Il presente lavoro si propone di analizzare l’esistenza di possibili differenze nel comportamento esplorativo di consumatori di nazionalità italiana e greca. Dalle analisi condotte risulta che entrambi i gruppi di acquirenti dimostrano una debole propensione verso i comportamenti di tipo ripetitivo ed una forte tendenza a provare ed acquistare dei nuovi prodotti. In entrambe le categorie di rispondenti è stata rilevata una scarsa propensione al rischio, la tendenza a concepire lo shopping come un’esperienza di carattere esplorativo, ed una certa propensione a provare nuovi brand. I consumatori italiani, tuttavia sono apparsi maggiormente predisposti verso i rapporti interpersonali. Nelle sezioni conclusive dell’articolo si discutono le implicazioni operative e di marketing dei risultati ottenuti.
This paper proposes a new model of advertising research based on the new understanding of the mind provided by brain science. It hypothesises that much advertising nowadays works implicitly-- either below, or at very low levels of, awareness--but that so-called affective (emotional) advertising does not work exclusively through implicit processes. It suggests that both recall
and recognition may be effective means of measurement for emotional advertising, and argues that attempts to prejudge advertising as either rational or emotional are highly problematic. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The authors review literature on online surveys and describe an experiment that compares an embedded e-mail survey with an attached e-mail survey. 150 students were randomly selected to receive the embedded e-mail survey and 150 students were randomly selected to receive the attached e-mail survey. The embedded survey yielded a significantly higher response rate than the attached survey, but there were no differences between the two methods on response speed, number of item omissions, or response bias. Suggestions are offered to future researchers of online surveys. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Many companies collect stated preference data (SP), such as intentions and satisfaction, as well as revealed preference data (RP), such as actual purchasing behaviour. It seems relevant to examine the predictive usefulness of this information for future revealed preferences, that is, customer behaviour. In this paper we address this issue by considering three case studies. Our results indicate that adding SP data to RP data for predicting future customer behaviour does not result in better forecasts.
Although there are numerous studies related to country-of-origin (COO) effects, empirical findings are dispersed because of the limited coverage of the origins, brands and countries used for investigation. This paper uses an existing data set that consists of a survey conducted across 20 nations to evaluate 11 automobile origins with 53 brands. This data set facilitates the verification of COO effects previously addressed in the literature from a holistic viewpoint. It also provides insight into the circumstances under which, and the extent to which, the COO effects could differ. The results derived from correspondence analysis (CA) suggest there are brand and national variations in the magnitude of COO effects. At brand level, COO effects appear to be more influential on the purchase behaviour of consumers who have a positive attitude towards the brand being investigated or perceive it to be of high quality. At the national level, COO effects seem to be more significant among nations where the availability of international automobile brands is lower. Furthermore, the findings not only support the notion that consumers tend to have a stronger preference for products that originate from their own countries, but also concur with the proposition that consumers also tend to have a stronger preference for products from countries in the same geographic region. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The impact of SERVQUAL (Parasuraman
et al. 1988) on the measurement of service quality is documented. Research highlighting conceptual, methodological and interpretative problems is critically reviewed in the light of recent advancements in service quality measurement and, specifically, research on the cognitive psychology of survey responding. Directions for future research are also discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
This paper advances the debate concerning the future of market research by presenting nine new rules to guide thought and action in a period of transition. These become the market researcher's manifesto for change. First, they describe the new marketplace emerging as we shift from a production-driven to a consumption-led economy. In response, marketers have shifted their focus of activity from completing transactions to building relationships. This context then provides the background for discussion about the role of the market researcher. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Mystery customer research and factors associated with memory likely to influence its accuracy Mystery customer research is a technique of quality assessment in the retail sector, where it is called mystery shopping, and also in the service sector. It is growing rapidly in popularity, but research in cognitive psychology suggests a number of potential threats to the reliability and validity of data collected through its use. In particular, various factors associated with the encoding, storage, and retrieval of information by mystery customer assessors are likely to influence the accuracy of the results, and individual differences between assessors should also be taken into account in designing mystery customer surveys. A number of specific recommendations designed to minimize errors arising from memory failures and distortions are outlined and discussed.
This paper discusses the criticism that has been targeted at the advertising industry about its hesitancy to use older models in advertising. It reports research on this issue in the context of current advertising in print media, using content analysis of British advertisements in inappropriate journals. The paper includes general discussion about ageism in advertising and its social implications.
