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Looks at the marketing literature on the subject of multi‐attribute utility models. Reviews the multiple objective and multi‐dimensional preference models within the framework of multiple attribute utility theory. Suggests that much of the research in this area has been information‐ rather than decision‐oriented and, as a result, this has not been integrated successfully into the field of strategic marketing policy‐making.

Prepaid mobile Internet is one of the most profitable services that are composed of multiple attributes. The overall utility of Internet service can be broken down into the sum of the utility of individual attribute levels. Based on the multi-attribute theory, rational consumers choose the service that yields the highest utility from a number of possible alternatives. Determining the optimal attribute levels that satisfy consumers' preferences and maximize the total revenue of the firm is a challenging multi-attribute decision problem for any mobile operator. When designing mobile Internet services, adopting a robust composition of services against different realizations of competitors' strategies can bring advantages for network operators. The purpose of this study is to determine the optimal attribute levels of prepaid mobile Internet packages with the aim of maximizing the total revenue of the firm by considering the paradigms of multi-attribute utility theory about consumer choices and the issue of uncertainty in counterpart services offered by the competitors.

This paper formulates the problem of multi-attribute pricing and design of mobile Internet plans in a competitive environment by developing deterministic and robust scenario-based mathematical models and considering the paradigms of multi-attribute utility theory about consumer choices. The proposed robust scenario-based models are based on three different paradigms, including maximizing expected revenue, minimizing the negative deviation from expected revenue and minimizing the maximum regret. A comprehensive numerical analysis is conducted to evaluate and compare the efficiency of the proposed models.

The evaluations reveal that deploying recourse policy can result in higher revenue for the firm when facing uncertainty. By doing sensitivity analysis, this paper shows that consumer preferences for brand attribute and consumers' purchase frequency can influence the revenue of network operators.

This paper develops a novel deterministic multi-attribute product line design (PLD) model to address the problem of determining the price and composition of prepaid mobile Internet plans. Furthermore, the issue of uncertainty in counterpart services offered by the competitors is studied for the first time in the PLD literature.

Advances in decision theory have allowed it to make an effective contribution to the modelling of the decision‐making process. Research work on maintenance decision making using decision theory, however, has received little emphasis to date. For this reason, very little has been done in utilizing two very important decision theory topics, namely utility theory and multi‐attribute utility theory. Investigates possible contributions from decision theory to the maintenance area and develops a framework to solve maintenance decision problems. This framework includes elicitation of both utility functions and prior probability distributions, optimization and sensitivity analysis modules. Details this framework and applies it to a real‐life maintenance problem.

To investigate the application of multi‐attribute utility theory (MAUT) to aid in the decision‐making process when performing benchmarking gap analysis.

MAUT is selected to identify the overall best‐in‐class (BIC) performer for performance metrics involving inventory record accuracy within a public sector warehouse. A traditional benchmarking analysis is conducted on 14 industry warehouse participants to determine industry best practices for the four critical warehouse metrics of picking and inventory accuracy, storage speed, and order cycle time. Inventory and picking tolerances are also investigated in the study. A gap analysis is performed on the critical metrics and the absolute BIC is used to measure performance gaps for each metric. The gap analysis results are then compared to the MAUT utility values, and a sensitivity analysis is performed to compare the two methods.

The results indicate that an approach based on MAUT is advantageous in its ability to consider all critical metrics in a benchmarking study. The MAUT approach allows the assignment of priorities and analyzes the subjectivity for these decisions, and provides a framework to identify one performer as best across all critical metrics.

This research study uses the additive utility theory (AUT) which is only one of multiple decision theory techniques.

A new approach to determine the best performer in a benchmarking study.

Traditional benchmarking studies use gap analysis to identify a BIC performer over a single critical metric. This research integrates a mathematically driven decision analysis technique to determine the overall best performer over multiple critical metrics.

The purpose of this paper is to use the concepts of the multi-attribute utility theory to develop a model to evaluate the design of low-density residential units to increase the profit of the company from a certain design, by assessing the changes in the market shares as a result of the built unit’s attributes.

The proposed platform consists of two stages: Stage I or relational model development and Stage II or design evaluation. Stage I is concerned with developing a mathematical model that links design variables (e.g. the R-Value of the building envelope and construction material) with the assessment attributes (e.g. price and carbon emissions). Stage II ensures the fulfillment of the corporation’s goals in maximizing profit and market shares using multi-attribute utility theory.

The application of the proposed model on a case study – a single-family house – shows that reducing the selling price of the unit is not always the best marketing strategy builders should pursue to increase their sales and accordingly their profit, as accounting for other attributes (e.g. performance, operational cost and environmental impact) leads to larger changes in the market shares and accordingly in profit.

The limitations of this research are manifested in the following points: it does not account for the impact of the marketing campaigns on the market shares; it considers the profit as a percentage of the construction cost; and it has not been validated on high-density residential buildings.

This research provides speculative builders with a platform that allows the objective evaluation of houses’ designs prior to introducing them to the market so builders can increase their market shares and consequently their profit. The proposed platform also contributes to increasing the sustainable performance of the housing industry, as it allows for the assessment of the design against economic, environmental and social attributes concurrently, which ensures a balanced consideration of the built houses on sustainability pillars.

The proposed platform for design evaluation extends the assessment attributes beyond the traditionally considered economic and environmental attributes. By doing so, it assists decision-makers in evaluating the potential social influence of the proposed design and, as a result, reduces the unwanted impact.

This research combines the concepts of multi-attribute utility with market studies to develop an objective decision support tool for evaluating the design of speculative houses to increase the sustainable performance of the builders without compromising on their profit.

