29 resultados para Marketing Analysis

em Aston University Research Archive


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Internet marketing, as a key area of e-commerce, plays an important role in SMEs’ e-commerce success. It is the use of Internet technologies in facilitating and supporting marketing activities. Its implementation and success require expert knowledge and extensive experience. SMEs admit that they are willing to embrace Internet marketing to enhance their business competitiveness, but do not know where to start and suffer from a lack of guidance. Evidence suggests that Internet marketing analysis is one of the most needed areas of training in e-commerce for SMEs. It is therefore evident that SMEs need to acquire Internet marketing knowledge from external sources. However, the majority of the literature fails to study what specific knowledge they need and from whom they should acquire the knowledge. This paper has addressed these issues through a questionnaire survey of UK SMEs in the service sector. It identifies SMEs’ specific transfer needs for Internet marketing knowledge, and discusses strategic issues for improving SMEs’ effectiveness of leveraging knowledge.

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Despite a growing body of scientific research, there is still much uncertainty about the effects of marketing expenditures on the demand for pharmaceuticals. Recently it was found that higher marketing expenditures for a brand may reduce the price elasticity of demand, and hence allow firms to charge higher prices (Windmeijer et al [1]). In this study we reconsider the study by Windmeijer et al. We find that their econometric models are based on an incorrect assumption of homogeneous parameters across brands. As a consequence, our conclusions concerning the effects of pharmaceutical marketing are different from theirs.

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A hybrid approach for integrating group Delphi, fuzzy logic and expert systems for developing marketing strategies is proposed in this paper. Within this approach, the group Delphi method is employed to help groups of managers undertake SWOT analysis. Fuzzy logic is applied to fuzzify the results of SWOT analysis. Expert systems are utilised to formulate marketing strategies based upon the fuzzified strategic inputs. In addition, guidelines are also provided to help users link the hybrid approach with managerial judgement and intuition. The effectiveness of the hybrid approach has been validated with MBA and MA marketing students. It is concluded that the hybrid approach is more effective in terms of decision confidence, group consensus, helping to understand strategic factors, helping strategic thinking, and coupling analysis with judgement, etc.

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This paper looks selectively at strategic group theory and seeks to explore the benefits and limitations of modern strategic group analysis within the context of practical strategy making in the pharmaceutical industry. The rise and fall of strategic group research is reviewed and suggestions advanced as to the reasons why strategic group research suffered criticism and frequently produced conflicting results. The paper concludes that strategic group research offers a valuable way to classify firms by their strategy and provides some suggestions as to how industry strategists may benefit from strategic group analysis and avoid the pitfalls exposed by previous research.

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Marketing scholars are increasingly recognizing the importance of investigating phenomena at multiple levels. However, the analyses methods that are currently dominant within marketing may not be appropriate to dealing with multilevel or nested data structures. We identify the state of contemporary multilevel marketing research, finding that typical empirical approaches within marketing research may be less effective at explicitly taking account of multilevel data structures than those in other organizational disciplines. A Monte Carlo simulation, based on results from a previously published marketing study, demonstrates that different approaches to analysis of the same data can result in very different results (both in terms of power and effect size). The implication is that marketing scholars should be cautious when analyzing multilevel or other grouped data, and we provide a discussion and introduction to the use of hierarchical linear modeling for this purpose.

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Purpose - This paper provides a deeper examination of the fundamentals of commonly-used techniques - such as coefficient alpha and factor analysis - in order to more strongly link the techniques used by marketing and social researchers to their underlying psychometric and statistical rationale. Design/methodology approach - A wide-ranging review and synthesis of psychometric and other measurement literature both within and outside the marketing field is used to illuminate and reconsider a number of misconceptions which seem to have evolved in marketing research. Findings - The research finds that marketing scholars have generally concentrated on reporting what are essentially arbitrary figures such as coefficient alpha, without fully understanding what these figures imply. It is argued that, if the link between theory and technique is not clearly understood, use of psychometric measure development tools actually runs the risk of detracting from the validity of the measures rather than enhancing it. Research limitations/implications - The focus on one stage of a particular form of measure development could be seen as rather specialised. The paper also runs the risk of increasing the amount of dogma surrounding measurement, which runs contrary to the spirit of this paper. Practical implications - This paper shows that researchers may need to spend more time interpreting measurement results. Rather than simply referring to precedence, one needs to understand the link between measurement theory and actual technique. Originality/value - This paper presents psychometric measurement and item analysis theory in easily understandable format, and offers an important set of conceptual tools for researchers in many fields. © Emerald Group Publishing Limited.

