The 4s web-marketing mix model

This paper reviews the criticism on the 4Ps Marketing Mix framework, the most popular tool of traditional marketing management, and categorizes the main objections of using the model as the foundation of physical marketing. It argues that applying the traditional approach, based on the 4Ps paradigm, is also a poor choice in the case of virtual marketing and identifies two main limitations of the framework in online environments: the drastically diminished role of the Ps and the lack of any strategic elements in the model. Next to identifying the critical factors of the Web marketing, the paper argues that the basis for successful E-Commerce is the full integration of the virtual activities into the company’s physical strategy, marketing plan and organisational processes. The four S elements of the Web-Marketing Mix framework present a sound and functional conceptual basis for designing, developing and commercialising Business-to-Consumer online projects. The model was originally developed for educational purposes and has been tested and refined by means of field projects; two of them are presented as case studies in the paper.\ud \u

CORPORATE SOCIAL RESPONSIBILITY IN ROMANIA

The purpose of this paper is to identify the main opportunities and limitations of corporate social responsibility (CSR). The survey was defined with the aim to involve the highest possible number of relevant CSR topics and give the issue a more wholesome perspective. It provides a basis for further comprehension and deeper analyses of specific CSR areas. The conditions determining the success of CSR in Romania have been defined in the paper on the basis of the previously cumulative knowledge as well as the results of various researches. This paper provides knowledge which may be useful in the programs promoting CSR.Corporate social responsibility, Supportive policies, Romania

What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective

Cognitive finance: Behavioural strategies of spending, saving, and investing.

Research in economics is increasingly open to empirical results. The advances in behavioural approaches are expanded here by applying cognitive methods to financial questions. The field of "cognitive finance" is approached by the exploration of decision strategies in the financial settings of spending, saving, and investing. Individual strategies in these different domains are searched for and elaborated to derive explanations for observed irregularities in financial decision making. Strong context-dependency and adaptive learning form the basis for this cognition-based approach to finance. Experiments, ratings, and real world data analysis are carried out in specific financial settings, combining different research methods to improve the understanding of natural financial behaviour. People use various strategies in the domains of spending, saving, and investing. Specific spending profiles can be elaborated for a better understanding of individual spending differences. It was found that people differ along four dimensions of spending, which can be labelled: General Leisure, Regular Maintenance, Risk Orientation, and Future Orientation. Saving behaviour is strongly dependent on how people mentally structure their finance and on their self-control attitude towards decision space restrictions, environmental cues, and contingency structures. Investment strategies depend on how companies, in which investments are placed, are evaluated on factors such as Honesty, Prestige, Innovation, and Power. Further on, different information integration strategies can be learned in decision situations with direct feedback. The mapping of cognitive processes in financial decision making is discussed and adaptive learning mechanisms are proposed for the observed behavioural differences. The construal of a "financial personality" is proposed in accordance with other dimensions of personality measures, to better acknowledge and predict variations in financial behaviour. This perspective enriches economic theories and provides a useful ground for improving individual financial services

Customer lifetime value: a framework for application in the insurance industry - building a business process to generate and maintain an automatic estimation agent

Research Project submited as partial fulfilment for the Master Degree in Statistics and Information Management, specialization in Knowledge Management and Business IntelligenceIn recent years the topic of Customer Lifetime Value (CLV) or in its expanded version, Customer Equity (CE) has become popular as a strategic tool across several industries, in particular in retail and services. Although the core concepts of CLV modelling have been studied for several years and the mathematics that underpins the concept is well understood, the application to specific industries is not trivial. The complexities associated with the development of a CLV programme as a business process are not insignificant causing a myriad of obstacles to its implementation. This research project builds a framework to develop and implement the CLV concept as maintainable business process with the focus on the Insurance Industry, in particular for the nonlife line of business. Key concepts, as churn modelling, portfolio stationary premiums, fiscal policies and balance sheet information must be integrated into the CLV framework. In addition, an automatic estimation machine (AEM) is developed to standardize CLV calculations. The concept of AEM is important, given that CLV information “must be fit for purpose”, when used in other business processes. The field work is carried out in a Portuguese Bancassurance Company which is part of an important Portuguese financial Group. Firstly this is done by investigating how to translate and apply the known CLV concepts into the insurance industry context. Secondly, a sensitivity study is done to establish the optimum parameters strategy. This is done by incorporating and comparing several Datamining concepts applied to churn prediction and customer base segmentation. Scenarios for balance sheet information usage and others actuarial concepts are analyzed to calibrate the Cash Flow component of the CLV framework. Thirdly, an Automatic Estimation Agent is defined for application to the current or the expanding firm portfolio, the advantages of using the SOA approach for deployment is also verified. Additionally a comparative impact study is done between two valuation views: the Premium/Cost driven versus the CLV driven. Finally a framework for a BPM is presented, not only for building the AEM but also for its maintenance according to an explicit performance threshold.O tema do valor embebido do Cliente (Customer Lifetime Value ou CLV), ou na sua versão expandida, valoração patrimonial do Cliente (Customer Equity), adquiriu alguma relevância como ferramenta estratégica em várias indústrias, em particular na Distribuição e Serviços. Embora os principais conceitos subjacentes ao CLV tenham sido já desenvolvidos e a matemática financeira possa ser considerada trivial, a sua aplicação prática não o é. As complexidades associadas ao desenvolvimento de um programa de CLV, especialmente na forma de Processo de Negócio não são insignificantes, existindo uma miríade de obstáculos à sua implementação. Este projecto de pesquisa desenvolve o enquadramento de adaptação, actividades e processos necessários para a aplicação do conceito à Industria de Seguros, especificamente para uma empresa que actue no Sector Não Vida. Conceitos-chave, como a modelação da erosão das carteiras, a estacionaridade dos prémios, as políticas fiscais e informação de balanço terão de ser integrados no âmbito do programa de modelação do valor embebido do Cliente. Um dos entregáveis será uma “máquina automática de estimação” do valor embebido, essa ferramenta servirá para padronizar os cálculos do CLV, para além disso é importante, dado que a informação do CLV será utilizada noutros processos de negócio, como por exemplo a distribuição ou vendas. O trabalho de campo é realizado numa empresa de Seguros tipo Bancassurance pertença de um Grupo Financeiro Português relevante. O primeiro passo do trabalho será a compressão do conceito do CLV e como aplicá-lo aos Seguros. Em segundo lugar, será feito um estudo de sensibilidade para determinar a estratégia óptima de parâmetros através de aplicação de técnicas de modelação. Em terceiro lugar serão abordados alguns detalhes da máquina automática de estimação e a sua utilização do ponto de vista dos Serviços e Sistemas de Negócio ( e.g. via SOA). Em paralelo será realizado um estudo de impacto comparativo entre as duas visões de avaliação do negócio: Rácio de Sinistralidade vs CLV. Por último será apresentado um desenho de processo para a manutenção continuada da utilização deste conceito no suporte ao negócio

Large Scale Deployment of Renewables for Electricity Generation

Comparisons of resource assessments suggest resource constraints are not an obstacle to the large-scale deployment of renewable energy technologies. Economic analysis identifies barriers to the adoption of renewable energy sources resulting from market structure, competition in an uneven playing field and various non-market place barriers. However, even if these barriers are removed, the problem of ‘technology lock-out’ remains. The key policy response is strategic deployment coupled with increased R&D support to accelerate the pace of improvement through market experience. The paper suggests significant contributions from various technologies, but does not assess their optimal or maximal market share