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Most investors' retirement portfolios have inter‐period cash inflows. The standard time‐weighted mean return (or geometric mean return) is generally used to report returns on investors' retirement portfolios. The purpose of this paper is to examine the standard time‐weighted mean return and point out additional deficiencies in the time‐weighted mean in this situation, which have not been addressed in the literature.

The paper provides examples that point out additional deficiencies that arise using geometric mean returns as estimates of an individual investor's performance.

With inter‐period cash flows the dollar‐weighted return can be affected by both timing and the sequence of the asset return series even if the investor has constant inflows or outflows of capital. In contrast for these same asset return arrays, the time‐weighted mean return measure may be unaffected by these important variations in the return arrays, and thus may misrepresent actual investor results. This is an important point that has not been addressed in the literature.

With inter‐period cash flows the dollar‐weighted return can be affected by both timing and the sequence of the asset return series even if the investor has constant inflows or outflows of capital. In contrast for these same asset return arrays, the time‐weighted mean return measure may be unaffected by these important variations in the return arrays, and thus may misrepresent actual investor results. This is an important point that has not been addressed in the literature.

The purpose of this paper is to develop some picture uncertain linguistic aggregation operators based on Bonferroni mean operators, which is combined with multiple attribute decision-making (MADM) and has applied the proposed MADM model for selecting the service outsourcing provider of communications industry under picture uncertain linguistic environment.

The service outsourcing provider selection problem of communications industry can be regarded as a typical MADM problem, in which the decision information should be aggregated. In this paper, the authors investigate the MADM problems with picture uncertain linguistic information based on traditional Bonferroni mean operator.

The results show that the proposed model can solve the MADM problems within the context of picture uncertain linguistic information, in which the attributes are existing interaction phenomenon. Some picture uncertain aggregation operators based on Bonferroni mean have been developed. A case study of service outsourcing provider selection problem of communications industry is provided to illustrate the effectiveness and feasibility of the proposed methods. The results show that the proposed methods are useful to aggregate the picture uncertain linguistic decision information in which the attributes are not independent so as to select the most suitable supplier.

The proposed methods can solve the picture uncertain linguistic MADM problem, in which the interactions exist among the attributes. Therefore, it can be used to solve service outsourcing provider selection problems and other similar management decision problems.

This paper develops some picture uncertain aggregation operators based on Bonferroni mean and further presents two methods based on the proposed operators for solving MADM problems. It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.

It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.

The paper investigates the MADM problems with picture uncertain linguistic information based on traditional Bonferroni mean operator and develops the picture uncertain linguistic Bonferroni mean operator and picture uncertain linguistic geometric Bonferroni mean operator, picture uncertain linguistic weighted Bonferroni mean operator and picture uncertain linguistic weighted geometric Bonferroni mean operator for aggregating the picture uncertain linguistic information, respectively. Finally, a numerical example concerning the service outsourcing provider selection problem of communications industry is provided to illustrate the effectiveness and feasibility of the proposed methods.

Suggests that the use of the geometric mean as a measure of average return on investment presents problems for estimating the variance as a measure of risk. Notes that the use of a measure based on the arithmetic mean seems an uncomfortable compromise. Shows that measures based on the geometric mean are also systematically biased in the case of log normal returns. Concludes that this can have major consequences for investment decision‐making and portfolio selection.

Intuitionistic linguistic fuzzy information (ILFI), characterized by linguistic terms and intuitionistic fuzzy sets (IFSs), can easily express the fuzzy information in the process of muticriteria decision making (MCDM) and muticriteria group decision making (MCGDM) problems. The purpose of this paper is to provide an overview of aggregation operators (AOs) and applications of ILFI.

First, some meaningful AOs for ILFI are summarized, and some extended MCDM approaches for intuitionistic uncertain linguistic variables (IULVs), such as extended TOPSIS, extended TODIM, extended VIKOR, are discussed. Then, the authors summarize and analyze the applications about the AOs of IULVs.

