Türk inşaat firmalarının teklif verme sürecinde karar vermelerini etkileyen faktörlerin analizi
Başlık çevirisi mevcut değil.
- Tez No: 46167
- Danışmanlar: PROF.DR. YILDIZ SEY
- Tez Türü: Doktora
- Konular: Mimarlık, Architecture
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 1995
- Dil: Türkçe
- Üniversite: İstanbul Teknik Üniversitesi
- Enstitü: Fen Bilimleri Enstitüsü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 194
Özet
Tezin amacı; yüklenici inşaat işletmelerin ihale süreçlerinde, işe girip/girmeme ve teklif fiyatı belirleme aşamalarındaki kararlarını etkileyen faktörlerin bir alan çalışmasıyla analiz edilmesi, dolayısıyla ilgili aşamalarda yüklenicilerin karar verme davranışlarının incelenmesidir. Tez; yapılan alan araştırması ve araştırma kapsamında yer alan konuların tanıtılması ile ilgili bölümlerden oluşur. Problem çevresini tanıtan ve tanımlayan bölümler aynı zamanda yapılan araştırmayı ve bulguların yorumlarını besleyici niteliktedir. İlk bölüm giriş bölümü olup; tez kapsamında ele alınan problemi tanıtır, kapsamını ve sınırlamalarını belirler. İkinci bölüm; genel olarak inşaat firmalarının tanımlanmasına yöneliktir.Bu bölümde özellikle, inşaat endüstrisinde yer alan firmaların amaçları ve davranış özellikleri üzerinde durulmuştur. Üçüncü bölüm; tezin bir karar verme problemini içermesi bakımından, karar verme konusunun özellikle inşaat işletmeleri açısından teorik olarak anlatılmasını hedefler. Dördüncü bölümde; problemin yer aldığı ihale süreci tanıtılarak, bu süreçte yapılması gerekli çalışmalar kontrol listeleri haline getirilmiş ve fiyatlandırma konularında yapılan teorik modellerin kapsamı tanıtılmıştır. Beşinci bölüm; yapılan araştırmanın adımlarını içerir. Araştırma, 44 yüklenici firmayı kapsayan ve temel olarak, ilk paragrafta sözü edilen karar konularına ilişkin 34 faktörün incelenmesine yönelik olarak hazırlanmış soru kağıdının uygulandığı bir alan çalışmasıdır. Bu bölümde araştırmanın metodu anlatılmış, faktörler firma büyüklüğü de ele alınarak analiz edilmiş ve sonuç olarak büyüklüklerine göre firmaların ihale süreçlerindeki karar verme davranışları yorumlanmıştır. Sonuç bölümü; yurt dışında aynı konuda yapılmış alan çalışmalarını tanıtır ve bu araştırmaların sonuçlarım tez kapsamında yapılan araştırmanın sonuçlarıyla karşılaştırarak genel bir değerlendirme yapar.
Özet (Çeviri)
Conventional bidding strategy models, based on the works of Friedman and Gates, attempt to answer the question of how the decision should be made. The prescriptions suggested by these models are based on differing sets of assumptions regarding the context of the problem. They are different, sometimes contradictory, and do not take into consideration how bidding is done by the construction industry. These models, as presented in the literature, tend to ignore the question:“How are bid decisions made?”The present research indicates that no strategy can be meaningful and hence useful unless input from the construction industry is incorporated in the model.1 The main objectives of this study are; 1. To identify the factors influencing Turkish contractors' decision to bid for a project in consideration of firm size. 2. To identify the factors influencing Turkish contractors' decision to set the markup size for pricing a job in consideration of firm size. 3. To evaluate contractor behaviour in bid/no-bid and markup decisions. Objectives of the study necessitated the identification of the various factors that influence the decision related to decision to bid and the appropriate mark-up size. Previous study is the base of this study.2 Additionally, a thorough review of the literature was conducted for the purpose of studying the available bidding models. The previous study and the intensive literature review resulted in identifying 34 factors affecting a contractor's decision on bid/no-bid and proper mark-up size. 1 Source: Ahmad, I. and Minkarah, I. (1988) Questionnaire survey on bidding in construction, ASCE Journal of Management in Engineering Divisions, 4, (3), July, p.229. 2 Previos study: Dikbaş, A. (1988) The Tendering Process Within the Contractor Organizations and The Factors Affecting Tender Decision, Unpublished master thesis, Istanbul Technical University, Faculty of Architecture. XIIn general, the assumption is made that different internal and external factors affect a contractor's decisions. The internal factors are those related to the contractor's organisation with all its assets, experience and strength. The external factors are those related to the owner and his representative, the competitors, and finally the project and it's related conditions. These parties interact in a changing social, economical, technological and political climate. The data collected should reflect the aggregate effect of the different parties on the contractor's decisions. The necessary data were collected primarily from the classified construction contractors in Turkey. The method used for the collection of the information is written questionnaire. The questionnaire that was originally prepared for a study done Istanbul Technical University by Dikbaş sets the foundation for the development of the written questionnaire.3 This questionnaire was modified to suit the bidding decision environment by taking a feedback from literature. Some factors were added and others removed depending on which were deemed appropriate and applicable. The questionnaire is divided into five parts. The first part contains questions about the firm, its type, its capacity, and other biographical data. The second part is a check-list contains questions about tendering process of the firm. The third part of the questionnaire