Thesis (M.B.A.)--University of Hong Kong, 1997. / Includes bibliographical references.

Submitted in partial fulfillment of the requirements for the Degree of Masters of Business Administration, Durban University of Technology, 2008. / Industrial buying stands for more than half the whole economic activity in industrialised countries. Therefore, it is important to understand how customers of Afrox perform buying activities. The fabrication industry is a fast growing industry and is, therefore, interesting to study. The understanding of the buying behaviour of industrial organisations is of paramount importance to the industrial marketer. The study is a quantitative, cross sectional and descriptive investigation into buyer behaviour in the fabrication industry of Afrox. It highlights that industrial buyer behaviour has an extensive area, both for the practical marketer as well as from an academic perspective. As the fabrication industry is once again expanding, it is of essence to understand the buying behaviour in this industry. This report has the intention of highlighting how industrial buyer behaviour can be described in the fabrication industry. The purpose of this dissertation was to investigate the characteristics of industrial buying behaviour of fabrication customers at Afrox. The purpose has been further developed in forms of research questions dealing with the buying process, buyer behaviour, buying centre and buyer choice criteria. The sample studied is from a current company data base. With regard to the buying process, the most significant factors are price, quality, and technical capability.

published_or_final_version / Civil Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Business Administration / Master / Master of Business Administration

published_or_final_version / Business Administration / Master / Master of Business Administration

published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

Information search and acquisition is one of the important tasks in industrial procurement. The main issues of the present study are whether the needs of information and their patterns of importance would be affected by the following variables: product type, position of the supply chain, factors of individual participant (position, current unit, experiences of departments), organization structural factors, innovational resources commitments. The empirical study contexts are six machinery related sub-industries, including: vehicle, casting, die and mold, fastener, hand-tool, and machinery industry. From the 345 valid survey samples, the current research tested several hypotheses, of which significant findings include: (1) Different positions at a supply chain would cause difference of information needs. (2) Factors of individual participant also bring about different buying information needs: the current unit and experiences in different departments would significantly affect importance of the finance-cost, technique, salesperson information. (3) Organizational factors, including authority, horizontal interaction, vertical division, would give rise to more positive effect on buying experiences, country-of-origin, salesperson information. On the other hand, solicit negative effect on finance-cost information. (4) The product type would significantly moderate the causal relation between organizational factors and buying experiences, country-of-origin, or salesperson information. (5) Finance-cost information is less important for the higher innovational commitment companies than the lower ones

For the past several decades, there has been a fundamental dispute between the appropriate mechanism for repeat procurement. On one hand, the supporters of Porter (1979) advocate a competitive setting where short-term contracts are used to increase buyer power and lower supplier prices. On the other hand, the supporters of Deming (1986) advocate the idea of long-term contracts to align buyer and supplier incentives. This trade-off between long-term and short-term contracts has fundamentally affected the practice of procurement, with most suppliers opting for hybrid strategies such as Incumbent Biasing: a strategy characterized by short-term contracts with frequent rebidding with an advantage given to the incumbent. This work examines this hybrid strategy to determine its effectiveness. First, we create an empirical model that identifies and measures the trade-offs between the Porter and Deming strategies. Using this model, we find that Incumbent Biasing has an impact on procurement performance via two mechanisms: first, Incumbent Biasing decreases bidding competitiveness in repeat procurement bidding, which decreases performance; second, Incumbent Biasing has a moderating effect where it improves incentive alignment between the buyer and supplier and improves procurement performance. We show that depending on the current contract design, the net effect of Incumbent Biasing on overall procurement performance can be either positive or negative. This is first work to empirically test the impact of Incumbent Biasing on procurement performance and the first to identify the positive and negative mechanisms by which this impact occurs. Using this research, managers will be able to identify their firm's position with regards to incentive alignment with their supplier to determine if Incumbent Biasing has a net positive effect for their firm. After identifying the impact of Incumbent Biasing on procurement performance, we contribute to the literature by testing this analysis through two additional extensions. First, using secondary data analysis we show that our construct for procurement performance is correlated with firm performance. We do this by comparing the answers to our procurement performance construct items to the change in gross margin of the publicly traded respondents in our study over time. This shows that our construct is not only reliable, but that procurement performance has a positive impact on overall firm performance. This is the first work to provide an empirical construct for procurement performance that is validated via secondary data analysis of firm performance. Second, we test a competing theory to Incumbent Biasing which is Multi-Sourcing: the strategy of spreading a contract to multiple suppliers to maintain competitiveness in bidding. Approximately $46\%$ of our sample identify as using both strategies simultaneously and we test for an impact between the two. We show that the two strategies to not impact each other and can be viewed independently. Subsequently, we test two Multi-Sourcing constructs in our model and find that there is no significant impact on bidding competitiveness from Multi-Sourcing. Subsequently, we examine the impact of repeatedly awarding a contract to a pool of bidders. In our model, one contract is bid repeatedly over time, resulting in bidders gaining information about their competitors' cost. The academic literature is mixed on how a buyer should approach this type of contract bidding interaction. On one hand, it is argued that establishing an awarding structure that favors the incumbent decreases the frequency of switching, and thus cost. On the other hand, it is argued that an awarding structure that favors the non-incumbent (entrant) bidders places competitive pressure on the incumbent and generates low margin bids. This issue is further complicated by the practice cited in the academic literature of ``defection', where entrant firms either perceive a bias or believe that their cost is uncompetitive and will not bid in future stages. We create a framework that explores the apparent contradictions in these recommendations and gives conditions when biasing toward the incumbent or entrant should be implemented. We first characterize bidders based on their effort to bid and their cost to supply the contract. We then show that in the case of low effort to bid and high cost for the entrant, entrant biasing is optimal; when the reverse is true incumbent biasing is optimal. Using the results from our analysis, we provide guidance to buyers facing a repeated procurement