IULVs, characterized by linguistic terms and IFSs, can more detailed and comprehensively express the criteria values in the process of MCDM and MCGDM. Therefore, lots of researchers pay more and more attention to the MCDM or MCGDM methods with IULVs.

The authors summarize and analyze the applications about the AOs of IULVs Finally, the authors point out some possible directions for future research.

In estimating the inputs into the modern portfolio theory (MPT) portfolio optimisation problem, it is usual to use equal weighted historic data. Equal weighting of the data, however, does not take account of the current state of the market. Consequently this approach is unlikely to perform well in any subsequent period as the data is still reflecting market conditions that are no longer valid. The need for some return weighting scheme that gives greater weight to the most recent data would seem desirable. Therefore, this study uses returns data which are weighted to give greater weight to the most recent observations to see if such a weighting scheme can offer improved ex ante performance over that based on unweighted data.

When one talks of the return performance one typically refers to an average buy‐and‐hold return, also known as time‐weighted return. However, the returns of investors can be quite different. Investor returns are determined not only by the returns on the underlying assets but also by the timing and magnitude of their capital flows into and out of these assets. To account for the annual‐to‐annual variation in assets under management, a dollar‐weighted return has to be calculated. The difference between time‐weighted returns and dollar‐weighted returns is known as the performance gap. The purpose of this paper will be to investigate this in the UK property market.

Using an approach similar to that of Dichev the authors examine the performance gap in the UK direct property market using historical return data for 45 market‐segments over the time period 1981‐2009.

The results show that the performance gap was negative, i.e. investor returns were greater than asset returns. That is, UK direct property investors have shown greater returns than their underlying investments. This implies that estimates of the performance of the UK property market based on property returns do not reflect the experience of investors as a group.

This study provides the first evidence of the performance gap in the UK direct real estate market.

The purpose of this paper is to generalize the traditional risk evaluation methods and to specify a multi-level risk evaluation framework, in order to prepare customized risk evaluation and to enable effectively integrating the elements of risk evaluation.

A real case study of an electric motor manufacturing company is presented to illustrate the advantages of this new framework compared to the traditional and fuzzy failure mode and effect analysis (FMEA) approaches.

The essence of the proposed total risk evaluation framework (TREF) is its flexible approach that enables the effective integration of firms’ individual requirements by developing tailor-made organizational risk evaluation.

Increasing product/service complexity has led to increasingly complex yet unique organizational operations; as a result, their risk evaluation is a very challenging task. Distinct structures, characteristics and processes within and between organizations require a flexible yet robust approach of evaluating risks efficiently. Most recent risk evaluation approaches are considered to be inadequate due to the lack of flexibility and an inappropriate structure for addressing the unique organizational demands and contextual factors. To address this challenge effectively, taking a crucial step toward customization of risk evaluation.

The purpose of this paper is to develop some 2-tuple linguistic aggregation operators based on Muirhead mean (MM), which is combined with multiple attribute group decision making (MAGDM) and applied the proposed MAGDM model for supplier selection under 2-tuple linguistic environment.

The supplier selection problem can be regarded as a typical MAGDM problem, in which the decision information should be aggregated. In this paper, the authors investigate the MAGDM problems with 2-tuple linguistic information based on traditional MM operator. The MM operator is a well-known mean type aggregation operator, which has some particular advantages for aggregating multi-dimension arguments. The prominent characteristic of the MM operator is that it can capture the whole interrelationship among the multi-input arguments. Motivated by this idea, in this paper, the authors develop the 2-tuple linguistic Muirhead mean (2TLMM) operator and the 2-tuple linguistic dual Muirhead mean (2TLDMM) operator for aggregating the 2-tuple linguistic information, respectively. Some desirable properties and special cases are discussed in detail. Based on which, two approaches to deal with MAGDM problems under 2-tuple linguistic information environment are developed. Finally, a numerical example concerns the supplier selection problem is provided to illustrate the effectiveness and feasibility of the proposed methods.