contains questions about the importance level of 34 potential factors affecting the decision on bid or no bid. The fourth part of the questionnaire also contains same questions about the importance level of 34 potential factors affecting the decision on the size of mark-up to be assigned. In that parts, a scale from '0' to '6' is used to measure the level of effect of each factor on the underlying decisions, where '0' means no effect and '6' means high effect. The respondents were asked to check a number on the scale which reflects their assessment regarding the different factors. The last part of the questionnaire contains questions about the critical points of bidding process and additional factors that reflect the firm's policy regarding bidding decision making. It was discussed face to face to a randomly selected sample contract manager of contractors by using the questionnaire. The sample was selected from the 322 classified contractors list which is published by several commerce and associations4. 3 Ibid.,105-108. 4 This study contains results based on the response obtained from 110 of the general contractors in the list were obtained from ICCO (Istanbul Chamber of Commerce), TIM- SE (Trade Union of Turkish Contractors) and Turkish Contractors Association. MlThe size of the sample was determined using the statistical formula5, and random numbers used to select the contractors from the list. The analysis of the data was through the use SPSS for Windows 5.0-6.0 and Excell 4.0 that are packages available on the PC. The data collected from the survey was coded and entered into the software that calculated all required statistics, such as the mean, the standard deviation, and the correlation coefficients. The data reduction technique (factor) and classify technique (discriminant) were employed in major portion of the data analysis. When deciding on the bid or no-bid and mark-up size, a contractor realises that the right size is a function of many factors. Table 1 embodies 34 factors that are thought to influence the bid/no-bid, and the percent mark-up decisions. The factors are ranked in accordance to their importance to Turkish contractors. The importance of each factor was measured using the following formula: Importance Index ='L(aX) x 100/6 where: a: constant expressing the weight given to each response. The weight ranges from '0' to '6' where '0' is the no important and '6' is the most important; X=n/N; n=the frequency of the response; N= total number of responses. The results indicate that when deciding on the mark-up size for a project, a contractor looks into the project characteristics, economic situation, company and site characteristics, and bidding situation in descending order of importance. It is worth noting that some factors are considered to be very important in one decision stage but not in the other, while some factors are considered important in both decision stage. For instance, type and size of job, current work load, degree of detail contract and project, competitors, bid-bond requirement and tender committee almost equally important for both bid/no-bid and percent-markup decision stages. On the other hand, owner, nearness to other jobs' site, inactive labor of the firm, time given to bid, prestige of the job and project delivery system were found to be more important for the bid/no-bid decision than for the percent- markup decision. Factors such as advance payment, equipment requirement, subcontracted amount, technology, site conditions and security of site location were considered to be more important for percent-markup decision than bid/no- bid decisions. 5 The formula (n=n'/(l+n'/N))'is devoloped by Kish. Substituting the variables a sample size of «=75 is introduced In this study a response rate %70 was assumed, and thus a total of 110 questionnaires were applicated to firms' contract managers. But a total of 44 questionnaires were received due to missing values. XMAfter this initial discussion, importance indices and rank order of the factors were determined according to categorization of contractors. Table 1. Importance indices and rank order of the factors affecting bid/no-bid and percent markup decisions. XIVThe objective of this study requires the categorization of contractors into different sizes. The number of permanent employees, the value of equipment owned and the business volume (current and past 5 years) were attributes considered for classifying the contractors. First, all size measurement were listed according to its values and, it was noted that the categorization of a contractor changes as a different classifying measure is utilized. All size measurement analyzed for an appropriate classification by using correlation technique. Finally, it decided to use business volume (as average of current and past 5 years) as the basis for categorization. This suggests the categorization of contractors into three groups. The first involves 13 contractors with an average business volume less than $ 10 million (US). This group is designated as small. The second, termed medium, embodies 14 contractors with an average business volume less than $ 100 million (US), but greater than or equal to $ 10 million (US). The third category, designated as large, contains 17 contractors with an average business volume greater or equal to $ 100 million (US). Table 2 presents the calculated importance indices and the associated rank orders of the factors affecting bid/no-bid decisions for each contractor group. Table 3 presents the calculated importance indices and the associated rank orders of the factors affecting percent-markup decisions for each contractor group. This results were