Recently, Balakrishnan and Jacob (1996) have proposed the use of Genetic Algorithms (GA) to solve the problem of identifying an optimal single new product using conjoint data. Here we extend and evaluate the GA approach with regard to the more general problem of product line design. We consider profit contribution as a firm's economic criterion to evaluate product design decisions and illustrate how the genetic operators work to find the product line with maximum profit contribution. In a Monte Carlo simulation, we assess the performance of the GA methodology in comparison to Green and Krieger's (1985) greedy heuristic.
The analysis of data from market research has, until fairly recently, been reliant upon statistical techniques that were developed during the nineteenth and early twentieth century for uses entirely other than the analysis of survey and other types of observational, non-experimental data. Such techniques rely on reviewing and relating the frequency distributions of variables that have been concocted and measured by researchers. This article argues that key features of such ‘frequentist’ statistics are also limitations that need to be recognized by academics, market research practitioners and the managers to whom they report findings. By focusing on variable distributions across cases, they overlook patterns of within-case configuration; they seek out only symmetrical, linear patterns by reviewing the ‘net effects’ of individual variables; they rely on a very circumscribed view of statistical inference from samples to populations; they are not good at demonstrating causal connections between variable or at handling system complexity. A follow-up article, ‘Rethinking data analysis (2) Some alternatives to frequentist approaches’ examines ways of approaching datasets that can be seen as viable alternatives.
The customer relationship management (CRM) industry is set to be worth $76.3 billion by 2005 but over 50% of projects will fail to meet benefit objectives. While CRM nirvana is the attainment of profitable one-to-one relationships, current activity is concentrated on segmentation. As technology has moved segmentation from simple classification towards more complex predictive modelling, the use of CRM analytic suites comprising statistical techniques such as decision trees, neural networks and cluster analysis is increasing. It is suggested that the subjective nature of cluster analysis may be overlooked when the technique is integrated with other 'tools' into a data-mining package and, consequently, that inadequately tested cluster analysis solutions may be contributing to CRM dissatisfaction. This paper reports the findings of a study which subjected a data set designed for segmentation purposes to a series of rigorous validity and reliability tests and went as far as to randomise the data to ascertain whether current methods could detect 'false' data. The study shows, alarmingly, that under certain conditions random data can 'pass' standard tests and highlights just how meticulously and thoroughly cluster analysis solutions must be tested before they can be safely used in formulating marketing strategy. Practical, theoretical and technical advice is offered for managers working with CRM analytics suites and avenues suggested for future research into improved CRM performance through effective management of the IT/marketing interface.
In this study 9 methods for measuring indirect importance are compared on the basis of their diagnosticity and stability. To the best knowledge of the authors the stability of results obtained with different methods is assessed for the first time. The deficiencies of an existing criterion for assessing diagnosticity are pointed out and a modified version is suggested. The empirical comparison is based on two real-world datasets from the ecommerce industry. Even though none of the methods appeared to be the best according to both criteria simultaneously, there seem to be grounds for recommending the theoretically sound Shapley value decomposition of R-square if stability and diagnosticity are about equally important for a decision maker, while negative contributions are undesirable.
Cluster analysis has been successfully used in market segmentation for several decades. However, alongside evidence for the value of the technique, a number of studies have highlighted the importance of testing the reliability and validity of cluster solutions. Yet, in a time-poor technologically sophisticated age when alluring output falls effortlessly from user-friendly statistical packages, managers may fail to appreciate the rigorous testing required to ensure robust solutions. The authors designed an experiment to investigate whether managers could distinguish between cluster analysis outputs derived from real and random data. Given information on only cluster centroids and demographic profilers, random data devoid of meaningful structure were perceived as equally useful for purposes of market segmentation as real data. If these findings generalise, then managers could be formulating segmentation strategy based on appealing statistics that are at best untested and at worst completely misleading. As cluster analysis is incorporated into the analytics suites of popular CRM systems, marketing managers are becoming increasingly distanced from the raw data. Yet, the consequences of inappropriate use of cluster analysis, and in particular inadequate validation, can be dramatic.
