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Modelling for age and retirement becomes essential in many situations where promotion is age‐based and retirement is on attaining a particular age. A step by step approach to modelling retirement and average age of population through system dynamics is presented. The deterministic situation, with fixed residence time, is presented first and, then, the system equations are modified to accommodate probabilistic age of individuals by normal distribution. The proposed model has been tested and a few policy alternatives are suggested.

This chapter introduces four research methods that are not covered in the previous chapters. They are (1) non-parametric statistics, (2) interpretive structural modeling, (3) analytic hierarchy process, and (4) data envelopment analysis. The methods are discussed with examples. The discussion, however, is introductory; so we urge the reader to go through the pertinent references for details.

This paper aims to present the cyclone shelter location problem as a problem of grouping a set of villages into a minimum number of clusters and finding the location and capacity of the shelters.

Proposes an algorithm to solve the location problem that uses a distance matrix of the villages, applies Elzinga‐Hearn method iteratively to group them into circular clusters, and determines the shelter size. It is implemented in a software package, which reads the village records from a database, executes the steps of the algorithm, and writes the results into a file.

The villages are grouped into 13 clusters, eight requiring cyclone shelters to be built and five requiring no shelter, taking into consideration the available space in double‐storeyed buildings in the villages. The capacity and location of the each shelter are also obtained.

The approach can be modified to address several practical constraints. For example, for the villages situated far from the coast, the limiting travel distance can be increased, considering that a lesser intensity cyclone would give more time to the villagers to reach the shelter.

Funds are available from a number of public and private organizations to construct cyclone shelters, which could be used properly only when optimal locations for the cyclone shelters are identified.

Originality of the work lies in adapting Elzinga‐Hearn method iteratively to group the villages into circular clusters and implementing the algorithm in software solution. The concerned authority, to take cyclone shelter location decisions, can use the software.

The purpose of this paper is to present a model of the 24‐h software development process to help software project managers assess the profitability of a 24‐h development configuration and to select the optimal partnering sites. The model also helps the customer‐support divisions of software firms to decide which customer requests need to be performed using the 24‐h development mode.

This paper presents a graphical representation of the 24‐h software development process. Highlighting the importance of interaction times between two sites and the role of product‐, process‐, and site‐related factors that influence its value, the paper adopts the method of pair‐wise comparison of factors as done in the case of analytical hierarchy process and proposes a multiplicative model for its estimation. The software development time and cost are thereafter estimated by using site‐specific values of work hours, compensation package, and productivity. The approach is used to determine the economic viability of 24‐h development and make optimum site selection for a number of decision‐making situations.

The results obtained from applying the models to hypothetical, but realistic problems, with different values for site‐ and personnel‐specific factors to prove the ability of the model to be used in real‐life situations.

The proposed model does not consider effects of factors like multiple interactions, reworks, and errors in communication.

A circular representation of the 24‐h software development process, the multiplicative model for estimating the length of interaction time, and the time and cost of development in such a process are the main contributions of the paper.

To create a benchmark for design evaluation of commercial web sites, to model customers' site navigation behavior, and to develop and implement algorithms for link‐structure personalization.

The principal methodology used for design benchmarking is a survey of corporate web sites of some US Fortune 500 companies and top Indian companies and statistical analysis of the data so collected. The principal methodological approach for modeling user behavior, user's interest and algorithms for link‐structure personalization, is the development of a Markov decision process (MDP) in the overall framework of a semi‐Markov model and implementing the same in a link‐structure personalization system.

It is observed that the functional web site features significantly differ for the sites dealing with various product categories whereas the non‐functional features do not. The over‐stressed or under‐stressed features in the Indian web sites are found. The statistics generated from the user behavior model are validated against the real life user behavior and found satisfactory. The appropriateness of the link‐structure personalization algorithms is established by comparing the set of links generated by the algorithm with the links generated by the optimal policy of the underlying MDP.

The corporate that have been considered are conglomerates offering a number of products and services. But we categorize these sites based on their major product offering. Our approach of modeling the user behavior as a semi‐Markov process is possible because of our advanced implementation infrastructure. Undesirable network effects like delays, bandwidth, etc. may not make such a model that attractive in a very traditional type of environment. But the data collected in such environment can still be mined after adequate pre‐processing and appropriate normalization

Using the benchmark proposed in this model a webmaster can evaluate his web site. The sites with low site evaluation index can be improved by adding features with high weight depending on the product offering of the company. Webmaster can design the three level information architecture described in the paper and subsequently implement link‐structure personalization algorithm to improve site navigability. Besides improving site navigability the user behavior data collected thereon can be mined to generate other valuable information.

