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The trade marketer is already faced with a high standard of data application in his approach to the buyer/seller relationship. The last thing he needs is an information revolution now. Yet it appears that we are on the verge of a new era of electronic databases with considerable potential advantages for productiveness and profitability. An already sophisticated level of database usage will be further enhanced by the advent of new information sources – retail scanning data, in‐home scanning. However, too much information could be a disadvantage and effective data management will be necessary. Competitive advantage will depend more than ever on the ability to apply these new databases to the marketing process, especially in forecasting future requirements at the macro and micro levels. Therefore mutual co‐operation will be an essential ingredient for the success of the buyer/seller relationship.

The purpose of this paper is to determine how the typical purchasers of products with nutrition symbols differ from other purchasers with respect to socio-demographic characteristics. Furthermore the authors examine if the typical purchaser is similar across six product types in Denmark and in the Netherlands.

The authors estimate probit models using a representative panel of households registering all their daily purchases during a year, three years after the introduction of a nutrition symbol in Denmark and the Netherlands (the Keyhole and the Choices). The purchase data are matched with information about labelling status. Other product and purchase characteristics, such as store-type and organic, are controlled for.

Households with children tend to have a lower probability of purchasing labelled products compared to other household types, while urbanity increases the probability. This holds both across countries and across products. In Denmark education is positively correlated with label purchase, while in the Netherlands it is income. Generally, the observable characteristics of the consumers are poor in explaining the probability of purchasing labelled products which suggests that other aspects as the underlying attitudes and general health awareness may be of greater importance in identifying these consumers.

There is a lack of studies analysing the effect of front-of-pack symbols on households’ product choices based on observed data as most previous studies are based on stated observation or purchase intentions.

This study aims to identify the major factors influencing the consumers to prefer milk products and also to analyze the awareness level of the Indian consumers.

In this study, the data is obtained through a structured questionnaire from Indian consumers considering convenience sampling under the nonprobability sampling technique. The consumer preference is explained using a multiple-regression model followed by analysis of variance (ANOVA), which shed insight on the significant differences between the variables that influence consumer preference for dairy products.

Investigation is done to analyze the factors influencing the consumers' buying behavior toward milk and its products. The results showed that quality, health consciousness, price and availability are the most influencing factors to buy milk products. Quantity of milk showed a significant relationship between age, monthly income and family size.

This study helps marketing managers to frame the marketing strategies based on consumer preference, quality, health consciousness, price and availability. The research outcome will not only be advantageous for the entrepreneurial perspective but also takes care of consumer likeliness. Though the research reveals the opinion of Indian consumers, it limits the likeliness of the western world. Because of the scarcity of resources, several dairy products are unexplored, which could pave the future scope of research.

The novelty of this study is to identify the quality, health consciousness, price and availability are the most influencing factors to buy milk products considering ANOVA and the multiple regression model.

The purpose of this paper is to compare prices for fresh tomatoes, potatoes, peppers, and apples at direct-to-consumer sales outlets (e.g. farmers markets, roadside stands, on-farm stores) in the USA to grocery stores and supercenters, while controlling for other attributes.

The author estimates a hedonic regression model to determine price differences at direct sales outlets, grocery stores, and supercenters in various regions and seasons of the year. The analysis is conducted using 2006 Nielsen Homescan data. Other product and market attributes are also considered, along with characteristics of the household sample.

Prices at direct sales outlets are lower than grocery store prices throughout the year and across the USA. Prices at direct sales outlets for some product/location/season combinations were higher than or comparable to supercenter prices.

Future research is needed to examine how price differences may vary across the various types of direct marketing outlets.

Few studies have examined price differences between direct sales outlets and conventional retail stores. No studies have used nationally representative data to analyze these price differences across produce type, season, and geographic areas.

There is a significant pressure on consulting businesses to produce innovative solutions and to assist their clients in producing innovative solutions for their organizational problems as well. In addition to that challenging need to innovate for survival and competition, as other contemporary firms, consultancies must face the global changes brought by the outbreak of the coronavirus infection since 2019. This qualitative pilot study aimed at exploring the impact of the coronavirus disease 2019 (COVID-19) pandemic on the approaches to innovation in the consulting industry.

Triggered from the literature gap on approaches to innovation in consultancies during the unprecedented COVID-19 pandemic, a grounded theory approach was used to generate a theoretical explanation of how the COVID-19 is affecting the strategies and approaches of businesses in harnessing innovation opportunities from the perspectives of four professionals from an information technology (IT) consultancy in the USA.

