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1 – 10 of over 14000Consumer expectation not only influences purchase decision but also post-purchase satisfaction and word-of-mouth (WOM). This study aims to develop theories of initial expectation…
Abstract
Purpose
Consumer expectation not only influences purchase decision but also post-purchase satisfaction and word-of-mouth (WOM). This study aims to develop theories of initial expectation management by suggesting when it is desirable for new products to raise or lower consumer expectations. It systematically examines the interplay of product value and consumer heterogeneity in the dynamic process of new product diffusion under competition.
Design/methodology/approach
Drawing on traditional diffusion and choice models, this study develops an agent-based model to formalize and analyze how consumers’ initial expectations of a new product influence the interdependent processes of product sales, consumer satisfaction and WOM. The simulation analyses in controlled settings help understand the underlying mechanisms in a stepwise manner.
Findings
The results show that, although the optimal strategy for low-value products is to induce consumer expectations higher than product value, high-value products are better introduced with expectations formed close to it. The results also highlight an important drawback of “under-promising” strategies in reducing the base and volume of WOM. Further, the analysis illustrates how consumer heterogeneities in product valuation and initial expectation affect the effectiveness of expectation management. For high-value products, both heterogeneities reduce the effectiveness of the optimal strategy. For low-value products, however, value heterogeneity enhances the effectiveness, whereas expectation heterogeneity reduces it.
Practical implications
Firms introducing new products should be sensitive to how consumers value the product and form expectations about it. Different from firms that must rely on aggressive advertising to sell inferior products by building up high expectations, those with superior products can rely more on the power of consumer WOM, which is much less costly and thus gives them a competitive advantage. Firms should also pay attention to how diversified the consumers are in product valuation and expectation. The expectation management strategy is more effective when consumers form more similar expectations. Inferior firms may leverage this mechanism to neutralize their disadvantages.
Originality/value
The articulated mechanisms help push forward the research on new product diffusion and consumer expectation management. To the best of the authors’ knowledge, this is one of the first studies to systematically analyze the impact of consumer heterogeneity on the effectiveness of expectation management.
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Kanghyun Yoon and Thanh V. Tran
This paper aims to propose a finite‐mixture brand‐choice model, which relaxes the common dichotomous assumption in market segmentation based on consumer loyalty. The model can be…
Abstract
Purpose
This paper aims to propose a finite‐mixture brand‐choice model, which relaxes the common dichotomous assumption in market segmentation based on consumer loyalty. The model can be used to estimate the optimal number of consumer segments and capture both across‐ and within‐household heterogeneity in consumers' evolutional patterns of loyalty behaviors.
Design/methodology/approach
The proposed model is empirically calibrated on a scanner panel data of two product categories, i.e. liquid detergent and toilet tissue obtained from the ERIM scanner panel of AC Nielsen.
Findings
Empirical results suggest that: the dichotomous classification of consumers into loyal and non‐loyal groups is sub‐optimal in capturing the heterogeneity in consumer loyalty. Two evolutional patterns of loyalty behaviors exist, showing that past experience with a particular brand may either increase or decrease the current level of loyalty, and consumers' sensitivity to various marketing variables differs between repeat and switching decisions (i.e. within‐household heterogeneity).
Research limitations/implications
The proposed model does not capture consumers' inertia/variety‐seeking tendencies. Furthermore, it does not account for the role of scale parameter in capturing consumer heterogeneity.
Originality/value
This study contributes to the stream of research on consumer loyalty and provides important marketing implications for practitioners in designing effective targeting programs as well as attraction/retention strategies.
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Joonwook Park, Priyali Rajagopal, William Dillon, Seoil Chaiy and Wayne DeSarbo
Joint space multidimensional scaling (MDS) maps are often utilized for positioning analyses and are estimated with survey data of consumer preferences, choices, considerations…
Abstract
Purpose
Joint space multidimensional scaling (MDS) maps are often utilized for positioning analyses and are estimated with survey data of consumer preferences, choices, considerations, intentions, etc. so as to provide a parsimonious spatial depiction of the competitive landscape. However, little attention has been given to the possibility that consumers may display heterogeneity in their information usage (Bettman et al., 1998) and the possible impact this may have on the corresponding estimated joint space maps. This paper aims to address this important issue and proposes a new Bayesian multidimensional unfolding model for the analysis of two or three-way dominance (e.g. preference) data. The authors’ new MDS model explicitly accommodates dimension selection and preference heterogeneity simultaneously in a unified framework.
Design/methodology/approach
This manuscript introduces a new Bayesian hierarchical spatial MDS model with accompanying Markov chain Monte Carlo algorithm for estimation that explicitly places constraints on a set of scale parameters in such a way as to model a consumer using or not using each latent dimension in forming his/her preferences while at the same time permitting consumers to differentially weigh each utilized latent dimension. In this manner, both preference heterogeneity and dimensionality selection heterogeneity are modeled simultaneously.