To assess and enhance the usability of an ecommerce site our work proposes: a benchmark to evaluate commercial web site design; a stochastic model to study and understand user behavior; an algorithm to personalize link‐structure of a commercial web site, and a general framework to implement a link‐structure personalization system.

Research and development (R&D) effectiveness has traditionally been measured in quantitative terms using measures such as the number of published papers (in journals, conference proceedings, etc.); patents; technologies successfully transferred or the external cash flow secured by a R&D organization. These are at times coupled with qualitative indicators such as the impact factor of the journals in which the papers are published and science citation index. However, all these measures often fail to adequately evaluate the effectiveness of research units (RUs) that carry out technological innovation projects. The present study examines this important conceptual question. The study attempts to develop a subjective measure of effectiveness of RU functioning within the laboratories under the Council of Scientific and Industrial Research (CSIR), India, in terms of peer review at four levels – self assessment, head of the RU, external scientific, and external administrative evaluators, using data from 236 RUs working in different laboratories functioning under CSIR. The measurement model component of structural equation modeling methodology using the LISREL 7.16 program has been adopted as the primary methodology for the study. In the measurement model presented, the observed indicators of the different effectiveness measure concepts (R&D effectiveness, user‐oriented effectiveness, administrative effectiveness and recognition) are assumed to possess causal relations with one another. Since subjective measures have not only weak measurement properties, but are also influenced by systematic and random measurement errors, the model's reliability and construct validity – both in terms of convergent validity and discriminate validity – have been ascertained.

Poor conditions of rural roads in most developing countries have hindered the growth of their rural economy. Investments from government and other sources in rural road projects are inadequate, leading often to political, rather than socio‐economic, considerations in allocating funds to specific projects. Realizing this, many donor organizations demand an unbiased study for prioritizing rural roads for funds allocation. This requires prioritizing rural roads on a rational basis. This paper seeks to examine this issue.

A two‐stage AHP model is developed considering several socio‐economic criteria relevant to a road and the region through which it passes. The model is exercised in a group‐decision environment. The final scores indicate a list of roads in decreasing order of priority.

The framework, when applied to 178 rural roads in two districts of Orissa, a relatively backward state of India, yields a ranked‐order list of roads.

Experts' judgments during pair‐wise comparison are associated with imprecision. Fuzzy AHP is a distinct alternative. Possible dependency among criteria has been ignored. Use of Analytic Network Process (ANP) can overcome problems arising from such dependencies.

Funds that are limited can be allotted to the highly ranked roads.

The paper presents application of AHP for ranking of rural roads in a developing country; development of a generic road prioritization framework; and devising a group decision‐making procedure that combines the best features of the group consensus and geometric mean methods.

The introductory paper begins with the issue about the relevance of research in management. It emphasizes the need for scholars to adopt methodologies best suited to the research problem of their choice. This paper contains sections on the nature of management research, dominant research paradigms, the methodological domain, quantitative versus qualitative research, and triangulation in using multiple methodologies. The paper provides a background to the purpose of the book and summarizes in brief the purpose of each the subsequent papers.

Economic literature highlights both positive and negative impact of FDI on economic growth. The purpose of this study is to confirm the relationship between various economic factors and FDI equity inflows and find out deviations, if any. This is investigated using standard time-series econometric models. The long and short run relationship is inquired with respect to market size, inflation rate, level of infrastructure, domestic investment and openness to trade. The choice of variables for Indian economy is purely based on empirical observations obtained from scientific literature review.

The study involves application of autoregressive distributive lag (ARDL) model to investigate the relationship. The long run co-integration between FDI and economic growth is tested by Pesaran ARDL model. The stationarity of data is tested by augmented Dickey Fuller test and Phillip–Perron unit root test. Error correction model is applied to study the short run relationship using Johansen’s vector error correction model method besides other tests.

The results show that the domestic investment, inflation rate, level of infrastructure and trade openness influence inward FDI flows. These factors have both long and short-term relationship with FDI inflows. However, market size is insignificant in influencing the foreign investments inflows. There lies an inverse relation between FDI and inflation rate.

To the best of the authors’ knowledge, the study is original. The methodology and interpretation of results are distinct and different from other similar studies.