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The present competitive marketing environment demands effective role of distribution channels to create and develop a value-based infrastructure where companies can easily distribute their products into the consumers’ market. Relationship bonding between the channel partners and the company strengthens marketing efficiencies of the distribution function, which is supported by policies of the companies relating to joint business actions and value sharing. Both the tangible functional value and emotional functionalities play a vital role in the continuous success and the growth of distribution channel. The purpose of this paper is to understand the value-based distribution channel relationship for greater channel equity in fast-moving consumer goods (FMCG) sector.

The present study used a survey design to collect data from 156 FMCG channel members selected through stratified random sampling procedure. A five-point Likert-type scale was personally administered to obtain participants’ responses. Data were analysed using the Relative to an Identified Distribution (RIDIT) approach.

The findings of the current research paper have demonstrated that in the current competitive marketing environment, only the functional values are not enough. This research paper identifies that there is a strong need of emotional touch and linkages which leads to a symbiotic channel–company relationship and commitments in FMCG industry.

The present research is an original and innovative thought process of evaluating factors influencing the value-based distribution channel relationship for greater channel equity pertaining to FMCG industry by using the RIDIT approach.

The potential advantage of extreme value theory in modeling management phenomena is the central theme of this paper. The statistics of extremes have played only a very limited role in management studies despite the disproportionate emphasis on unusual events in the world of managers. An overview of this theory and related statistical models is presented, and illustrative empirical examples provided.

The purpose of this paper is to analyze the suitability of the real option methods in the valuation of WiMAX networks. Particularly, the shapes of the probability distributions for the investment costs and net present values (NPV) are examined.

The study analyzes the costs and NPV distributions by simulating an investment project in a rural area. The paper examines the influences of different uncertainty models and the shapes of the resulting investment costs, NPVs, and NPV ratios. The simulated option values are compared to results from different analytical equations.

The analysis in this study shows that the shape of the uncertainty – or error – in the parameters does not affect the shapes of the investment costs or NPV distribution. Instead, the subject of the uncertainty – i.e. the parameters for which the uncertainty is modeled – matters.

The study shows that the uncertainties and opportunities in network investments may increase the value of the projects dramatically and thus they should be taken into account. The shape of the NPV distribution varies depending on the technology and construction strategy of the network. This makes the real option valuation challenging since the assumptions of the valuation models must be satisfied for reliable results. Analytical option valuation formulas give the same results as simulation, only if the assumptions are sufficiently fulfilled and the parameters properly estimated.

The uncertainty in the service rate growth or population growth parameter influences the resulting distributions. The investment costs are positively skewed and can be approximated by a log‐normal distribution. This makes NPV negatively skewed, which suits badly in the existing analytical option valuation methods assuming log‐normal assets. Also, the NPV ratio is correlated with the investment costs.

This study examines problems that may occur when conventional Value‐at‐Risk (VaR) estimators are used to quantify market risks in an agricultural context. For example, standard VaR methods, such as the variance‐covariance method or historical simulation, can fail when the return distribution is fat tailed. This problem is aggravated when long‐term VaR forecasts are desired. Extreme Value Theory (EVT) is proposed to overcome these problems. The application of EVT is illustrated by an example from the German hog market. Multi‐period VaR forecasts derived by EVT are found to deviate considerably from standard forecasts. We conclude that EVT is a useful complement to traditional VaR methods.

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

This essay explores certain aspects of single product industry basic systems of the type Sraffa develops in Part I of Production of Commodities by Means of Commodities. It focusses on triangular trade as the simplest expression of the more general n-commodity case. Two elements of the framework are explored: (i) the relation of exchange between all commodities, conceived as the configuration of exchange which is applicable to the subsistence and surplus models, and (ii) the value/price expressions of labour time, applicable to the surplus model only, which posits the productivity of, remuneration to and extraction from living labour added to the system. This analysis complements and extends the Marxian reading of Sraffa’s notions of surplus and deficit industries first explored in Carter (2014b). The methodology of ‘given quantities’ in expositing the relations developed is adopted in this essay as it corresponds to the same method employed by Sraffa. This allows readers to easily move from the present essay to Sraffa’s book and importantly his archival notes which are now for all interested parties available as colour digital images on the Wren Library website.

The last few years in the financial markets have shown great instability and high volatility. In order to capture the amount of risk a financial firm takes on in a single trading day, risk managers use a technology known as value‐at‐risk (VaR). There are many methodologies available to calculate VaR, and each has its limitations. Many past methods have included a normality assumption, which can often produce misleading figures as most financial returns are characterized by skewness (asymmetry) and leptokurtosis (fat‐tails). The purpose of this paper is to provide an overview of VaR and describe some of the most recent computational approaches.

