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The satisfaction and loyalty research argues that customer satisfaction is an antecedent to share of wallet (SOW). The double jeopardy view, however, argues that satisfaction and SOW levels are driven exclusively by penetration levels. Customer satisfaction and penetration, however, are not always positively related. The purpose of this paper is to explore the relevance and validity of these two divergent perspectives to creating growth in customer share of spending.

The authors examine a series of models evaluating the impact of both the relative penetration of a brand, and the satisfaction ratings of its customers on SOW using data covering 11 industry sectors, 188 brands, and 4,263 customers.

The authors find that part of the problem in reconciling these two views has been in how satisfaction is measured and analyzed. When using absolute satisfaction ratings of the firm/brand, the explanatory power of satisfaction on SOW is very weak at both the individual and firm level. When using satisfaction metrics relative to other competing brands, however, satisfaction is a strong predictor of customers’ share of category spending.

As predicted by double jeopardy, penetration is a strong predictor of firm-level SOW, but has almost no explanatory power at the individual level.

Managers need to focus on both improving penetration/reach and becoming the preferred brand in a customer’s usage set.

The research examines if (and if yes, how) satisfaction and penetration contribute to customers’ SOW allocations both at the individual and brand level.

Calls for empirical and theory-based outcome measures in the place marketing literature are made more pressing as policymakers manage post-COVID high street recovery. This study aims to evaluate how knowledge of repeat buying established in the consumer marketing domain might be adapted to benchmark place marketing effectiveness, applying the Law of Double Jeopardy to capture the predictable relationship between footfall and visit frequency on competing high streets.

The authors match footfall and survey data collected simultaneously on nine local high streets in one London borough to ask if a predictable Double Jeopardy relationship exists. The authors then test the theoretical assumptions of independence that underpin the Law in patterns of switching; the predictable distribution of regular, infrequent and new visitors; and the absence of user segmentation.

The authors observe that Double Jeopardy constrains behavioural outcomes, that a simple model fits high street footfall data well and that its theoretical assumptions are supported.

This paper makes several practical and theoretical contributions. The authors demonstrate a method to model expected repeat visit frequency from footfall density and elaborate footfall data into its frequency classes. The authors also locate the effects of loyalty over time within existing knowledge of spatial competition for high street patronage and demonstrate how place marketing insights can be derived from applications of this useful law.

The theory of double jeopardy (DJ) is shown to hold across broad ranging geographies and physical product categories. However, there is very little research appertaining to the subject within an online environment. In particular, studies that investigate the presence of DJ and the contrasting view point to DJ, namely, that of negative double jeopardy (NDJ), are lacking. This study aims to contribute to this identified research gap and examines the presence of DJ and NDJ within a product category, utilising data from Twitter.

A total of 354,676 tweets are scraped from Twitter and their sentiment analysed and allocated into positive, negative and no-opinion clusters using fuzzy c-means clustering. The sentiment is then compared to the market share of brands within the beer product category to establish whether a DJ or NDJ effect is present.

Data reveal an NDJ effect with regards to original tweets (i.e. tweets which have not been retweeted). That is, when analysing tweets relating to brands within a defined beer category, the authors find that larger brands suffer by having an increased negativity amongst the larger proportion of tweets associated with them.

The clustering approach to analyse sentiment in Twitter data brings a new direction to analysis of such sentiment. Future consideration of different numbers of clusters may further the insights this form of analysis can bring to the DJ/NDJ phenomenon. Managerial implications discuss the uncovered practitioner’s paradox of NDJ and strategies for dealing with DJ and NDJ effects.

This study is the first to explore the presence of DJ and NDJ through the utilisation of sentiment analysis-derived data and fuzzy clustering. DJ and NDJ are under-explored constructs in the online environment. Typically, past research examines DJ and NDJ in separate and detached fashions. Thus, the study is of theoretical value because it outlines boundaries to the DJ and NDJ conditions. Second, this research is the first study to analyse the sentiment of consumer-authored tweets to explore DJ and NDJ effects. Finally, the current study offers valuable insight into the DJ and NDJ effects for practicing marketing managers.

