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The purpose of this study is to determine the relationship between the geographic market size of businesses and the competitiveness of being able to bid at low prices.

The design of this study is based on a natural experiment approach. Firstly, after controlling for the firm size and other factors, the author sees that firms participating in bidding in a large region are more competitive to bid at lower prices than firms doing business in a smaller region. The author then tests for causality in a natural experiment of the exogenous event.

The results show that firms participating in the bidding process in a large area are more competitive to bid at lower prices than firms doing business in a small area. This is tested in a natural experiment, and the result is that they are more competitive because they do business in a larger area.

The practical implication is that, when aiming for competitiveness, it is most important to consider the nature of the business and to see the essence of the business, for example, that networks are important in the construction industry, and that doing business over a wide area is the way to become competitive.

The social implications are that to make firms more competitive, we must look at the characteristics of the industry and come up with policies that fit the reality, such as encouraging them to do business in a wide area.

The originality of this study is that this study viewed competitiveness as being able to bid low prices for public procurement and found that doing business in a wide area is competitive. Furthermore, the causal effect of the study was to test the fact that doing business in a wide area does not mean doing business in a wide area because it is competitive, but that doing business in a wide area creates a competitive advantage.

The aim is to examine the importance small and medium-sized enterprises (SMEs) see in different network partners regarding successful tendering in public procurement, and whether this perception predicts the number of joint bids and wins.

The data were collected by an electronic questionnaire which was sent to the registered users of the leading electronic platform for public procurement in Finland. The data were analysed with statistical methods.

The findings suggest that a favourable perception of the importance of horizontal networks in public procurement is associated with a larger number of joint bids and better success in joint bidding. However, the results do not establish a positive correlation between vertical networks and consortium bidding.

The data were collected from a single EU country. Since the criteria for bidding consortia may vary between countries, different results might have been achieved from other countries.

SMEs should be encouraged to form bidding consortia and acquire related experience. Policymakers should minimise barriers to consortium bidding, e.g. by offering more information. They should also assess the merits of joint bidding because they rarely encourage SMEs to bid as a consortium.

Consortium bidding is a way of enhancing SMEs’ possibilities to participate in public tender contests, even in large contracts.

While consortium bidding has been recognised to enhance SMEs’ possibilities of participating in public procurement, there is limited research into how SMEs’ network collaborations relate to bidding as a consortium.

Firms embedded in networks of relations are theorized through Gnyawali and Madhavan’s (2001) (G&M) structural embeddedness model to gain competitive advantage from topological characteristics. Empirical studies to support their theory have never been executed in full. Our study provided a full empirical test of their model in a digital trading network to achieve a higher degree of certainty that those network structural characteristics can have a major impact on the degree to which certain firms lead to competitiveness in a digital trading network environment.

To examine how firms respond in competitive situations, we chose the hyper-active digital trading network, eBay as our empirical context. We used eBay auction data to analyze how the network characteristics of eBay resellers impact their competitive behaviors.

Our study found strong support for the G&M model of competitiveness. We offer explanations for where support was not as strong as the Gynawali and Madavan theory proposes.

Our research is limited by our chosen context and findings in support of part of G&M model. Future studies in other digital contexts are needed to enhance the modeling of network topologies and further study the impacts of network density and structural autonomy on competitive action.

Our study suggests that managers proceed cautiously in forming partnerships, weighing circumstances where the firm can find itself with increased information power and avoiding, to the greatest extent possible, situations where the playing field is roughly equal.

Theory-making in this domain has begun as well as initial empirical testing. Much more needs to be accomplished, though, before embeddedness modeling can be thought of as being well established.

The G& M Model of competitiveness is an SNA explanation of why some competitive units succeed and others do not. Our study is the first, full blown empirical analysis of the theory.

In this paper, the main focus is on supply and demand auction systems with resource pooling in modern supply chain from a theoretical modeling perspective. The supply and demand auction systems in modern supply chains among manufacturers and suppliers serve as information sharing mechanisms. The purpose of this paper is to match the supply and demand such that a modern supply chain can achieve incentive compatibility and economic efficiency. The authors design such a supply and demand auction system that can integrate resources to efficiently match the supply and demand.

