Marketing mix

Summary

The term "marketing mix" is a foundation model for businesses, historically centered around product, price, place, and promotion (also known as the "4 Ps"). The marketing mix has been defined as the "set of marketing tools that the firm uses to pursue its marketing objectives in the target market". Marketing theory emerged in the early twenty-first century. The contemporary marketing mix which has become the dominant framework for marketing management decisions was first published in 1984. In services marketing, an extended marketing mix is used, typically comprising 7 Ps ( product, price, promotion, place, people, process, physical evidence), made up of the original 4 Ps extended by process, people and physical evidence. Occasionally service marketers will refer to 8 Ps (product, price, place, promotion, people, positioning, packaging, and performance), comprising these 7 Ps plus performance. In the 1990s, the model of 4 Cs was introduced as a more customer-driven replacement of t

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https://en.wikipedia.org/wiki/Marketing_mix

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Working capital restrictions can have disruptive effects on the coordination of the operations and finances of a company. Working capital restrictions may limit the inventory ordering power, reduce revenues, and increase the use of high premium debt. It may restrict the use of marketing and dynamic pricing decisions intended to smooth the variations of demand and revenues that result from the stochastic nature of the product life cycle. Given working capital’s multiplex composition and cost structure, its study requires careful assumptions to adequately capture its effects on the operational and financial sides. For this dissertation, we develop three models that explicitly take into account working capital restrictions. For the first research project, we build on a single-product finite-horizon periodic-review inventory management setting and include key financial aspects such as working capital constraints, payment delays and multiple sources of financing. While the Modigliani and Miller’s irrelevance principle establishes that the financial choices of a firm do not play a role in its valuation, our exploratory study examines the robustness of this result in a richer setting which intrinsically departs from their assumptions. Our numerical experiments show that when short-term debt as such becomes prohibitive or when downstream payment delays increase, the required working capital inflates rapidly. For the second research project, we study how a company should combine its inventory, product launch and marketing decisions to coordinate the operations and finances of a product portfolio that is working capital constrained. Our results show that the product portfolio benefits greatly from the joint management, reducing the amount of working capital required per product, and increasing the benefits per allocated working capital. For the last research project, we study how a company should combine its inventory, product launch and dynamic pricing decisions to coordinate the operations and finances of a product portfolio that is working capital constrained. We find that optimal product launch and pricing decisions help avoid simultaneous peak demands and simultaneous product launches. However, we find that working capital constraints can have strong negative effects on profits and may force not to launch a product in the worst cases.

EPFL2013

How Many CPU Cores is an FPGA Worth? Lessons Learned from Accelerating String Sorting on a CPU-FPGA System

Mikhail Asiatici, Paolo Ienne, Damian Maiorano

String sorting is a fundamental kernel of string matching and database index construction; yet, it has not been studied as extensively as fixed-length keys sorting. Because processing variable-length keys in hardware is challenging, it is no surprise that no hardware-accelerated string sorters have been proposed yet. In this paper, we present Parallel Hybrid Super Scalar String Sample Sort (pHS(5)) on Intel HARPv2, a heterogeneous CPU-FPGA system with a server-grade CPU. Our pHS(5) extends pS(5), the state-of-the-art string sorting algorithm for multi-core shared memory CPUs, by adding multiple processing elements (PEs) on the FPGA. Each PE accelerates one instance of the most effectively parallelizable among the dominant kernels of pS(5) by up to 33% compared to a single Intel Xeon Broadwell core despite a clock frequency that is 17 times slower. Furthermore, we extended the job scheduling mechanism of pS(5) to schedule the accelerable kernel not only among available CPU cores but also on our PEs, while retaining the complex high-level control flow and the sorting of the smaller data sets on the CPU. Overall, we accelerate the entire algorithm by up to 10% with respect to the 28-thread software baseline running on the Xeon processor and by up to 36% at lower thread counts. Finally, we generalize our results assuming pS(5) as representative of software that is heavily optimized for modern multi-core CPUs and investigate the performance and energy advantage that an FPGA in a datacenter setting can offer to regular RTL users compared to additional CPU cores.

SPRINGER2021

EPFL2013