Transition through resonance in linear and nonlinear systems

In this work an asymptotic method known as the Krylov- Bogol iubov-Mit ropolsky (KBM) method is used to analyze linear and nonlinear systems. A system of first order equations for amplitude and phase is deduced. Using these first order equations the amplitude-response is approximated. The amplitude-response is then compared with the displacement response obtained by the Runge-Kutta method. Also, a comparative study is made between the stationary and nonstat ionary resonances in linear and nonlinear systems. The effect of linear variation of forcing frequency on the amplitude of the systems is closely examined. The consequence of different sweep rates on the amplitudes of the systems is also discussed

Salesperson Efficiency Benchmarking Using Sales Response Data: Who is Working Hard and Working Smart?

A key to enhancing sales force productivity is finding ways to help existing reps sell more. In this paper, we focus on the process of internal efficiency benchmarking of a firm’s sales representatives aimed at identifying strong and weak performers and providing meaningful and actionable directions for improving productivity of relatively inefficient performers. We propose to do this by utilizing measures of two fundamental attributes of a salesperson’s controllable work activity as inputs in a DEA (data envelopment analysis) – based procedure: how hard and how smart s/he works. The suggested metrics are derived in an empirical application using archival sales response data from a pharmaceutical company sales force. The application shows that, on average, working smart has larger effects on sales than working hard. In comparison to a conventional DEA benchmarking that simply uses raw sales calls as input measures, the proposed model that uses more ‘processing’ of the sales response data to derive working smart and hard input measures shows much larger potential for efficiency improvement and offers more meaningful and actionable guidance for improving sales force productivity

Project Tracking Tool

The project entitled “PROJECT TRACKING TOOL” deals with the various levels of project development and will account for time used in analysis, design programming, testing and verification etc. It is a known fact that the software solution institutes engage in many projects at the same time, and it is mandatory to monitor and manage ongoing tasks to meet deadlines for a smooth operation of business and a timely delivery of promised assignments with its clients to maintain its reputation and to have future business. During the lifetime of a project, the organization has to commemorate all the activities of the project. This tool makes it easier for the organization to monitor the projects. It maintains records and tracks various parameters that influence software project development process and helps the management to take decisions at various stages of the project development. The product will assist the organization in maintaining record of every project it undertakes. All the information relevant to the projects like size, time, effort and departments involved, etc. is maintained by this tool

Keyword portfolio optimization in paid search advertising

This paper uses investment portfolio theory to determine budget allocation in paid online search advertising. The approach focuses on risk-adjusted performance and favors diversified portfolios of unrelated or negatively correlated keywords. An empirical investigation employs averages, variances and co-variances for keyword popularities, which are estimated using growth rates for 15 major sectors taken from the Google Trends database. In line with portfolio theory, the results show that the average keyword popularity growth is strongly related to the standard deviation of growth for each keyword in the sample (R2 = 74%). Hypothesis testing of differences in Sharpe ratios documents a significantly better performance of the proposed approach compared to that of other strategies currently used by practitioners

Behavioral Implications of Demand Perception in Inventory Management

The newsvendor problem is one of the rudimentary problems of inventory management with significant practical consequences, thus receiving considerable attention in the behavioral operational research literature. In this chapter, we focus on how decision makers perceive demand uncertainty in the newsvendor setting and discuss how such perception patterns influence commonly observed phenomena in order decisions, such as the pull-to-center effect. Drawing from behavioral biases such as over precision, we propose that decision makers tend to perceive demand to be smaller than it actually is in high margin contexts, and this effect becomes more pronounced with increases in demand size. The opposite pattern is observed in low margin settings; decision makers perceive demand to be larger than the true demand, and this tendency is stronger at lower mean demand levels. Concurrently, decision makers tend to perceive demand to be less variable than it actually is, and this tendency propagates as the variability of demand increases in low margin contexts and decreases in high margin contexts. These perceptions, in turn, lead to more skewed decisions at both ends of the demand spectrum. We discuss how decision makers can be made aware of these biases and how decision processes can be re-designed to convert these unconscious competencies into capabilities to improve decision making

Network effects in two-sided markets: why a 50/50 user split is not necessarily revenue optimal

Our study applies empirical scrutiny to the network effects of a leading European online dating platform. While one might expect equal gender representation on such a platform to yield the best user experience and the highest revenue per user, our analysis shows that the platform requires only 36.2 % of its user base to be female to maximize revenue, primarily because women exert stronger positive cross-side network effects on men than vice versa; this optimum results in 17.2 % higher sales than a 50/50 split. Intermediaries of two-sided markets can use our model to improve user acquisition strategies

Empirical Models of Manufacturer-Retailer Interaction: A Review and Agenda for Future Research

The nature of the interaction between manufacturers and retailers has received a great deal of empirical attention in the last 15 years. One major line of empirical research examines the balance of power between them and ranges from reduced form models quantifying aggregate profit and other related trends for manufacturers and retailers to structural models that test alternative forms of manufacturer-retailer pricing interaction. A second line of research addresses the sources of leverage for each party, e.g., trade promotions and their pass-through, customer information from loyalty programs, manufacturer advertising, productassortment in general, and private label assortment in particular. The purpose of this article is to synthesize what has been learnt about the nature of the interaction between manufacturers and retailers and the effectiveness of each party’s sources of leverage and to highlight gaps in our knowledge that future research should attempt to fill