The authors propose three theoretic models of modern supply chain auctions with resource pooling according to the Vickrey auction principle. They are supply auction model with demand resource pooling, demand auction model with supply resource pooling, and double auction model with demand and supply resource pooling. For the proposed auction models, the authors present three corresponding algorithms to allocate resources in the auction process by linear programming, and study the incentive compatibility and define the Walrasian equilibriums for the proposed auction models. The authors show that the solutions of the proposed algorithms are Walrasian equilibriums.

By introducing the auction mechanism, the authors aim to realize the following three functions. First is price mining: auction is an open mechanism with multiple participants. Everyone has his own utility and purchasing ability. So, the final price reflects the market value of the auction. Second is dynamic modern supply chain construction: through auction, firm can find appropriate partner efficiently. Third is resources integration: in business practices, especially in modern supply chain auctions, auctioneers can integrate resources and ally buyers or sellers to gain more efficiency in auctions.

In the paper, the authors propose three theoretic models and corresponding algorithms of modern supply chain auctions with resource pooling according using the Vickrey auction principle, which achieves three functions: price mining, dynamic modern supply chain construction and resources integrating. Besides, these proposed models are much closer to practical settings and may have potential applications in modern supply chain management.

The variance between the winning bid and the owner's estimated cost (OEC) is one of the construction management risks in the pre-tendering phase. The study aims to enhance the quality of the owner's estimation for predicting precisely the contract cost at the pre-tendering phase and avoiding future issues that arise through the construction phase.

This paper integrated artificial neural networks (ANN), deep neural networks (DNN) and time series (TS) techniques to estimate the ratio of a low bid to the OEC (R) for different size contracts and three types of contracts (building, electric and mechanic) accurately based on 94 contracts from King Saud University. The ANN and DNN models were evaluated using mean absolute percentage error (MAPE), mean sum square error (MSSE) and root mean sums square error (RMSSE).

The main finding is that the ANN provides high accuracy with MAPE, MSSE and RMSSE a 2.94%, 0.0015 and 0.039, respectively. The DNN's precision was high, with an RMSSE of 0.15 on average.

The owner and consultant are expected to use the study's findings to create more accuracy of the owner's estimate and decrease the difference between the owner's estimate and the lowest submitted offer for better decision-making.

This study fills the knowledge gap by developing an ANN model to handle missing TS data and forecasting the difference between a low bid and an OEC at the pre-tendering phase.

For a public project leader charged with a construction project, it can be crucial to meet the budget, while maximizing the qualities within a construction project. A method to achieve this is to use the “opposite design build” procurement method, in which the price is fixed and the contractors compete on adding a wide range of qualities to the project. However, such procurement approaches are rare, and it is difficult to find models on how to implement such an approach.

This study firstly looks at the literature on design-build, quality-only as the main selection criterion and to some degree on constructors’ bidding behaviour. Secondly, it explains a model for a design-build, quality-only procurement designed within the public tendering legislations. Thirdly, it investigates the outcome of the model applied to a specific case in Norway.

There seems to be a research gap within literature and cases on design-build, quality-only selection with a fixed price. The developed model allowed for negotiations, which led to more comparable and improved bids. In the investigated case, and the client was able to implement more qualities in the project than expected within the budget.

The researcher was himself partly involved in the process as an advisor.

The developed method is relatively simple and might readily be applied by any client to maximise a project’s qualities within a given fixed price.

The long-term value should be to widen the range of useful procurement methods.

Forests support human livelihoods and mitigate against climate change, yet they are at a risk of irreversible loss due to high degradation rates. The success of forest conservation mechanisms depends on involvement and support by forest dependent communities. In this paper, the authors assess forest dependent household's willingness to pay (WTP) labour or cash for a conservation programme seeking to restore degraded forestland in Mount Elgon Forest, Kenya.

