Information communication technologies and distance education in Sri Lanka: a case study of two universities

Sri Lanka's participation rates in higher education are low and have risen only slightly in the last few decades; the number of places for higher education in the state university system only caters for around 3% of the university entrant age cohort. The literature reveals that the highly competitive global knowledge economy increasingly favours workers with high levels of education who are also lifelong learners. This lack of access to higher education for a sizable proportion of the labour force is identified as a severe impediment to Sri Lanka‟s competitiveness in the global knowledge economy. The literature also suggests that Information and Communication Technologies are increasingly relied upon in many contexts in order to deliver flexible learning, to cater especially for the needs of lifelong learners in today‟s higher educational landscape. The government of Sri Lanka invested heavily in ICTs for distance education during the period 2003-2009 in a bid to increase access to higher education; but there has been little research into the impact of this. To address this lack, this study investigated the impact of ICTs on distance education in Sri Lanka with respect to increasing access to higher education. In order to achieve this aim, the research focused on Sri Lanka‟s effort from three perspectives: policy perspective, implementation perspective and user perspective. A multiple case study research using an ethnographic approach was conducted to observe Orange Valley University‟s and Yellow Fields University‟s (pseudonymous) implementation of distance education programmes using questionnaires, qualitative interviewing and document analysis. In total, data for the analysis was collected from 129 questionnaires, 33 individual interviews and 2 group interviews. The research revealed that ICTs have indeed increased opportunities for higher education; but mainly for people of affluent families from the Western Province. Issues identified were categorized under the themes: quality assurance, location, language, digital literacies and access to resources. Recommendations were offered to tackle the identified issues in accordance with the study findings. The study also revealed the strong presence of a multifaceted digital divide in the country. In conclusion, this research has shown that iii although ICT-enabled distance education has the potential to increase access to higher education the present implementation of the system in Sri Lanka has been less than successful.

The probability of sale and price premiums in withdrawn auctioned properties

This paper examines the impact of the auction process of residential properties that whilst unsuccessful at auction sold subsequently. The empirical analysis considers both the probability of sale and the premium of the subsequent sale price over the guide price, reserve and opening bid. The findings highlight that the final achieved sale price is influenced by key price variables revealed both prior to and during the auction itself. Factors such as auction participation, the number of individual bidders and the number of bids are significant in a number of the alternative specifications.

Corruption and individual ethics: insights from a public procurement auction

This article proposes an auction model where two firms compete for obtaining the license for a public project and an auctioneer acting as a public official representing the political power, decides the winner of the contest. Players as firms face a social dilemma in the sense that the higher is the bribe offered, the higher would be the willingness of a pure monetary maximizer public official to give her the license. However, it implies inducing a cost of reducing all players’ payoffs as far as our model includes an endogenous externality, which depends on bribe. All players’ payoffs decrease with the bribe (and increase with higher quality). We find that the presence of bribe aversion in either the officials’ or the firms’ utility function shifts equilibrium towards more pro-social behavior. When the quality and bribe-bid strategy space is discrete, multiple equilibria emerge including more pro-social bids than would be predicted under a continuous strategy space.

The probability of sale and price premiums in withdrawn auctioned properties

This paper examines the impact of the auction process of residential properties that whilst unsuccessful at auction sold subsequently. The empirical analysis considers both the probability of sale and the premium of the subsequent sale price over the guide price, reserve and opening bid. The findings highlight that the final achieved sale price is influenced by key price variables revealed both prior to and during the auction itself. Factors such as auction participation, the number of individual bidders and the number of bids are significant in a number of the alternative specifications.

Big Data and ecosystem research programmes

The size and complexity of data sets generated within ecosystem-level programmes merits their capture, curation, storage and analysis, synthesis and visualisation using Big Data approaches. This review looks at previous attempts to organise and analyse such data through the International Biological Programme and draws on the mistakes made and the lessons learned for effective Big Data approaches to current Research Councils United Kingdom (RCUK) ecosystem-level programmes, using Biodiversity and Ecosystem Service Sustainability (BESS) and Environmental Virtual Observatory Pilot (EVOp) as exemplars. The challenges raised by such data are identified, explored and suggestions are made for the two major issues of extending analyses across different spatio-temporal scales and for the effective integration of quantitative and qualitative data.

