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In the last decade, PSS (Product/ Service System) emerged as a new effective business model in helping manufacturers increase significantly productivity and customer’s satisfaction, whist minimizing environmental impact. PSS contributes drastically to the development of an innovative transaction trend, in which rather than just providing physical products separately, industrial Companies are more focusing on integrated service offers and customer’s need fulfillment. However, to implement successfully PSS, manufacturers have to overcome many challenges and uncertainties. The uncertainties in the PSS planning phase are related to market, environment or company analysis; reliability, product/service integration, supplier coordination etc in the design and development stages are considered as potential uncertainties. Uncertainty is defined as “State of deficiency of information related to a future event” (Sakao et al., 2009). In which, risks derived from negative side of uncertainties may reduce efficiency of the model or even make the implementation process fail to some extent. If the uncertainty is resolved in a favorable way, risks can be seen as potential business opportunities for the development of PSS Companies. While many Companies already have their own uncertainty management initiative; others just utilize their long time experience to treat uncertainties. Therefore, numerous Companies are seeking a comprehensive uncertainty management framework that could be applicable in most circumstances. In order to fulfill this urgent need, our thesis aimed to develop a holistic framework in order to manage risks occurred in PSS planning, design and development stages. Based on previous valuable PSS researches and useful empirical data collected, our dissertation first determined successfully critical uncertainty factors and potential business opportunities exploited from those. In addition, the research investigated elaborately PSS product quality thresholds and producers’ perception on reliability of their products before constructing a general uncertainty management framework. In which the whole management process based on Active Risk Management philosophy, included Risk Management Planning, Risk Identification, Risk Assessment and Prioritization, Risk Quantification, Risk Response Planning, Risk Tracking and Control were introduced as a helpful guideline to support PSS Companies to treat effectively uncertainties in PSS planning, design and development.

Practitioners and academics have long discussed strategies for brand sales growth. A recent example is an industry debate in which different brand growth strategies were argued: https://www.mmaglobal.com/thegreatdebate (MMA Global & Neustarr, 2021). A central question in this arena is whether a brand should focus on its heavy, light, or non-buyers in its efforts to grow its sales. This study contributes to our knowledge about how sales growth can occur by investigating the potential contribution these three buyer groups can make to any sales gain. Using both, a simulation study and an empirical study of purchases of approximately 12,400 households in the UK, across different brands and categories, we show that almost any brand’s headroom growth potential lies mostly in light or non-buyers of that brand. Even for large brands with high penetration the growth potential of light brand buyers eclipses heavy brand buyers.

The Modern Data Analysis paradigm (Williams, 2021) advocates using multiple methods to address the same research question, which is rarely done in studies of advertising creative effects. In this paper, we apply the MDA paradigm to data from Hartnett, Kennedy, et al. (2016), which coded 158 creative variables for 312 television advertisements with commercially validated short-term sales effectiveness outcomes. We found that many models give higher classification accuracy than the ordinal regression model previously applied, some significantly higher. Importantly, by applying many alternative but equally plausible analytical methods, we can identify creative variables associated with commercial success and have evidence-based confidence that these creative variables are artefacts of the data, and not artefacts of any particular analytical method and its associated assumptions. The findings reveal several alternative creative variables that are consistently associated with sales success across methods, which relate to the timing aspects of visual branding. Refereed/Peer-reviewed

Purpose The study investigates the long-term erosion of repeat-purchase loyalty among consumers who purchase brands in a one-year base period. Design/methodology/approach The study uses a five-year consumer panel of continuous reporters. We identify brand buyers in a base year, then calculate the proportion that fail to buy the brand in later years. We analyse the top 20 brands in 10 consumer goods categories. Findings We find pronounced erosion in repeat-buying over the long-term. The proportion of buyers from a base year that fail to buy in a later year increases steadily over time, from 57% in year 2 to 71.5% by year 5. Moreover, we identify brand and marketing mix factors linked to this over-time customer loss or erosion. Research limitations/implications The study provides evidence that consumers’ propensity to buy particular brands changes over a period of years, even though those brands continue to exhibit a stable market share. This evidence provides a different interpretation than the literature to date, which has viewed purchase propensities as fixed. Practical implications The study finds that store brands and niche brands exhibit lower levels of erosion in their buyer base; that a broad range is associated with lower erosion, and that high price promotion incidence is associated with lower erosion for manufacturer brands. Originality/value Loyalty erosion has been reported before (Ehrenberg, 1988; East and Hammond, 1996) but only over short periods. This study examines the phenomenon over five years, confirms that the rate of erosion does diminish over time, and that it is related to category and brand characteristics, as well as marketing mix decisions.