The results show that the proposed can solve the MAGDM problems within the context of 2-tuple linguistic information, in which the attributes are existing interaction phenomenon. Some 2-tuple aggregation operators based on MM have been developed. A case study of supplier selection is provided to illustrate the effectiveness and feasibility of the proposed methods. The results show that the proposed methods are useful to aggregate the linguistic decision information in which the attributes are not independent so as to select the most suitable supplier.

The proposed methods can solve the 2-tuple linguistic MAGDM problem, in which the interactions exist among the attributes. Therefore, it can be used to supplier selection problems and other similar management decision problems.

The paper develop some 2-tuple aggregation operators based on MM, and further present two methods based on the proposed operators for solving MAGDM problems. It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.

Modular construction is considered a well-established construction method for improving the efficiency of the construction industry worldwide. However, the industry struggles to achieve higher levels of modularisation in urban areas. Previous studies on decision-making for modularisation have, so far, not focussed much on its application in urban areas. As modular construction could bring lots of advantages such as speed of construction, This study aims to develop a decision-making tool that can assist the project planners in deciding whether the modular construction techniques should be applied in their urban area project.

Based on the literature review, a total of 35 decision-making factors of modularisation were identified for this study. The decision-making model is then developed to evaluate the significance of each factor using the analytic hierarchy process (AHP) approach. A total number of 72 valid responses were obtained and analysed. The geometric mean of priorities is adopted to obtain the par-wise comparison between the critical factors in which each factor’s weighting in the decision-making model is calculated. Afterwards, the robustness of the decision-making model is demonstrated by the real-life projects in China, Hong Kong and the UK, respectively.

A total of 35 decision-making factors allocated in five criteria for modular construction selection in urban areas were identified. The criteria include site attributes, project characteristics, labour consideration, environmental and organisation and project risk. Their impact was calculated using the AHP to indicate the relative importance with respect to the adoption of modularisation in urban areas. Afterwards, a two-level decision-making model was developed that can be used as a decision-making tool for the adoption of modular construction.

The outcome of this research will be beneficial to industrial practitioners and academics in understanding the critical attributes that affect the adoption of modular construction in an urban area. It further enables the building professionals to assess the feasibility of using modular construction in their projects, especially at the early stage, so as to facilitate its use.

There is a number of literature on the decision-making model on the adoption of modular construction. However, previous studies did not provide specific concerns related to urban areas, whereas there is an urgent need to have an updated analysis that can be catered to the modular construction in the urban area. In this research study, the 35 decision-making factors were ranked by the experienced project managers and then a pair-wise comparison was conducted. With this information, the robust decision-making model is formulated to offer a kept promised indicator in adopting modularisation in the urban area.

The purpose of this paper is to develop weights of key performance areas (KPAs) and performance indicators for public private partnerships (PPPs) in Bangladesh. Since a variety of PPP arrangements is observable, different performance measurement approaches exist in the literature. However, analysing the relative importance of indicators influencing the performance score of particular projects using the perspective of developing countries remains unexplored.

The authors’ method involves application of the analytical hierarchy process (AHP) to develop weights for eight KPAs for which 41 contributing performance indicators have been developed. In total, 68 respondents (62 per cent of the PPP practitioners in Bangladesh) participated in a structured questionnaire survey and their judgements have been found to be consistent, using consistency ratios, a geometric consistency index and one-way ANOVA test.

“Feasibility analysis”, “life cycle evaluation and monitoring” and “optimal risk allocation” are the most significant performance indicators in Bangladesh. “Financing” is the most important KPA, followed by “planning and initiation” and “transparency and accountability”. Interestingly, unlike the cost, time and quality measures of the public sector comparator analysis used in most developed countries, a different set of indicators and KPAs are found dominant.

This suggests that performance indicators and their weights may differ for developing countries. Future research could usefully focus on testing this model in different countries and applying it to derive performance scores for individual PPPs.

An application of AHP in determining weights of the performance indicators represents a major contribution to the literature on PPP performance measurement in the developing countries including Bangladesh.