The findings of this pilot study showed that organizational leaders' increased responsiveness, a Job-To-Be-Done strategy, organizational support and team adaption are the keys to harvesting dynamic capabilities for better competition, even during global environmental changes.

This implies that managers remain the main actors in a firm's efforts to harvest dynamic capabilities. Innovation strategists, business leaders and policymakers can confidently work together to implement novel and flexible work settings that integrate both social and economic advancements.

Theoretical implications support the sustainable innovation strategy concepts and the Job-To-Be-Done theory. Finally, the substantive theory from this pilot study lays the ground for future research on approaches to innovation in the consulting industry.

This study responds to the call of Fader and Hardie for more research on buyer behaviour toward stock keeping units (SKU). This paper aims to examine whether different SKU‐based product variants appeal to buyers with different demographic characteristics.

This study examines the product variants (such as size, formulation, type) of a range of brands in six consumer goods categories. The authors calculate and compare the market share of each variant within each demographic group. If a variant has a higher market share within a specific demographic group than the overall average, this indicates segmentation at the product variant level.

The findings show that there are many differences in the market shares of product variants among different demographic groups of buyers. The largest differences are found extensively within the age and employment status variables.

Functionally different product variants tend to draw different demographic‐based segments of buyers, which has not been previously shown.

The purpose of this paper is to examine gender differences in store loyalty and how those differences evolve with age.

Data for the study were collected in a survey of 32,054 shoppers in more than 50 grocery stores belonging to the same chain. In total, 20 satisfaction items were factor-analysed, resulting in four satisfaction factors. A logistic regression with store exclusivity as the dependent variable was then run to test the research hypotheses.

This study finds that men are more loyal than women to the store chain, while women are more loyal than men to individual stores. Women’s loyalty is more influenced by their satisfaction with interaction with store employees, while for men loyalty is more influenced by satisfaction with impersonal dimensions. Store loyalty increases with age, an effect that cannot be explained solely by declining mobility and cognitive impairment.

This research examines declared behavioural practices rather than actual behaviour. However, in view of the high frequency of purchases in the retail category examined, and also because of the large sample of over 50 different stores, declared practices should be highly correlated with actual behaviour.

Results from satisfaction surveys should be interpreted differently for men and women. Loyalty programmes may want to adapt their approach, to incorporate gender differences into their loyalty reinforcing measures.

This paper should also help to a better understanding of loyalty programs for both men and women, younger and older people.

This is the first demonstration from an in store customer survey that the shopping experience drives store loyalty differently for men and women.

JUST a year ago the Bullock Report was published with a ffurry of trumpets. We expressed our opinion on it then and we have no reason to change it now.

The purpose of this paper is to present and explain the identity theft cycle. The identity theft cycle explains how a perpetrator goes through various stages of confidence and experimentation when stealing an individual's identity.

The paper takes a conceptual approach by first describing identity theft in detail and then discussing the seriousness of identity theft for consumers today. The paper then presents and explains the identity theft cycle in greater detail including the stages of discovery, action, and trial.

The paper provides evidence to suggest that if identity theft is detected early, consumers can protect themselves from the vast and difficult consequences of identity theft.

This paper fulfills an important area of research by providing basic information about the nature of identity theft. This paper also discusses the various ways that perpetrators steal consumers' information, as well as teaches consumers how to proactively protect themselves from identity theft.

The purpose of this paper is to examine the effects of distribution channels on demand for apparel, home textiles, and other textiles (including shoes) in urban China.

The estimation procedure used in this study is implemented in three steps: first, the price/unit value information is estimated; second, the parameters for a set of demand systems are estimated; and third, the J‐test and likelihood ratio testing are used to determine the most suitable model for the data set.

The results indicate that households spend more on apparel than home textiles and other textile products if they purchase textile products from small stores. It also indicates that they would spend more on home textiles and other textiles if they purchase from chain stores and supermarkets.

The estimation of Chinese textile consumption presents a significant challenge to both academic researchers and industry, due to China's large population, income inequality, different consumption channels, and other related issues. First, the results presented in the paper provide a clear indication for textile producers, exporters, and others to choose their distribution channels to target specific customers; second, the disaggregated textile expenditure and price elasticity estimates from this article can be used in various analytical procedures (i.e. simulation models) to evaluate the welfare effects of domestic policies and international trade policies. Quantification of the welfare impacts of domestic policies and international trade policies would be more meaningful if disaggregate textile elasticity estimates are used in simulation models.