This article generalizes the well-known negative binomial distribution (NBD) theory to attendance behavior at sporting events. Using data from a large national survey across a range of sporting events in Australia, including Australian football, rugby league, soccer (outdoor), horse racing, motor sports, rugby union, cricket (outdoor), netball (indoor and outdoor), basketball (indoor and outdoor), harness racing, and dog racing, we show that the NBD is very robust in describing sporting event attendance behavior. This result has implications for sporting event marketing activities, such as which attendee segments should be targeted, how to increase ticket sales, as well as predicting future attendance behavior. Refereed/Peer-reviewed

This research examines the retrospective buying behaviour of customers acquired by a new brand, both at category and brand level. New brand launches are risky endeavours for marketers, as many fail to attract a sustainable customer base.We examine new brand launches in six packaged goods categories in the UK,across a wide range of brand and category conditions, including premium brands and private labels. The results show that, in the pre-launch period, buyers of anew brand are more likely to have been heavier (more frequent) category buyers and, where applicable, heavier buyers of a parent brand. However, despite disproportionately drawing from heavy category buyers, the buyers of new launches tend to become only light brand buyers. This suggests that new brands are more likely to ‘slip’ into the repertoire of heavy category or parent brand buyers. This research contributes to our understanding of repertoire formation in packaged goods categories. It also has implications for the pre-testing of new launches and the scheduling of marketing activities. Refereed/Peer-reviewed

This paper compares consumer behavioral brand loyalty in purchasing for on-the-go and for take-home consumption. The study uses two consumer packaged goods datasets from the UK. The first dataset contains actual consumer repeat purchasing of soft-drink brands for on-the-go consumption. The second dataset contains actual consumer repeat purchasing of the same brands for take-home consumption. Using polarization index as a behavioral loyalty measure, estimated from the Beta Binomial – Negative Binomial Distribution, the study finds that consumer loyalty to brands is markedly higher in purchasing for on the go consumption than for take home consumption.

New brand launches are risky endeavors for marketers, as many fail to attract a sustainable customer base. This research examines the buying behavior of customers acquired by a new brand and revisits the theoretical norms of the NBD-Dirichlet model benchmarks. Investigating 40 new brand launches in the UK, across a wide range of brand and category conditions, we find that in the first 12 months, new launches have more, but less loyal buyers than expected from NBD-Dirichlet benchmarks, irrespective of type, price point, or the sales gained by the new launch. Further we find exploratory evidence that new buyers of brands have weaker associations than existing buyers. We propose that the combination of the new experience that lacks distinctiveness in encoding means that the experience of buying the new brand creates weaker memory traces in new buyers and that these buyers need additional marketing reinforcement to consolidate the memory of buying the brand to establish the brand in their ongoing repertoire. Refereed/Peer-reviewed

This study investigates the variation in brand growth and decline across many different product categories. It uses recent consumer panel data from the UK, covering 639 brands across 28 categories, including food, personal care, home care and pet food, over a five-year period from 2008 to 2012. Consistent with the literature, the study finds that most brands in the consumer packaged goods market are stationary, as only 14% of the brands change their market share by more than three points. However, the study discovers that some categories are more dynamic than others. The percentage of brands that change their share by more than three points is different across the categories, varying from 0% to 44%. The study further examines some potential factors that can affect the variation and finds that category penetration and purchase frequency have significant effects on the variation. The lower the category penetration and category purchase frequency, the lower the brand share stationarity. On the other hand, proportion of sales on promotion in the category and new SKU introductions do not have a significant effect on the variation. Refereed/Peer-reviewed

This paper investigates behavioral loyalty of consumers to online grocery retailers over time. The study uses consumer packaged goods data from the UK, one of the most advanced online retailing countries. The data contains actual consumer repeat purchasing of three product categories (soft drinks, toothpaste, and cat food) from four major grocery retailers (Tesco, Asda, Sainsbury’s, and Waitrose) operating online from 2005 to 2014. Using three measures of behavioral loyalty (share of category requirement, repertoire size, and polarization index), the study finds that consumer loyalty to online retailers has declined from 2005 to 2009 and remained stable from 2010 to 2014.