This study aims to understand the degree of predictability and value in analyzing consumer purchase patterns in the US wine retail market. The study considers whether brands in US wine retailing follow the well-established Duplication of Purchase Law and Double Jeopardy Law.

Over 20,000 customer panel wine purchases were analyzed from a number of locations within a supermarket chain based on the West Coast of the USA. Cross-purchasing behavior for the top 20 wine brands by market penetration was analyzed to assess whether the well-established Duplication of Purchase Law and Double Jeopardy Law hold up in this wine retail setting in the USA. The degree of predictability and the existence of anomalies in expected cross-purchasing behavior were identified in the analysis.

Results confirmed a Double Jeopardy pattern and that wine cross-purchasing patterns for the most part followed the Duplication of Purchase Law. However, exceptions to these patterns were found, which indicated areas in need of managerial attention due to the potential to remedy, develop or monitor the most prominent variations between predicted and realized cross-purchasing behavior. Repeated identification of variations has been identified in other product categories, known as market partitions.

Although it is commonly believed that wine is a unique product category, the results of this study demonstrate that consumer behavior toward wine is similar to other fast-moving consumer goods. The exceptions suggest that while similar consumer purchase patterns are evident, consumers are more likely to cross purchase wine brands and grape types more than would be expected given Duplication of Purchase Law benchmarks.

The Bedford Committee (1986) and the Accounting Education Change Commission (AECC, 1990) have strongly supported, along with practicing accountants, the use of innovative teaching techniques. Innovations involve active student participation and focus on development of critical thinking, communication, and technology skills. This paper extends prior research and describes how spreadsheet software is used to develop Jeopardy! boards to teach governmental accounting and enhance non-technical skills. Student survey results demonstrate support for use of a computer-based Jeopardy! game as a learning tool and a vehicle to self-assess learning. Written communication and teamwork skills are emphasized as students develop content in groups.

Compared with the large brands, not only do the small brands attract fewer customers but also their customers buy them less frequently. This twin disadvantage of the less popular brands is termed “double jeopardy” (DJ). Earlier studies on the DJ effect have generally explained this as a behavioral phenomenon relating to the size structure of the market. This article aims to argue that the DJ effect is also influenced by the relationship between consumer choice antecedents and consumer buying behavior.

Using consumer attitudinal and behavioral data on various toothpaste brands collected by a leading consumer goods company, it is shown that small brands are jeopardized in terms of individual‐level choice antecedents of both loyal and switching consumers. In particular, small brands are further jeopardized for brand=switching consumers in terms of weaker attitude‐choice relationship.

The research findings have significant managerial implications. the research suggests that double jeopardy of small brands may not be as irreversible phenomenon posited. A more in‐depth understanding of the individual‐level antecedents of consumer choice should help small brands to develop innovative offensive and defensive strategies aimed at favorable individual choice antecedents of loyal and switching consumers. For example, it may be prudent for a small brand to concentrate on a selected few segments (such as brand‐loyal segments) instead of spreading scarce brand resources across scattered promotion and distribution strategies.

Examines the choice antecedents of consumers who either are loyal to a brand or are brand switchers.

Increasing and maintaining the population’s consumption of healthful food may hinder the global obesity pandemic. The purpose of this paper is to empirically test whether it is possible for healthful sub-brands to achieve higher consumer behavioural loyalty than their less healthful counterparts.

The study analysed three years of consumer panel data detailing all purchases from five consumer goods categories for 15,000 UK households. The analysis uses best-practice techniques for measuring behavioural loyalty: double jeopardy, polarisation index, duplication of purchase and user profile comparisons. Each sub-brand’s healthfulness was objectively coded.

Despite the level of healthfulness, all sub-brands have predictable repeat purchase patterns, share customers as expected and have similar user profiles as each other. The size of the customer base, not nutrition content, is, by far, the biggest determinant of loyalty levels.

Consumers do not show higher levels of loyalty to healthful sub-brands, or groups of healthful sub-brands. Nor do they buy less healthful sub-brands less often (as a “treat”). There are also no sub-groups of (health conscious) consumers who would only purchase healthful options.