also considered by the grouped factors. All factors are grouped in both decision stage by means of factor analysis6. The 11 factor groups are listed on the bid/no-bid decision stage by using varimax rotation method. These factor groups are as follows7 : l.Size and prestige of the job, 2,Owner, 3.Advanteges gained from the job (or specific features that provide advantages), 4. Cash-flow conditions of the job, 5.Risk factors, 6.Degree of difficulties (or adequacy of the firm), 7.Type of job and competitors, 8.Bidding conditions, 9.Resources requirements and site conditions, 10. Contents of contract, 11. Supervisors and tender committee. The 9 factor groups are listed on the percent-markup decisions stage by using varimax rotation method. These factor groups are as follows: l.Risk factors, 2.Contents of the job and cash-flow conditions, 3. Competitions factors, 4.specific features of the job for the firm, 5.Prestige of the job, 6.Resources 6 Factor analysis is a statistical technique used to identify a relatively small number of factors that can be used to represent relationships among sets of many interrelated individual factors (in both bid/no-bid and percent-markup decision stages). 7 Ranked of the basis of importance levels. XVrequirements, 7. Time given to bid, 8.Conditions of contract and the site, 9.Project delivery system and supervisors. Table 2. Importance indices and rank order of the factors affecting bid/no-bid decisions for small, medium and large. 8 Payment conditions of earned value 88,46 83,33 64,71 16 9 Experiences of the firm 80,77 80,95 68,63 12 1 0 Type of Job 75,64 11 75,00 68,63 13 1 1 Inactive labor of the firm 1 2, Prestige of the job 73,08 70,51 12 14 70,24 67,86 11 13 68,63 70,59 14 10 1 3 ' Desirability of the job 58,97 28 70,24 12 75,49 'This ranking is considered all of the firms (Large+Medium+Small). xviTable 3. Importance indices and rank order of the factors affecting percent markup decisions for small, medium and large. Ul !S id K > s Factors Affecting Percent-Markup Decisions Small Firms Importance Index Rank Medium Firms Importance Index ! Rank Large Firms Importance Index Rank 1 i Risk involved in job 91,03 78,57 92,16 2 ! Payment conditions of earned value 89,74 83,33 81,37 3 Capital requirment 80,77 78,57 90,20 Size of Job 84,62 72,62 88,24 Owner 85,90 83,33 78,43 Escalation 84,62 76,19 83,33 7 Continuity of job 8 : Experiences of the firm 84,62 74,36 6 11 71,43 80,95 82,35 75,49 5 12 9 Advance payment and its conditions 75,64 10 71,43 10 81,37 1 0 Nearness to other jobs (as site location) 80,77 65,48 16 80,39 1 1 Type of Job 12 Technology 67,95 76,92 80,95 67,65 66,67 13 67,65 16 17 1 3 Availability of credit and its conditions 67,95 58,33 22 78,43 10 1 4 Desirability of the job 60,26 26 67,86 11 74,51 13 1 5 Equipment requirement 69,23 15 67,86 12 67,65 18 1 6 Prestige of the job 69,23 16 59,52 21 72,55 14 1 7 Current work load 71,79 14 66,67 14 64,71 20 1 8 Security of the site location 62,82 23 57,14 25 77,45 11 1 9 Inactive la bor of the firm 74,36 12 66,67 15 60,78 23 This ranking is considered ali of the firms (Large+ Medium+Small). xvuFigure 1 shows a chart of factor groups affecting bid/no-bid decisions and the firms. Figure 2 shows a chart of factor groups affecting markup decision and the firms. Fig.l. Factors Groups Affecting Bid/No-Bid Decisions According to size of the Firms. Fig.l. Factors Groups Affecting Percent-Markup Decisions According to size of the firms. XVUlFinally, discriminant analysis8 was used to test whether differences do exist between small, medium and large contractors with regard to the importance of the factors affecting the decision stages, or that the inferences that are generated from the correlation coefficients are more accurate and differences do exist. In addition, if the groups are proven to be different then discriminant analysis will help in identifying the underlying dimensions of discrimination. The discriminant analysis produced two canonical functions as discriminators between the three groups for both bid/no-bid and percent-markup decision stages. The canonical correlation coefficient for functions and the eigen value are very high. This high association implies that the three classes vary in their evaluation for the importance of the both decision stages. By examining the correlations for the discriminant functions on the bid/no-bid decisions stage, it may be noticed that the other firms of the contractor, project delivery system, materials procurement, credit and advance payment conditions and owner being the factors involved in the definition of the functions. Thus, by examining the correlations for the discriminant functions on percent- markup decisions stage, it may be noticed that the contents and cash-flow of the job, materials equipment, contract and site conditions, labor requirements and inactive labor of the firm,time given to bid being the factors involved in the definition of the functions. Second, third and fourth chapters of the thesis attempts to survey the field covered cthe construction firm and its objectives and behaviours, decision making in construction firms and tendering process in the construction firms' and to address some areas previously neglected in the literature of the subject. 8 Discriminant analysis, first introduced by sir Ronald Fisher, is statistical technique most commonly used to investigate this type of problems. The concept underlying discriminant analysis is fairly simple. Linear combinations of independent, sometimes called predictor, variables are formed and serve as basis for classifying cases into one of the groups. XIX
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