Supplier selection and order allocation are significant decisions for a manufacturer to ensure stable material flows in a highly competitive supply chain, in particular when customers are willing to accept products with less desirable product attributes. Hence, this study develops efficient methodologies to solve optimally the integrated supplier selection and order allocation problem incorporating customer flexibility for a manufacturer producing multiple products over a multi-period planning horizon. In this research, a new fuzzy multi-attribute approach is proposed to evaluate customer flexibility which is characterized through range and response. The approach calculates the product’s general utility value. This value is used by a bi-variant function which is developed to determine the retail price for the product. A new mixed integer program model describing the behavior of the basic problem is firstly developed. This basic model is the first to jointly determine: 1) type and quantity of the product variants to be offered; 2) the suppliers to be selected and orders to be allocated; and 3) inventory levels of product variants and raw materials/components. The objective is to maximize the manufacturer’s total profit subject to various operating constraints. This basic problem constitutes a very complex combinatorial optimization problem that is Nondeterministic Polynomial (NP)-hard. To tackle this challenge, two new optimization algorithms, i.e., an improved genetic approach called king GA (KGA) and an innovative hybrid algorithm called (CP-SA) _I which combines the techniques of constraint programming and simulated annealing are developed to locate optimal solutions. Extensive computational experiments demonstrate the effectiveness of these algorithms and also show clearly that (CP-SA) _I outperforms KGA in terms of both solution quality and computational cost. To examine the influence of subcontracting as one widespread practice in modern production management, this study also develops a modified mathematical model. It shares some similarity with the basic model but brings additional complexity by taking into consideration subcontractors for inter-mediate components and machine capacity. Since (CP-SA) _I outperforms KGA, it is employed and modified to solve the modified problem. Hence, this study presents a new hybrid algorithm called (CP-SA) _II, to locate optimal solutions. This study also establishes a new parallel (CP-SA) _II algorithm to enhance the performance of (CP-SA) _II. This parallel algorithm is implemented on a distributed computing platform based on the contemporary Graphic Processing Unit (GPU) using the Compute Unified Device Architecture (CUDA) programming model. Extensive numerical experiments conducted clearly demonstrate that the parallel (CP-SA) _II algorithm and its serial counterpart are efficient and robust optimization tools for formulating integrated supplier selection and order allocation decisions. Sensitivity analysis is employed to study the effects of the critical parameters on the performance of these algorithms. Finally, the convergence behavior of the proposed parallel (CP-SA) _II algorithm is studied theoretically. The results prove that the search process eventually converges to the global optimum if the overall best solution is maintained over time. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

The profitability of a manufacturer could be largely affected by underlying uncertainties embedded in the fast-changing business environment. Random factors, such as input material price at the procurement end or output product price and demand at the sales end, might produce significant risks. Effective financial hedging therefore needs to be taken to mitigate these risk exposures. Although it is common to use commodity futures to control the risks at either end separately, little has been done on the hedging of these risk exposures in an integrated manner. Therefore, this study aims to develop a planning approach that performs financial hedging on both the procurement risk and the sales risk in a joint manner. This planning approach is based on a framework that has a risk-averse commodity processor that procures input commodity and sells output commodity in the spot market, while hedging the procurement risk and sales risk through trading futures contracts in the commodity markets. Both the input and output commodities futures are used for the hedging. A both-end-hedging model is developed to quantitatively evaluate the approach. The evaluation is based on an objective function that considers both profit maximisation and risk mitigation. Decisions on spot procurement, input futures hedging position, and output futures hedging position are optimised simultaneously. As the input commodity is the main production material for the output commodity, positive correlation between the input material price and the output product price is considered. The customer demand is considered negatively correlated with the output product price. An ethanol plant using corn as the main input material is employed as an example to implement the proposed model. The model is represented as a stochastic program, and the Gibson-Schwartz two-factor model is employed to describe the stochastic commodity prices. Historical commodity price data are used to estimate the parameters for the two-factor model with state-space form and Kalman filter. By generating various scenarios representing evolving prices and the random customer demand, the stochastic program could be solved using linear programming algorithms under its deterministic equivalent. Numerical experiments are carried out to demonstrate the benefit that could be gained from applying the both-end-hedging approach proposed in this study. Comparing with traditional no-hedging model or single-end-hedging models, the improvement obtained from the proposed model is found to be significant. The effectiveness of the model is further tested in various price trend and price correlation, demand elasticity and volatility, and risk attitude of the decision maker. It is found that the proposed approach is robust in these various circumstances, and the approach is especially effective when the price trend is uncertain and when the decision maker has a strong risk-averse attitude. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy