In the present scenario of high unemployment; Multilevel Marketing (MLM) generates employment for people who have no permanent source of earning. MLM system has emerged as one of the prime alternatives in the current marketing system. India has become a very popular destination of doing MLM business with high potential of growth. MLM system provides lucrative compensation that works as motivation for people to join this business. Motivation for executives of any firm plays a major role in its success. It also leads commitment of employees towards work and responsibilities. An attempt has been made to identify the motivational variables that have the highest level of contribution for joining the MLM system. Most of the MLMcompanies focus on compensation plan or reward system but apart from that a number of variables have been found which motivate the distributors to engage in MLM business. Further, the distributors play a vital role in the growth of the business. In this study, we also propose a motivational model to help MLM companies formulate better strategies in making a large network of people for growth of business.

This paper shows that the Taguchi method of optimization can be easily used in optimizing the visual display unit (VDU) parameters for maximizing the readability on the laptop. Researchers use five factors, each at three levels which are font size, font style, line spacing, viewing distance and screen inclination angle with reading time in seconds (for reading about 300 words) as the response variable. Other parameters like text/background color combination (black/white), table height, illumination etc. were kept constant. Experiments were conducted by varying different parameters on the basis of L27 orthogonal array design. Results show that there is a 15.3% decrease in mean reading time when working at optimal condition. Results also show that factor A is the most important factor which is font size followed by factor C (line spacing), factor E (screen inclination angle), factor D (viewing distance) and factor B (the font style) which is the least important factor.

In a brief review of the literature on stocks’ pricing, the study shows that information vis-à-vis noise serves critical roles in the equilibrium process. It is dynamic in nature and there are different infiltrating aspects from the standard finance to behavioral finance points of views. The aspects of market efficiency, fundamental risk, noise traders’ risk, and implementation costs make the stock markets noisy and thereby, limit the arbitrage opportunity of informed traders. Investors’ psychological bases viz., belief and preferences contribute more in the equilibrium process. Beliefs include representativeness, conservativeness, and anchoring, availability biases, optimism and wishful thinking, overconfidence, and herd behavior tendency on the part of the investors. On the preferences, investors are influenced by disposition effect, prospects based on reference points, mental accounting, ambiguity aversion, and self control.The study explores the empirical literature also and reviews the six puzzles in the standard finance. Finally, the work identifies a few research gaps to be addressed in the literature.

The main objective of this study was to develop a set of measures, evaluate their importance and effect in cold supply chain performance. This investigation reviewed previous research works on all the stages of the farm product supply chain. Based on farm product supply chain, 4 measures with 31 metrics were identified and developed to measure the cold supply chain performance. A survey was organized to establish the importance and the effect of identified measures. The 5 point Likert scale questionnaire was distributed among SC academics and practitioners. The observed finding infers that the measurement instrument was substantiating for evaluating cold supply chain performance in farm industry. The new developed metrics will help firms improve the visibility of supply among partners and in better decision making. The investigation was enfolded up through the plan of direction intended for future study.

A multitude of techniques fall under the domain of Multi- Criteria Decision Making (MCDM) which is used to select the best alternative among the available ones. The objective of this paper is to compare some of these techniques with respect to the problem of selection of 3D printers, which is associated with multiple attributes. The weights of the criteria were determined using analytical network process (ANP). Next, the alternatives were ranked using three different MCDM techniques- 1.TOPSIS which ranks alternatives having the shortest distance to the ideal solution as well as the greatest distance from the negative-ideal solution 2. Deng’s Similarity based Approach where the most preferred alternative should have the highest degree of similarity to the positive ideal solution and the lowest degree of similarity to the negative-ideal solution and 3.PROMETHEE and GAIA. The solutions for each of these three cases were analyzed thoroughly, and reasons for any deviations were discussed.

This paper proposes an application of Analytical Hierarchy Process (AHP) to help decision maker evaluate different processes to identify the weaknesses of an automobile car service where the best alternatives and critical success factors are identified to improve their performances against the market leader. The proposed benchmarking process may help provide effective systematic decision support tool. Thus the endeavor has been made for car service industry to exhibit proposed framework by applying AHP to enhance its competitiveness. The proposed study provides an opportunity to apply to other industries in addition with a diminutive alteration.

The present study seeks to examine the stock-selection performance of the sample open-ended equity mutual fund schemes of Birla Sun Life Mutual Fund Company based on traditional and conditional performance measures. It is generally expected that inclusion of some relevant predetermined public information variables in the conditional CAPM provides better performance estimates as compared to the traditional measures. The study reports that after inclusion of conditioning public information variables, the selectivity performances of the schemes have dramatically improved relative to the traditional measure and also found that conditional measure is superior to traditional measure in statistical test.

Unexpected occurrence like natural calamity, abruptly change in customer demands, upgradation of technologies, necessity of compatible suppliers etc. is the most challenging issues even for efficient global supply chain management. Therefore, modeling of responsive supply chain is an emerging technology for sustaining any firm/industry in future competitive environment. In this paper, an attempt has been made to not only analyze the performance of efficient supply chain management but also how to improve the performance of existing supply chain with the objective of developing a modeling of responsive supply chain management. The complexity of the model is also highlighted with the help of numerical example. This paper also explores the possibility to mathematical modeling of the responsive supply chain which will be an emerging topic for researchers and practitioners. The modeling of responsive supply chain can be employed as a competitive strategy for e-commerce, green supply chain, and compatible supplier selection problem. The another salient feature of this paper is that a distinct comparative literature review of the lean, agile, efficient, and responsive supply chain management has been presented.

The main objective of this paper is to identify and understand the relationship dynamics among the quality enabled factors affecting the scheduling stage of production system life cycle. For this purpose, Interpretative structural modelling (ISM) approach has been utilized for developing the relationships among the various factors of the scheduling system stage. Afterwards, MICMAC (Matriced Impacts Croises Multiplication Appliqueeaun Classement) analysis has been carried out in order to classify the factors into different categories and to disclose the direct and indirect effects of each factor on the scheduling system. It is an approach for refining the decision making in the scheduling stage of production system life cycle.

Six Sigma is considered as a logical business strategy that attempts to identify and eliminate the defects or failures for improving the quality of product and processes. A decision on project selection in Six Sigma is always very critical; it plays a key role in successful implementation of Six Sigma. Selection of a right Six Sigma project is essentially important for an automotive company because it greatly influences the manufacturing costs. This paper discusses an approach for right Six Sigma project selection at an automotive industry using fuzzy logic based TOPSIS method. The fuzzy TOPSIS is a well recognized tool to undertake the fuzziness of the data involved in choosing the right preferences. In this context, evaluation criteria have been designed for selection of best alternative. The weights of evaluation criteria are calculated by using the MDL (modified digital logic) method and final ranking is calculated through priority index obtained by using fuzzy TOPSIS method. In the selected case study, this approach has rightly helped to identify the right project for implementing Six Sigma for achieving improvement in productivity.