbohydrate-group) and 54% in the control-group (CON). The testosterone was higher for the CHO than the CON group after the overload training (694.0 +/- A 54.6 vs. CON 610.8 +/- A 47.9 pmol/l). On the ninth day participants performed 10 x 800 m at mean 3 km velocity. An all-out 1000 m running was performed before and after the 10 x 800 m. Before, during, and after this protocol, the runners received solution containing CHO or the CON equivalent. The performance on 800 m series did not differ in either group between the first and last series of 800 m, but for the all-out 1000 m test the performance decrement was lower for CHO group (5.3 +/- A 1.0 vs. 10.6 +/- A 1.3%). The cortisol concentrations were lower in the CHO group in relation to CON group (22.4 +/- A 0.9 vs. 27.6 +/- A 1.4 pmol/l) and the IGF1/IGFBP3 ratio increased 12.7% in the CHO group. During recovery, blood glucose concentrations remained higher in the CHO group in comparison with the CON group. It was concluded that CHO supplementation possibly attenuated the suppression of the hypothalamic-pituitary-gonadal axis and resulted in less catabolic stress, and thus improved running performance.