Data were collected from 919 households in Mt Elgon forest reserve, Kenya. A double bounded contingent valuation approach was used to examine households' WTP and an ordered probit model to estimate the determinants of WTP.

The findings of the study show a higher WTP for conservation through labour days (12 days/month, equivalent to 1800 KES/month) compared to cash (KES 450/month). Forest dependence has a significant influence on households' willingness to support conservation activities. A higher WTP was observed amongst households with higher vulnerability (high shocks value, low asset value and those in the poorest wealth categories) implying that they are more willing to contribute for forest conservation.

While emerging literature on WTP for forest conservation is growing, few studies have paid attention on the influence of forest dependence on WTP for forest conservation. There are limited studies on use of in-kind contribution as a payment vehicle for WTP. The study's findings show a high WTP in form of labour suggesting the importance of embracing in-kind contribution as a mechanism of supporting forest conservation in contexts of developing countries.

This paper aims to investigate the impact of day trading on market quality on the Taiwan stock market with the implementation of a unique policy change. This paper examines 396 listed stocks from June 2015 to October 2016, a period when the stock market in Taiwan officially approved selected stocks for day trading for all investors. Within the sample period, the empirical findings show that day trading increases the bid–ask spread, price depth and stock volatility, indicating that day trading activities not only cause higher transaction costs and trading risk but also raise the market’s ability to absorb price impact. This paper considers two-stage regression and tests the exogenous shock because of further relaxation for day trading to deal with the possible endogenous problem and the main findings remain consistent. Since early 2014, the Taiwan stock market has been experiencing a distinct growth in trading volume after unwinding the day trading; however, the results show that the impacts of stock day trading on market quality are not all positive.

The estimation of market value of intangible benefits of afforestation has always been a challenging task, and the contingent valuation method is a popular method used in environmental assessment. The NTPC set up a coal-based power plant in Korba, India and planted 1.6 million trees on 19% of the project area.

The individual's mean and median willingness to pay (WTP) for four intangible benefits, namely, pollution control (PC), improvement in underground water level (IUGWL), soil conservation and remediation (SCR) in addition to total WTP from the afforestation program of NTPC were estimated using a customized procedure for logit model based upon respondent's age, education, occupation, income and bid amount asked to pay. Stratified multistage random sampling has been used to select the respondents.

The procedure increases the number of respondents who are willing to pay as compared to conventional CVM. The finding of the study shows that the highest WTP was observed for PC (Rs. 462.84 per month per household) followed by SCR and IUGWL, whereas for total WTP it was Rs. 972.60.

The proposed customized procedure and the results thereof would be useful in improving the WTP estimates for other similar studies in order to conserve the environment.

The purpose of this study is to investigate how procurement strategies may be designed to facilitate exploration and exploitation in construction projects.

This paper is based on a literature review of organizational research and construction management literature together with a brief interview study of Swedish clients and contractors.

The theoretical and empirical findings propose that small and simple projects with low uncertainty and scarce resources may focus on exploitation to enhance short-term efficiency through traditional procurement strategies including delivery systems that separate the actors and their activities (i.e. pure design-build- or design-bid-build-contracts), fixed price payment and price focus in bid evaluation. Large complex projects with high uncertainty and customization benefit from combining exploration and exploitation to enhance sustainable performance. This requires collaborative procurement strategies including joint specification through early contractor involvement, cost reimbursement coupled with incentive-based payment, bid evaluation based on multiple criteria and collaborative tools and activities in partnering arrangements.

This paper contributes to organizational learning literature by pinpointing the need for integrating procurement strategies that enhance combination of exploration and exploitation. The main contribution to the construction management literature involves the investigation of how procurement strategies may affect exploration and exploitation, as identified and articulated in the propositions developed in this paper.

From a practical perspective, the findings highlight the importance of tailoring procurement strategies to project characteristics to enhance a suitable balance between exploration and exploitation in construction projects.

The explicit focus on the operational project-level is uncommon but relevant in organizational learning literature.