Findings
The superiority of this model over existing spatial models is demonstrated in both the case of simulated data, where the structure of the data is known in advance, as well as in an empirical application/illustration relating to the positioning of digital cameras. In the empirical application/illustration, the policy implications of accounting for the presence of dimensionality selection heterogeneity is shown to be derived from the Bayesian spatial analyses conducted. The results demonstrate that a model that incorporates dimensionality selection heterogeneity outperforms models that cannot recognize that consumers may be selective in the product information that they choose to process. Such results also show that a marketing manager may encounter biased parameter estimates and distorted market structures if he/she ignores such dimensionality selection heterogeneity.
Research limitations/implications
The proposed Bayesian spatial model provides information regarding how individual consumers utilize each dimension and how the relationship with behavioral variables can help marketers understand the underlying reasons for selective dimensional usage. Further, the proposed approach helps a marketing manager to identify major dimension(s) that could maximize the effect of a change of brand positioning, and thus identify potential opportunities/threats that existing MDS methods cannot provides.
Originality/value
To date, no existent spatial model utilized for brand positioning can accommodate the various forms of heterogeneity exhibited by real consumers mentioned above. The end result can be very inaccurate and biased portrayals of competitive market structure whose strategy implications may be wrong and non-optimal. Given the role of such spatial models in the classical segmentation-targeting-positioning paradigm which forms the basis of all marketing strategy, the value of such research can be dramatic in many marketing applications, as illustrated in the manuscript via analyses of both synthetic and actual data.
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MengQi (Annie) Ding and Avi Goldfarb
This article reviews the quantitative marketing literature on artificial intelligence (AI) through an economics lens. We apply the framework in Prediction Machines: The Simple…
Abstract
This article reviews the quantitative marketing literature on artificial intelligence (AI) through an economics lens. We apply the framework in Prediction Machines: The Simple Economics of Artificial Intelligence to systematically categorize 96 research papers on AI in marketing academia into five levels of impact, which are prediction, decision, tool, strategy, and society. For each paper, we further identify each individual component of a task, the research question, the AI model used, and the broad decision type. Overall, we find there are fewer marketing papers focusing on strategy and society, and accordingly, we discuss future research opportunities in those areas.
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Jordi Lopez-Sintas, Giuseppe Lamberti and Pilar Lopez-Belbeze
This article explores the heterogenous social mechanisms that drive responsible environmental behaviours by investigating differences in the mean effect of the psychosocial…
Abstract
Purpose
This article explores the heterogenous social mechanisms that drive responsible environmental behaviours by investigating differences in the mean effect of the psychosocial determinants of the intention to buy organic foods.
Design/methodology/approach
Using data for a representative sample of the Spanish population, we estimated the mean effect of the constructs represented in the responsible environmental behaviour (REB) theory that affect sustainable food consumption, and examined the social mechanisms that may explain heterogeneity in the mean effect of those constructs. Confirmatory factor analysis, linear regression, and latent class regression were used in the analysis.
Findings
We found that the effect of REB’s psychosocial constructs varied significantly, demonstrating social heterogeneity in the estimated average effect. We identified different social mechanisms that explain variations in organic food purchase intentions: environmental attitudes and social norms shape these intentions among socioeconomically privileged consumers, whereas personal norms shape these intentions among less socially advantaged consumers.
Originality/value
Our research contributes to the literature by highlighting the existence of differing social mechanisms explaining organic food purchase intentions. The uncovering of three social mechanisms explaining differences in the mean effect of factors driving those intentions provides valuable insights with regard to both further developing a holistic framework for responsible environmental behaviours and developing new public policies and marketing strategies aimed at improving sustainable food consumption.
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María Fuentes-Blasco, Beatriz Moliner-Velázquez and Irene Gil-Saura
The literature recognizes the need to study differences in consumer behavior in highly competitive and dynamic markets. In this paper, the authors look at how the heterogeneous…
Abstract
Purpose
The literature recognizes the need to study differences in consumer behavior in highly competitive and dynamic markets. In this paper, the authors look at how the heterogeneous evaluation of retailing influences customer satisfaction and loyalty. The purpose of this paper is to analyze unobserved heterogeneity on customer value dimensions perceptions in retail establishments, and their potential effects on positive forms of behavioral outcomes considering customer satisfaction as a mediating variable.
Design/methodology/approach
On a sample of 820 retail customers, the authors apply a finite mixture structural equation modeling that analyzes unobserved heterogeneity simultaneously. In this model, the authors study the influence of heterogeneous perceptions of excellence, efficiency, entertainment and aesthetics on customer satisfaction and of satisfaction on word-of-mouth (WOM) referral and WOM activity.