This paper details an alternate methodology that permits the consumer decision process to be observed without the constraint of model phases or 'sets'. A new custom-developed computerised process tracing methodology is utilised, identifying the decision wave boundaries in a durable product purchase scenario. The electronic process tracing methodology reveals multiple pathways to consumer choice for a durable purchase decision. Consumers choose an airconditioningalternative using up to ten decision waves, 40% of which may be outside our current decision models. This research suggests that most consumers do not construct a choice set to make a purchase decision, and this may have an impact on product positioning and differentiation decisions, as well as identifying the importance of being the 'last alternative standing'. This research found three common pathways to consumer choice. Marketing tactics must address the informational requirements of each pathway for their product to become a candidate for selection. Yes Yes
This article deals with the effects of a somewhat overlooked response inducing technique in mail surveys, i.e. the inclusion of questionnaire identification numbers. Results indicate that the inclusion of such numbers has a positive effect on response rate and has no effect on item omission. Furthermore, it is suggested that efforts to make identification numbers more visible do not always produce desirable results. More specifically, it has been found that use of an inappropriate colour and excessive use of graphics have a negative effect on response rate.
The author presents her views on the significance of user-generated content for marketing research. The impact of online social networks on marketing strategy is discussed, and it is noted that nearly 140 million brands have pages on the Facebook web site. The author believes that some essential features of marketing research into consumer behavior remain unaffected by technological innovations, such as the importance of analyzing qualitative data.
The authors examine the concept of consumer savvy, distinguishing consumer savvy from marketing savvy, and examine three ways of measuring consumer savvy in adults and children. The measurement of human intelligence has a 100 year history and so the researchers’ modest intention at this early stage of exploration is to provide a first view of the conceptual and research issues relating to consumer savvy. The paper also presents early exploratory research on certain aspects of consumer savvy. These include intergenerational effects based on the relationship between the ‘know how’ of a mother and her child. Implications for researchers (academic and practitioners) are examined.
This paper measures patterns of loyalty for variants of a product, such as different pack sizes or flavour. Unlike brands, product variants are functionally highly differentiated. The study undertakes large-scale analysis of panel data and the results shows that product variants can attract markedly different loyalty levels. However, these different loyalty levels are closely related to big differences in the variants' market shares - higher loyalty predictably goes with higher sales. Some variants were found to be very popular, and some are bought by only a fraction of the market. However, neither large nor small variants seem generally to attract a special or unusually loyal customer base. The functional differentiation embodied in product variants therefore affects consumers' preferences but not the persistence of these preferences, i.e. loyalty. The study also illustrates a methodological basis for the analysis of consumer panel data. The mathematical model used here provides benchmarks for the variants' loyalty measures. The study has practical implications in analysing market performance of variants, customer switching behaviour, and understanding the relationship between product differentiation and consumer choice.
Customer satisfaction has become one of the main objectives in all areas of business, especially the tourist trade. One of the most difficult problems is to know how to obtain this satisfaction, which involves identifying customers' needs and desires, and transferring them to our product or service specifications. In order to ascertain the consumer voice, we can ask consumers directly, or thy to deduce their requirements by indirect methods. Statistical design of experiments (SDE) is considered to be a powerful tool for evaluating the revealed importance that not only shows the weight of the most relevant aspects but also that of their interactions. The aim of this paper is to show SDE's application in designing a tourist route. It also makes suggestions and offers directions for future applications, focusing in particular on marketing services. Postprint (published version)
Using information effectively has become a critical determinant for gaining competitive advantage and enhancing business performance. The type and extent to which market research information is used can play a significant role in a firm's level of performance. Surprisingly, little empirical research has been conducted on the usefulness of market research. This paper examines the prevalence of type ('background' and 'decision' research) and perceived usefulness of market research commissioned for enhancing business performance. Information relating to 6036 research projects collected from 68 organisations was reviewed, and a sample of 1550 market research projects was selected for the study. The data were collected by personal interviews and a mail questionnaire relating to 1550 projects on four dimensions of 'usefulness' (overall usefulness, actionable, value and market understanding) and on respondents' level of 'involvement' on those projects. 'Background research' predominates over 'decision research' as a research activity, but was regarded as less useful by managers over the first three dimensions of usefulness. This result was not compromised by the extent of manager involvement. The result was more marked when the dimensionality of the ratings was studied using a factor analysis. The study has produced evidence that if the current emphasis on 'background research' were to shift to 'decision research' then market research would be deemed more useful by managers.