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E-atmospherics have been often analyzed in terms of functional features, leaving its characteristics' link to social capital co-creation as a fertile research area. Prior research have demonstrated the capacity of e-atmospherics' at modifying shopping habits towards deeper engagement. Little is known on how processes and cues emerging from the social aspects of lifestyle influence purchasing behavior. The anatomy of social dimension and ICT is the focus of this research, where attention is devoted to unpack the meanings and type of online mundane social capital creation. Taking a cross-product/services approach to better investigate social construction impact, our approach also involves both an emerging and a mature market where exploratory content analysis of landing page are done on Turkish and French web sites, respectively. We contend that by comprehending social capital, daily micro practices, habits and routine, a better and deeper understanding on e-atmospherics incumbent and potential effects on its multi-national e-customer will be acquired.

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Growth in availability and ability of modern statistical software has resulted in greater numbers of research techniques being applied across the marketing discipline. However, with such advances come concerns that techniques may be misinterpreted by researchers. This issue is critical since misinterpretation could cause erroneous findings. This paper investigates some assumptions regarding: 1) the assessment of discriminant validity; and 2) what confirmatory factor analysis accomplishes. Examples that address these points are presented, and some procedural remedies are suggested based upon the literature. This paper is, therefore, primarily concerned with the development of measurement theory and practice. If advances in theory development are not based upon sound methodological practice, we as researchers could be basing our work upon shaky foundations.

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This paper shows how mobile phone technology can influence the development of egovernance in emerging countries. We evaluate the conditions under which consumers really engage with m-services. We argue that the lower cost of m-infrastructure is more appropriate than the Internet-based structure that prevents large part of the population access to ICT. However, m-technology should not be separated from the Internet but be integrated allowing emerging country to leap frog the technological cycle.

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The purpose of this study is to develop econometric models to better understand the economic factors affecting inbound tourist flows from each of six origin countries that contribute to Hong Kong’s international tourism demand. To this end, we test alternative cointegration and error correction approaches to examine the economic determinants of tourist flows to Hong Kong, and to produce accurate econometric forecasts of inbound tourism demand. Our empirical findings show that permanent income is the most significant determinant of tourism demand in all models. The variables of own price, weighted substitute prices, trade volume, the share price index (as an indicator of changes in wealth in origin countries), and a dummy variable representing the Beijing incident (1989) are also found to be important determinants for some origin countries. The average long-run income and own price elasticity was measured at 2.66 and – 1.02, respectively. It was hypothesised that permanent income is a better explanatory variable of long-haul tourism demand than current income. A novel approach (grid search process) has been used to empirically derive the weights to be attached to the lagged income variable for estimating permanent income. The results indicate that permanent income, estimated with empirically determined relatively small weighting factors, was capable of producing better results than the current income variable in explaining long-haul tourism demand. This finding suggests that the use of current income in previous empirical tourism demand studies may have produced inaccurate results. The share price index, as a measure of wealth, was also found to be significant in two models. Studies of tourism demand rarely include wealth as an explanatory forecasting long-haul tourism demand. However, finding a satisfactory proxy for wealth common to different countries is problematic. This study indicates with the ECM (Error Correction Models) based on the Engle-Granger (1987) approach produce more accurate forecasts than ECM based on Pesaran and Shin (1998) and Johansen (1988, 1991, 1995) approaches for all of the long-haul markets and Japan. Overall, ECM produce better forecasts than the OLS, ARIMA and NAÏVE models, indicating the superiority of the application of a cointegration approach for tourism demand forecasting. The results show that permanent income is the most important explanatory variable for tourism demand from all countries but there are substantial variations between countries with the long-run elasticity ranging between 1.1 for the U.S. and 5.3 for U.K. Price is the next most important variable with the long-run elasticities ranging between -0.8 for Japan and -1.3 for Germany and short-run elasticities ranging between – 0.14 for Germany and -0.7 for Taiwan. The fastest growing market is Mainland China. The findings have implications for policies and strategies on investment, marketing promotion and pricing.

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The recent history of small shop and independent retailing has been one of decline. The most desirable form of assistance is the provision of information which will increase the efficiency model of marketing mix effeciveness which may be applied in small scale retailing. A further aim is to enhance theoretical development in the marketing field. Recent changes in retailing have affected location, product range, pricing and promotion practices. Although a large number of variables representing aspects of the marketing mix may be identified, it is not possible, on the basis of currently available information, to quantify or rank them according to their effect on sales performance. In designing a suitable study a major issue is that of access to a suitable representative sample of small retailers. The publish nature of the retail activities involved facilitates the use of a novel observation approach to data collection. A cross-sectional survey research design was used focussing on a clustered random sample of greengrocers and gent's fashion outfitters in the West Midlands. Linear multiple regression was the main analytical technique. Powerful regression models were evolved for both types of retailing. For greengrocers the major influences on trade are pedestrian traffic and shelf display space. For gent's outfitters they are centrality-to-other shopping, advertising and shelf display space. The models may be utilised by retailers to determine the relative strength of marketing mix variables. The level of precision is not sufficient to permit cost benefit analysis. Comparison of the findings for the two distinct kinds of business studied suggests an overall model of marketing mix effectiveness might be based on frequency of purchase, homogeneity of the shopping environment, elasticity of demand and bulk characteristics of the good sold by a shop.