Findings
The results show two latent segments where the intensity of causal relations varies, which means that the effect of value dimensions and satisfaction are over or underestimated when heterogeneity is ignored.
Originality/value
The main value of the paper has been to analyze the potential heterogeneity of value dimensions (intravariable approach), and their links with satisfaction and some dimensions of loyalty (intervariable approach). Customer heterogeneity must be studied to understand the satisfaction process and WOM responses in order to design more efficient and effective relationship marketing strategies.
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The purpose of this paper is to apply a very simple but powerful analysis of the variance‐covariance matrix of individual best‐worst scores to detect which attributes are…
Abstract
Purpose
The purpose of this paper is to apply a very simple but powerful analysis of the variance‐covariance matrix of individual best‐worst scores to detect which attributes are determining utility components and drive distinct consumer segments.
Design/methodology/approach
First an analysis of variance and covariance is used to find attributes which are perceived to have different importance by different consumers and which jointly drive consumer segments. Then we model consumer heterogeneity with Latent Clustering and identify utility dimensions of on‐premise wine purchase behaviour with a principal component analysis.
Findings
Four consumer segments were found on the UK on‐premise market, which differ in the relative strength of five wine choice utility dimensions: ease of trial, new experience, restaurant advice, low risk food matching and cognitive choice. These segments are characterised by sociodemographics as well as wine and dine behaviour variables.
Research limitations/implications
Attributes with high variance signal respondents’ disagreement on their importance and indicate the existence of distinctive consumer segments. Attributes jointly driving those segments can be identified by a high covariance. Principal component analysis condenses a small number of behavioural drivers which allow an effective interpretation and targeting of different consumer segments.
Practical implications
This paper's analysis opens new doors for marketing research to a more insightful interpretation of best‐worst data and attitude scales. This information gives marketing managers powerful advice on which attributes they have to focus in order to target different consumer segments.
Originality/value
This is the first study considering individual differences in BW scores to find post hoc segments based on revealed differences in attribute importance.
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The thought and rationale of sustainable competitive advantage in strategy are significantly influenced by the Schumpeterian models of dynamic competition in IO and evolutionary…
Abstract
Purpose
The thought and rationale of sustainable competitive advantage in strategy are significantly influenced by the Schumpeterian models of dynamic competition in IO and evolutionary economics. Yet, most analytical accounts of sustainable competitive advantage fail to explain how firms' investment choices influence, and are simultaneously influenced by, the co‐evolution of “external” industry competition and “internal” firm competences. This paper aims to contribute to the development of a theory of endogenous market structure in strategy.
Design/methodology/approach
Two alternative assumptions are developed – concerning temporally heterogeneous firm investment strategy – that lie central to a proposed behavioral theory of endogenous market structure. Additionally, a theoretical description is provided of the endogeneity of the demand‐side determinants of firm investment strategy and industrial market structure. Finally, guidelines are provided for empirical application of [incorporating] the alternative assumptions and theoretical arguments.
Practical implications
It is expected that the theoretical arguments in the paper will influence strategy scholars to develop dynamic models of firm performance that render themselves amenable to sound empirical analyses.
Originality/value
The paper contributes towards developing a theory of endogenous market structure in strategy.
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This study aims to explore optimal pricing strategies for innovations with direct network externalities – the effect that the number of adopters of an innovation has on the…
Abstract
Purpose
This study aims to explore optimal pricing strategies for innovations with direct network externalities – the effect that the number of adopters of an innovation has on the utility of the innovation to other potential adopters. Examples of such innovations are fax machines, e‐mail, cellular phones, and software programs such as word processors. The success of these innovations requires a minimum number of adopters.
Design/methodology/approach
The paper uses agent‐based modeling and simulation.
Findings
The relationship between price and net present value (NPV) of revenue resembles an asymmetric inverse U‐shape. A low‐pricing strategy outperforms high‐pricing, while a moderate‐pricing strategy outperforms both low‐ and high‐pricing strategies. Moreover, heterogeneity of consumer price sensitivity positively affects the NPV of sales.
Practical implications
Pricing durable new products with network externalities is more challenging than other types of innovations. The results indicate that firms can maximize their NPV by adopting a moderate pricing strategy. Moreover, firms must consider heterogeneity of consumer price sensitivity along with the market price elasticity when making pricing decisions. Detailed strategic implications and recommendations are discussed.
Originality/value
Several recent studies have called for examining pricing strategies for new products with network externalities. The study findings challenge the common wisdom that a penetration pricing strategy is an optimal approach for durable products with network externalities. Moreover, while other studies have highlighted the importance of market price elasticity, extensive simulation experiments conducted in this study show that heterogeneity of consumer price sensitivity is an important factor that must be considered. Finally, the study presents an agent‐based modeling approach for exploring optimal pricing of innovations with network externalities.
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