This paper presents a model for equipment selection in earthmoving operations, utilizing multi‐attribute utility theory, analytical hierarchy process and computer simulation. Fleet configurations in the developed model are generated randomly from predefined fleet scenarios within a specified range. Simulation experiments are conducted for these generated configurations. The performance of these configurations is obtained from simulation experiments in the form of four measures which represent loader utilization, hauler utilization, project duration and project total cost. The utility values which represent the degree of satisfaction with those measures are estimated. These utility values are multiplied by their corresponding measures’ weights, calculated utilizing the analytical hierarchy process, in order to estimate the expected utility for each configured fleet. The fleet configuration that has the largest utility value is selected as the optimum fleet for the case at hand. A numerical example is presented to illustrate the different features of the developed model.

A bridge network is a major capital asset that requires continuing investment in order to maintain the network within acceptable limits of safety and serviceability. Ranking and prioritizing procedures have been widely used by several departments of transportation to select bridges for intervention and to distribute the available funds among competing projects. The available ranking and prioritizing procedures have various drawbacks, and an improved, rational ranking and prioritizing procedure is needed. The paper aims to address these issues.

The requirements and characteristics of an innovative ranking and prioritizing method are identified during interviews with professionals involved in bridge management. Based on these requirements, multi‐attribute utility theory (MAUT) is selected to develop the method. A technique to develop utility functions based on the analytical hierarchy process (AHP) is discussed. A hierarchy structure that captures the decision‐making elements is presented. A case study is used to demonstrate the applicability and the validity of the proposed ranking method.

The research findings have identified the decision objectives and the criteria essential to rank and prioritize bridge projects, and these are included within a framework to rank and prioritize bridge projects while incorporating experts' input in the process.

The proposed framework includes weights for the various objectives and recommends utility functions to evaluate the different attributes. In addition, the framework provides flexibility to adjust the weights and to modify the utility functions to reflect network‐specific characteristics. This method can be used by departments of transportation to rank bridges in a network, even incorporating conflicting criteria, and it can be integrated within an already implemented bridge management methodology.

Ranking and prioritizing projects are essential steps in bridge management. Current methods for ranking and prioritizing bridge projects are associated with various drawbacks. This paper proposes an innovative ranking method for bridge networks, based on MAUT. This theory provides flexibility for the decision makers in expressing their degree of satisfaction with each bridge attribute.

Despite substantial advances in technologies enhancing the energy efficiency of buildings, they remain the largest consumers of energy in the USA compared with other sectors. In addition, the current rating systems for sustainable buildings do not reflect all potential energy savings during the design, construction, and occupancy of the built environment. The purpose of this paper is to examine the application of multi-attribute utility theory (MAUT) as a framework for quantifying energy decisions made during the design phase of a building construction project.

The MAUT method was applied to a case study, and the results were compared with subjective results from the decision makers. Analysis of the results suggested that MAUT is a decision analysis tool that could aid decision makers in communicating their decision criteria and expectations.

Findings from this research suggest that using an analysis method provides the decision makers with a systematic way to include their concerns and preferences and specific requirements of the project along with the criteria for sustainable energy and the built environment at the same time. Using a multi-criteria, decision-making method provides the decision makers with quantitative information, which facilitates the comparison of alternatives. MAUT enabled the various stakeholders of the project to collaborate on the inputs of the problems and allowed the decision makers to communicate their priorities and expectations more effectively.

The findings indicated that MAUT provides stakeholders with a quantitative and holistic approach to decision making in which they can track changes in parameters during the process. The implementation of MAUT as a decision analysis tool in designing construction projects ultimately could lead to better decision making for sustainable building designs.

Leading organizations do not stop at the gathering and analysis of performance data; rather, these organizations use performance measurement to stimulate improvement efforts and successfully translate strategy into action. In other words, they use performance measurement for managing their organizations. The most commonly used performance evaluation tool, the balanced scorecard (BSC) has been used extensively in the manufacturing, government, banking, retail, insurance and financial services sectors. This paper looks at potential applications and benefits of using the BSC as a framework to evaluate the performance improvement resulting from IT/IS implementation by a construction organization. The paper firstly seeks to adapt the original BSC concept to construction and then attempts to develop a performance measurement framework in the form of a tiered “Construct IT” BSC. The developed framework allows for the measurement of IT/IS performance at three different decision‐making tiers (i.e., project, business unit and enterprise tiers). At each tier, a group of performance indicators are used to describe key aspects of activities that occur frequently enough to warrant meaningful measurement and comparison. The proposed framework applies the analytic hierarchy process (AHP) and multi‐attribute utility theory (MAUT) to facilitate aggregating the obtained diverse performance measurements, thus giving rise to an overall IT/IS performance improvement measure (score) at each decision‐making tier. To illustrate the application of the proposed framework, a project tier example is provided.

The sheer volume of decisions taken within the public sector procurement process prevents perfect and complete information being obtained and applied to every best value tender analysis that is carried out. As such, uncertainty must be accepted as a feature of the best value decision‐making process. This paper reports research which is developing a methodology for utilising the uncertainty component in best value tender analysis in order to create a more transparent decision making process. The main output of the research is the production of a robust support tool which aids the multi objective decision making process within the public sector of the UK construction industry by provoking rational discussion with respect to; the industry’s key performance indicators (KPIs), the client’s attitude to risk and provides a transparent audit trail of the decisions taken. The underlying rationale for the support tool is based on a combination of the Analytic Hierarchy Process (AHP), Multi‐Attribute Utility Theory (MAUT) and Whole Life Costing (WLC). The paper demonstrates the practical utility of the methodology of the tool through a tender decision process.