This paper compares the Student‐t, autoregressive conditional heteroskedastic (ARCH) family of models, and extreme value theory (EVT) as a means of capturing the fat‐tailed nature of a returns distribution.

Recent research has utilized the third and fourth moments to estimate the shape index parameter of the tail. Other approaches, such as extreme value theory, focus on the extreme values to calculate the tail ends of a distribution. By highlighting benefits and limitations of the Student‐t, autoregressive conditional heteroskedastic (ARCH) family of models, and the extreme value theory, one can see that there is no one particular model that is best for computing VaR (although all of the models have proven to capture the fat‐tailed nature better than a normal distribution).

This paper details the basic advantages, disadvantages, and mathematics of current parametric methodologies used to assess value‐at‐risk (VaR), since accurate VaR measures reduce a firm's capital requirement and reassure creditors and investors of the firm's risk level.

This paper examines the profit distribution of engineering projects in the integrated project delivery (IPD) mode. IPD is a new delivery method that can ameliorate many of the disadvantages of traditional delivery methods and improve project results. In the implementation of IPD, the profit distribution is key for ensuring the success of IPD projects.

This paper described a new method for characterizing profit distribution in the IPD mode. The payment function and Shapley value of the cooperative fuzzy game of fuzzy alliance were defined by considering the Choquet integral of the fuzzy measure. The participation of each player was considered, and the influence of participation on the profit distribution was discussed. Lastly, changes in the profit distribution of core participants under different alliance combinations were studied.

A case from a report of The American Institute of Architects (AIA) was used to verify the fuzzy alliance model. There was a significant correlation between the degree of participation of the owner, architect and builder and the profit distribution among these three participants.

The theoretical research in this paper has some limitations. Initially, this paper selects a case with only three key participants in order to simplify the research. When there are many core participants, how to establish the alliance in the IPD mode and how to establish the corresponding profit distribution model, further work is certainly required to disentangle these complexities in models. Second, in this case, BIM technology has little impact on the income of the whole project. Therefore, this paper does not consider the impact of BIM technology on the marginal effect of the IPD project. Third, the contract type in the case is a custom tri-party based on IFOA. There is no classified discussion of the impact of different contracts on the profit distribute in the paper.

Based on the in-depth study of cooperative game with alliance structure, this paper promotes the classic cooperative game with alliance structure. The authors define the payoff function of fuzzy cooperative games by Choquet integral of fuzzy measure, and introduce the idea into the field of IPD. It aims at extending the solution to a cooperative game without a core. It can be obtained through a simple calculation. In the IPD alliance, the fuzziness and uncertainty of the participation degree of each participant will affect the profit of the whole project. The authors find that the higher the participation rate of players, the more profit each participant has. The greater the influence weight of the designer on the alliance, the lower the influence weight of the contractor on the alliance, the lower the participation of the contractor and the designer, and the lower the income distribution value of the three core participants. It shows a monotonous decline status.

For any construction enterprise, it can make more profits if it joins the grand alliance. In the IPD alliance, each participant can maximize their own interests, which can also promote the enthusiasm of construction enterprises to participate in the alliance and increase the application of IPD mode in AEC industry. This research method provides a new fast, effective, and more realistic solution method for cooperative countermeasures. It can be further extended to other cooperative game fields and advance a new research perspective and solution for the distribution of cooperative interests.

The contribution of this paper is the development of a fuzzy alliance model that provides a tool for measuring the profit distribution in IPD. This is the first quantitative model to connect the degree of participation with the profit distribution in IPD using fuzzy alliance.

Application of financial risk models in the emerging markets poses special challenges. A fundamental challenge is to accurately model the return distributions which are particularly fat tailed and skewed. Value-at-Risk (VaR) measures based on the Extreme Value Theory (EVT) have been suggested, but typically data histories are limited, making it hard to test and apply EVT. The chapter addresses issues in (i) modeling the VaR measure in the presence of structural breaks in an economy, (ii) the choice of stable innovation distribution with volatility clustering effects, (iii) modeling the tails of the empirical distribution, and (iv) fixing the cut-off point for isolating extreme observations. Pakistan offers an instructive case since its equity market exhibits high volatility and incidence of extreme returns. The recent Global Financial Crisis has been another source of extreme returns. The confluence of the two sources of volatility provides us with a rich data set to test the VaR/EVT model rigorously and examine practical challenges in its application in an emerging market.