Previous research on ethnocentrism and lifestyle has focused on attitudinal segmentation. However, consumer attitudes may not always be consistent with the actual purchasing decision. Since behavioural intentions are more proximal predictors of behaviours than attitudes, segmenting markets using purchasing intentions might be more appropriate. The purpose of this study is to use purchasing intention to examine whether lifestyle and ethnocentrism can be useful indicators in segmenting foreign and domestic food markets. Data were collected from 1856 households in Turkey. Ethnocentrism, lifestyle (with its dimensions of fashion consciousness, cost consciousness, health consciousness, and craftsmanship) and demographics proved to be valid instruments in segmenting domestic and foreign food markets. The findings have implications both for foreign marketers who operate in or plan to enter the emerging Turkish food industry, and for domestic operators.
Since the publication of Churchill's (1979) paper in which he proposed a 'paradigm' for the construction of multi-item scales, scholars have developed a considerable number of such scales designed to measure a wide variety of marketing phenomena. Despite adherence to the principles set in Churchill's paper and expanded by subsequent authors, experience indicates that the use, or 'borrowing', of existing scales has not been without problems. In this paper we report the findings of an investigation into the impact that the adoption of different scales has on the structural relationship of latent variables. The results lead to the conclusion that the underlying principles or content validity of scales should be examined before being employed in subsequent studies. This practice should be followed even in the case of the most carefully developed and tested multi-item scales.
Theory and past research suggests that greater levels of consumer involvement and product usage lead to higher levels of word of mouth (WOM). This paper presents some tests of hypotheses related to product usage and WOM, based on secondary consumer panel data from five fmcg product trials. The main findings are that brand usage range within a product category has a pervasive effect on pre-trial intentions to recommend the trialled product, as well as the actual number of WOM conversations generated by the trial and their effectiveness (the rate of attitudinal conversion based on interest generated). Frequency of product use only significantly affects the number of WOM conversations. Second, compared to non-users, being a loyal user of the trialled product (having used the brand more frequently than other brands) has a negative effect on WOM effectiveness, while non-loyal users' WOM is more effective compared to that of loyal users. The study thereby provides more evidence that loyal users are not necessarily the best targets of WOM marketing campaigns, and suggests that research on the interaction between involvement or product usage and loyalty in relation to firm-generated WOM may be an interesting area of further research.
Big data is here for some and coming for many. It promises access to new knowledge along with some challenges, but let's not forget the important lessons of the past to ensure that we are advancing knowledge and making the right decisions from the data we have. In this paper, we submit that marketing's emphasis on statistical significance is misplaced, especially in the new world of big data. We include case examples to demonstrate how statistical significance is easy to find, but not necessarily important. We will also discuss the alternative route for generating robust knowledge. Specifically, we espouse the tradition pioneered by Andrew Ehrenberg of Many Sets of Data (MSoD) and descriptive models as the way to advance marketing science, and as a solid foundation for data interpretation in market research studies. We offer insights for market research practitioners and marketers alike, to ensure they are getting the best from their data for robust marketing decision-making.
More information is available from single source panels than is often realised. This includes descriptions of the category and of the brand, and the associations between brand share and price, demographics, weight of viewing and recent viewing. Data can be aggregated into weeks and normal time series modelling compared with the disaggregate findings; the latter seem to be the more sensitive. Reasons for the brand choice at each purchase occasion can be studied by multivariate regression. These include the shopper's loyalty to the brand, its relative price, a trend term, and recent advertising for the brand and for its competitors measured by adstock. Short-term advertising effects have been seen at two to 28 days half life for various brands; no effects have been found for some others. Competitors' adverse effects may be larger or smaller than ours. Diminishing returns to higher current advertising pressure can also be measured and are usually slight. A minority of occasions are under high pressure, and most of these are for heavy viewers who are also affected by competitors' activities and often have untypical brand shares. Any bivariate relation between recent advertising exposure and brand choice is potentially affected by purchase/viewing bias, which often occurs, and by other confounding factors, such as price. Such relationships can give misleading indications of advertising effects.
This paper investigates whether a ‘wisdom of the crowd’ approach might offer an alternative to recent political polls that have raised questions about survey data quality. Data collection costs have become so low that, as well as the question of data quality, concerns have also been raised about low response rates, professional respondents and respondent interaction. There are also uncertainties about self-selecting ‘samples’. This paper looks at more than 100 such surveys and reports that, in five out of the six cases discussed, £0.08p interviews delivered results in line with known outcomes. The results discussed in the paper show that such interviews are not a waste of money.