Mathematical relationships between scoring parameters in capped tendering

Mathematical relationships between Scoring Parameters can be used in Economic Scoring Formulas (ESF) in tendering to distribute the score among bidders in the economic part of a proposal. Each contracting authority must set an ESF when publishing tender specifications and the strategy of each bidder will differ depending on the ESF selected and the weight of the overall proposal scoring. This paper introduces the various mathematical relationships and density distributions that describe and inter-relate not only the main Scoring Parameters but the main Forecasting Parameters in any capped tender (those whose price is upper-limited). Forecasting Parameters, as variables that can be known in advance before the deadline of a tender is reached, together with Scoring Parameters constitute the basis of a future Bid Tender Forecasting Model.

Detecting abnormal and collusive bids in capped tendering

Recent developments in the area of Bid Tender Forecasting have enabled bidders to implement new types of easy-to-use tools for increasing their chances of winning contracts. Although these new tools (such as iso-Score Curve Graphs, Scoring Probability Graphs, and Position Probability Graphs) are designed for bidders in capped tendering (tenders with an upper price limit), some of their principles can also be applied by a Contracting Authority to detect which bidders do not follow a standard pattern, that is, their bids are extremely high or low. Since a collusive bid generally needs to be sufficiently high or low to make an impact on the bid distribution, any person in charge of supervising capped tenders can be alerted to any bidder that might be involved in a cartel after identifying the same abnormal behavior in a series of tenders through simple calculations and a new type of graph.

Estimating future bidding performance of competitor bidders in capped tenders

Research in Bid Tender Forecasting Models (BTFM) has been in progress since the 1950s. None of the developed models were easy-to-use tools for effective use by bidding practitioners because the advanced mathematical apparatus and massive data inputs required. This scenario began to change in 2012 with the development of the Smartbid BTFM, a quite simple model that presents a series of graphs that enables any project manager to study competitors using a relatively short historical tender dataset. However, despite the advantages of this new model, so far, it is still necessary to study all the auction participants as an indivisible group; that is, the original BTFM was not devised for analyzing the behavior of a single bidding competitor or a subgroup of them. The present paper tries to solve that flaw and presents a stand-alone methodology useful for estimating future competitors’ bidding behaviors separately.

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.

Analysis of the distribution of the number of bidders in construction contract auctions

The number of bidders, N, involved in a construction procurement auction is known to have an important effect on the value of the lowest bid and the mark-up applied by bidders. In practice, for example, it is important for a bidder to have a good estimate of N when bidding for a current contract. One approach, instigated by Friedman in 1956, is to make such an estimate by statistical analysis and modelling. Since then, however, finding a suitable model for N has been an enduring problem for researchers and, despite intensive research activity in the subsequent 30 years, little progress has been made, due principally to the absence of new ideas and perspectives. The debate is resumed by checking old assumptions, providing new evidence relating to concomitant variables and proposing a new model. In doing this and in order to ensure universality, a novel approach is developed and tested by using a unique set of 12 construction tender databases from four continents. This shows the new model provides a significant advancement on previous versions. Several new research questions are also posed and other approaches identified for future study.

Improving the estimation of probability of bidder participation in procurement auctions

Anticipating the number and identity of bidders has significant influence in many theoretical results of the auction itself and bidders' bidding behaviour. This is because when a bidder knows in advance which specific bidders are likely competitors, this knowledge gives a company a head start when setting the bid price. However, despite these competitive implications, most previous studies have focused almost entirely on forecasting the number of bidders and only a few authors have dealt with the identity dimension qualitatively. Using a case study with immediate real-life applications, this paper develops a method for estimating every potential bidder's probability of participating in a future auction as a function of the tender economic size removing the bias caused by the contract size opportunities distribution. This way, a bidder or auctioner will be able to estimate the likelihood of a specific group of key, previously identified bidders in a future tender.

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.