İnşaat ihalelerinde dengesiz tekliflerin tespiti ve engellenmesi için bir model önerisi
Detection and prevention of unbalanced bids in construction projects
Yazar: FIRAT DOĞU AKIN
Danışman: DOÇ. DR. ATİLLA DAMCI
İstanbul Teknik Üniversitesi / Fen Bilimleri Enstitüsü / İnşaat Mühendisliği Ana Bilim Dalı / Yapı İşletmesi Bilim Dalı
Derece: Yüksek Lisans, 2019
Konu: İnşaat Mühendisliği = Civil Engineering

Özet:
İhale aşamasında sunulan tekliflerde, istekliler tarafından toplam proje fiyatı değiştirilmeden, nakit akışını iyileştirmek ve/veya kârı maksimize etmek amacıyla manipülasyon yapılmasına dengesiz teklif denir. Dengesiz teklifin varlığı hem işveren hem de istekliler açısından ciddi sorun olabilmektedir. Dengesiz teklif oluşturmak için matematiksel dengesiz adı altında erken/geç yüklemeye bağlı dengesiz teklif, miktar hatasına bağlı dengesiz teklif olmak üzere iki adet dengesiz teklif türü vardır. Matematiksel dengesiz teklife ek olarak ise, içeriden gelen gizli bilgiye bağlı dengesiz teklif bulunmaktadır.
Literatür içerisinde, dengesiz teklif üzerine birçok çalışma bulunmasına rağmen bu çalışmalar çoğunlukla isteklilerin kârlarını arttırmalarını amaçlayan optimizasyon problemlerini esas almaktadır. İşverenin çıkarlarını gözeten modellerin önerildiği çalışma sayısı ise kısıtlıdır. Dengesiz teklifin tespiti ve engellenmesi, adil bir rekabet ortamının oluşması ve sözleşme taraflarının öngörülemeyen maliyet artışlarından korunması açısından önem arz etmektedir. Sözleşme türlerine göre uygulanabilecek dengesiz teklif türü farklılık gösterebilmektedir. Götürü bedel anahtar teslim sözleşme türünde matematiksel olarak teklif dengesizleştirmesi olabilir. Birim fiyat usulü sözleşme türünde ise hem matematiksel hem de miktar hatasına bağlı olarak teklif dengesizleştirmesi olabilmektedir. Birim fiyat usulü sözleşmelerde, aktivitelere ait miktarların değişme olasılığı hem işveren hem de istekli açısından büyük bir risk oluşturmaktadır.  Bu tezin kapsamında birim fiyat usulü sözleşmelerde erken yüklemeye bağlı ve miktar hatasına bağlı dengesiz tekliflerin tespiti ve engellenmesini sağlayan bir model önerilmiştir. 
Model oluşturulurken literatür araştırmasında hem istekli bakış açısından oluşturulan modeller hem de işveren bakış açısından oluşturulan modellerin eksiklikleri belirlenerek çalışmada sunulan model geliştirilmiştir. Modelde yer alan işlemler, Microsoft Excel ile entegre edilmiş Visual Basic programlama dili kullanarak otomatikleştirilmiş ve kullanıcıları yönlendirecek şekilde düzenlenmiştir. Modelin geçerliliğini test etmek amacı ile model, 18 adet iş kalemini içeren bir proje için beş adet istekli tarafından sunulan tekliflerden oluşan örnek bir olay üzerinde uygulanmıştır. Sonuçlar incelendiğinde modelin hem ön yükleme yöntemi ile hem de miktar hatasına bağlı olarak dengesizleştirilen teklifleri tespit edebileceği görülmüştür. 
Sonuç bölümünde ise modelin geliştirilmesi için yapılabilecek eklentilerden bahsedilmiştir. Bu eklentilerin ilki, iş kalemi miktarlarının artış ve azalışlarının işveren ve istekli için doğurabileceği risklerin etkilerini azaltmak için istatistiksel analizlerden yararlanmaktır. İkincisi ise, toplam teklif içinde yüksek mali değere sahip aktivitelerin majör, düşük mali değere sahip aktivitelerin ise minör olarak adlandırılmaktadır. Modelin tekliflerdeki dengesizliği tespit ederken yararlanılan S eğrileri ise minör ve majör ayrımı gözetilerek oluşturulabilir. Böylece isteklilerin mali değeri yüksek aktivitelerde yaptıkları dengesizlikleri, mali değeri düşük aktiviteleri kullanarak sübvanse etmeleri engellenebilir.

Abstract:
The oldest, and most familiar project delivery system in the construction industry is Design-Bid-Build. There are various alternatives (e.g., Design-Build, Professional Construction Management, etc.) that can be used instead of Design-Bid-Build project delivery system. Nevertheless, it is still most commonly preferred project delivery system by a great number of owners, particularly in the public sector. 