Sub-brands do not have extraordinarily loyal or disloyal customers because of their healthfulness. Marketers need to focus on growing sub-brands by increasing their customer base, which will then naturally grow consumer loyalty towards them.

This research brings novel evidence-based knowledge to an emerging cross-disciplinary area of health marketing. This is the first study comparing behavioural loyalty and user profiles towards objectively defined healthful/less healthful sub-brands.

This research evaluates attitude — behaviour relationships in the wine market by examining consumer attitudes towards six brands of white wine. This is done using a Likert style questionnaire, including brand ‘usage’ questions on a sample of 110 respondents who are a representative sample of wine consumers. The research evaluates consumer attitudes towards brand attributes, and examines the relationship they have with the usage patterns and market share of the brands. The research is a replication with extension of Ehrenberg's studies, in that a scaling technique to examine the strength of the attributes is used to further examine the attitude‐behaviour relationships. The results of the study find support for Ehrenberg's theory that there is a strong relationship between brand usage and positive attitudes towards the brand, and current brand usage and claimed intentions to buy in the future. Furthermore, there is a pattern of Double Jeopardy showing that among users, positive attitudes are fewer for small brands than big brands. The use of the scaling technique did not obtain more significant detailed information than previously used ‘free choice’ methods. The overriding managerial implication is the importance to generate actual brand ‘trial’ not simply create an image.

The purpose of this paper is to examine the interactive effects of gender and age on evaluations of job applicants. Given the double jeopardy hypothesis, the authors might anticipate that older women would be denigrated most in hiring evaluations. However, given expectations of normative gender behavior, the authors might anticipate that older men would be penalized most for not already having stable employment. This study aims to examine which hypothesis best describes selection biases based on age and gender.

Stimuli depicting male and female job applicants at the various ages were developed. The stimuli were standardized by collecting facial photos of older White men and women at ages 20, 40, and 60, and morphing these faces onto standardized bodies using Adobe Photoshop. Participants viewed six stimuli, one from each age by gender combination, and made evaluations across job relevant dimensions.

Results showed an interaction between age and gender, such that older male applicants were evaluated more negatively than older female and younger male applicants. These findings support for the violation of gender normative behavior hypothesis.

This study has implications for organizational leaders who can use this information to provide training for selection officers concerning biases against older workers and how to avoid them.

Original, novel stimuli are used in an experimental design to examine the effects of age in employment in a standardized manner which controls for extraneous variables such as attractiveness across age.

The purpose of this paper is to identify how fashion and cosmetics e-stores compete and grow to help e-commerce managers set the corresponding marketing strategy. It describes the relevance of customer acquisition and retention to market share as the essential performance metrics.

An empirical generalization approach where patterns in data appearing across studies are described by a mathematical or graphical method is used. To do that, the authors observed real transactional data and the effect of how e-stores benefit from new and returning customers and gain a larger market share. The authors have analysed behavioural data from nearly 124,000 e-commerce customers in two highly popular product categories (fashion and cosmetics) in the size of 10,000,000 euros in sales or more.

Fashion and cosmetics e-stores with more market penetration tend to have a higher market share measured both by the number of total purchases and the number of sales in euro. In other words, market penetration is a solid predictor of market share in all circumstances. Interestingly, no significant difference in loyalty has been observed in relation to market share growth except in the situation where the market partition was excluded from the product category.

The businesses under study derived only from one country and only two product categories were observed. Thus, there is a potential limitation in generalizing the findings to the whole e-commerce market from a geographical and category perspective. The length of the observation period may also play a role as a longer period increases the chance of repeat buying.

E-commerce managers can gain long-term market share growth mainly via higher market penetration (acquisition of new customers) and should avoid misleading overfocus on loyalty tactics (retention of current customers). The study also provides important benchmarks for e-commerce businesses in the fashion and cosmetic categories.

In the market share growth literature, only a handful of studies focus on stores and not on products. Moreover, there is a dominance of fast-moving consumer goods categories. Surprisingly, studies analysing ever-growing e-commerce markets are scarce. Thus, this research is original because it describes, using empirical data, how brands online, at the store level and within the fashion and cosmetics category, grow their market share. It is also one of the few studies that work with real business transactional data.