This research confirms empirical patterns about in-store behaviors based on a large number of shops and store visits, specifically 654,000 transactions in 40 supermarkets, hypermarkets, convenience and specialty stores in the USA, UK, China, and Australia. Integrating new data with past findings highlights that: (i) many shopping trips are short; (ii) shoppers typically only cover a small proportion of the store on any trip, and (iii) the heterogeneity of key behavioral measures (store coverage, number of items bought, and trip length) is generalizable across countries, most store formats, and store size. These patterns can help retailers and manufacturers benchmark and predict behavior and provide a base for further theoretical developments.

This paper proposes and validates the negative binomial distribution (NBD) to predict the variation in repertoire size (the number of brands purchased by a consumer in a specific time period) within a category. From a managerial perspective, the variation is crucial for brand managers who would like to know the nature and intensity of competition that is facing their brands. Empirical findings across multiple datasets from UK consumer packaged goods demonstrate that the NBD model predicts variations in repertoire size very well in different time periods (1 year, 18 months and 3 years), and different buyer groups (light and heavy category buyers). The paper then suggests a simple method to predict those who are brand exclusively loyal, those who are loyal to a few brands, and those who are diversified to buy multiple brands, based on very little information such as category and brand penetrations, using the parameters of the NBD model. Refereed/Peer-reviewed

The negative binomial distribution (NBD) has been widely used in marketing for modeling purchase frequency counts, particularly in packaged goods contexts. A key managerially relevant use of this model is Conditional Trend Analysis (CTA)-a method of benchmarking future sales utilizing the NBD conditional expectation. CTA allows brand managers to identify whether the sales change in a second period is accounted for by previous non-, light, or heavy buyers of the brand. Although a useful tool, the conditional prediction of the NBD suffers from a bias: it under predicts what the period-one non-buyer class will do in period two and over predicts the sales contribution of existing buyers. In addition, the NBD's assumption of a gamma-distributed mean purchase rate lacks theoretical support-it is not possible to explain why a gamma distribution should hold. This paper therefore proposes an alternative model using a log-normal distribution in place of the gamma distribution, hence creating a Poisson log-normal (PLN) distribution. The PLN distribution has a stronger theoretical grounding than the NBD as it has a natural interpretation relying on the central limit theorem. Empirical analysis of brands in multiple categories shows that the PLN distribution gives better predictions than the NBD. Refereed/Peer-reviewed

Purpose This paper aims to extend the known boundary conditions of the negative binomial distribution (NBD) model, and to test the applicability of conditional trend analysis (CTA) – a key method to identify whether changes in overall sales are accounted for by previous non-buyers, light buyers or heavy buyers – in industrial purchasing situations. Design/methodology/approach The study tested the NBD model and CTA in an industrial marketing context using a 12-month data set of purchases from an Australian supplier of a range of industrial plastic resins. Findings The purchase data displayed a good NBD fit; the study therefore extends the known boundary conditions of the model. The application of CTA provided second-period purchasing frequency estimates showing no significant difference from actual data, indicating the applicability of this method to industrial purchasing. Research limitations/implications Data relate to just one supplier. Further research across several industries is required to confirm the generalizability and robustness of NBD and CTA to industrial markets. Practical implications Marketing decisions can be improved through appropriate analysis of customer purchasing data. However, without access to equivalent competitor data, industrial marketers are constrained in benchmarking the purchasing patterns of their own customers. The results indicate that use of the NBD model enables valid benchmarking for industrial products, while CTA would enable appropriate analysis of purchases by different classes of customer. Originality/value This paper extends the known boundary conditions of the NBD model and provides the first published results, indicating the appropriateness of CTA to predict purchasing frequencies of different industrial customer classes.

Price promotions dominate the modern grocery retail environment. This paper documents the prevalence and nature of these price promotions (i.e., deal types and discount depths) in the United States and United Kingdom. The analysis comprises of 23 categories across five retail chains. One of the key findings is that multiple-unit promotions – deal types that have been under-researched – account for approximately half of all price promotion activity. The analysis also identifies an increase in price promotion prevalence since the Global Financial Crisis, predominantly driven by national brand promotions. This research carries important implications for the alignment of academic research with common industry practices Refereed/Peer-reviewed