This project delivery system mainly consists of five sequential stages: 1) pre-design stage, 2) design stage, 3) bid and award stage, 4) construction stage, and 5) post construction stage. In the bid and award stage, the owners aim to select the most appropriate contractors, who are capable of completing the project in budget, on time and at desired quality. Therefore, this phase plays a key role in the project success.
In a bid and award stage, a bidder may propose an unbalance bid to gain unfair competitive advantage against the other bidders. The idea of unbalanced bidding is not a new concept in the construction industry. Unbalanced bidding can be defined as manipulating the price of bid items without affecting the total bid price. 
There are two main methods of unbalancing a bid: mathematically (front-end loading) and materially (quantity error exploitation). Front-loading is a method that increases the unit prices of the activities scheduled to start in the early phases of the project while reducing the unit prices of the activities scheduled to start in the later phases. Thus, contractors can achieve better cash flows and higher profits while reducing their financial risks in the project.
End-loading is a method that is applied by increasing unit prices of activities in the later phases of the project. End-loading is a less-used method compared to front-loading. End-loading method is usually used for taking advantage of the escalation in countries with high inflation rates. Quantity error exploitation is a method applied by increasing the unit prices of the activities in which actual quantities are expected to exceed the estimated ones, while decreasing the unit prices of the activities that are overestimated. 
Unbalanced bids are not forbidden in the construction industry, but they are considered as unethical and risky strategy. Numerous researches have been conducted to address unbalanced bids. Most of these studies represent a contractor's viewpoint on bid unbalancing. In many of them, models have been developed to help contractors in maximizing their profits while submitting the lowest possible bid price. Even though the researchers ae focused on unbalanced bid from the contractors' perspective, there are various disadvantages of unbalanced bids for owners, too.
These disadvantages are, (1) not having a real competition environment, (2) owner has to pay in advance in unbalanced bid created by front-loading, (3) owner may pay more due to inflation in unbalanced bid created by end-loading, (4) failure of the lowest bid at the end of project. Therefore, owners' effort to detect and prevent unbalanced bids in advance may prevent its negative impacts on the overall project performance. However, in the literature, there are a limited number of models that have been developed to help owners to detect and prevent unbalanced bids. If an owner has a model to detect and prevent unbalanced bids, a fair competition environment can be achieved. 
Therefore, this study focused on developing a user-friendly model for the determination and prevention of unbalanced bids. After reviewing the existing models in the literature, advantages and shortcomings of the existing models are identified to assist the development of the model proposed in this study. The proposed model detects and prevents unbalanced bids which are caused by front loading and quantity error exploitation in unit price contracts. Unlike existing models, the developed model does not focus only on the unit prices or the schedule, but considers them simultaneously. These features, which overcome the shortcomings of the existing models, show the importance of the developed model.
The owner identifies the constraints according to the characteristics of the project and introduces them to the model. The inputs of the proposed model are the acceptable unit price range, early start times of activities, activity durations, estimated quantities of the activities, the unit prices of the bidders, early start times of activities and activity durations offered by the bidders. The outputs of the proposed model are schedules, S curves and cash flows of owners and bidders.
First, the proposed model identifies the lowest bid and sorts the bidders according to their bid prices. After identifying the lowest bidder, the unit prices of the lowest bid are compared with the unit prices taken from the database obtained from the previous projects. This comparison is made to determine whether the unit prices of the lowest bid are in acceptable range or not. If the unit prices are not in the acceptable range, then the model uses the lower and upper limits of the acceptable range to shift the unit prices into the acceptable range due to having an unbalanced bid created by quantity error exploitation. The model does not adjust the unit prices that fall into the acceptable range.
In the next step, the proposed model plots the S curves of the selected bidder. According to the characteristics of the project, the user determines one of the payment periods as a checkpoint. The lowest bidder's S curve is compared with the owner's S curve according to the chosen payment period. If there is a significant difference between the cash flows generated by the owner and the bidder during the chosen payment period, then the model detects that the bid is unbalanced by frontloading. In order to prevent the unbalanced bid, the proposed model offers to use the owner's schedule is used instead of the bidder's schedule. However, if the bid is still unbalanced, then it is rejected and the second lowest bid is considered for evaluation.
In order to demonstrate how the proposed model can be applied in a real-life problem, a case study is presented in this study. According to the findings, it was observed that the proposed model can detect and prevent bids that are unbalanced by frontloading and quantity error exploitation. As a result, the proposed model is of benefit to owners as it provides an approach for a bidding process that provides a fair competition environment, which may be considered as a significant contribution.
The model can be improved by adding new features in order to detect and prevent unbalanced bids more effectively. Statistical analysis tools can be used in identification of lower and upper limits of unit prices which are obtained from previous projects. In addition, major (a bid item's total price is equal to or greater than five percent of the construction cost estimated by the owner) and minor (a bid item's total price is less than five percent of the construction cost estimated by the owner) activities can be considered in evaluation of unit prices and S curves.