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Sentiment is fundamental to human communication. Countless marketing applications mine opinions from social media communication, news articles, customer feedback, or corporate communication. Various sentiment analysis methods are available and new ones have recently been proposed. Lexicons can relate individual words and expressions to sentiment scores. In contrast, machine learning methods are more complex to interpret, but promise higher accuracy, i.e., fewer false classifications. We propose an empirical framework and quantify these trade-offs for different types of research questions, data characteristics, and analytical resources to enable informed method decisions contingent on the application context. Based on a meta-analysis of 272 datasets and 12 million sentiment-labeled text documents, we find that the recently proposed transfer learning models indeed perform best, but can perform worse than popular leaderboard benchmarks suggest. We quantify the accuracy-interpretability trade-off, showing that, compared to widely established lexicons, transfer learning models on average classify more than 20 percentage points more documents correctly. To form realistic performance expectations, additional context variables, most importantly the desired number of sentiment classes and the text length, should be taken into account. We provide a pre-trained sentiment analysis model (called SiEBERT) with open-source scripts that can be applied as easily as an off-the-shelf lexicon.

PurposeThe Covid-19 pandemic has a strong effect on societies, business and consumers. Governments have taken measures to reduce the spread of the pandemic, such as social distancing and lockdowns. The latter has also resulted in a temporary closure of physical stores for “non-essential” retailing. Covid-19 thus has a profound impact on how people live. The period of relative isolation, social distancing and economic uncertainty changes the way we behave. New consumer behaviors span all areas of life, from how we work to how we shop to how we entertain ourselves. These shifts have important implications for retailers. This paper aims to discuss the potential structural effect on shopping behavior and retailing when Covid-19 measures are no longer needed and society moves back to a normal situation.Design/methodology/approachThe paper synthesizes empirical and conceptual literature on the consequences of COVID-19 and introduces a conceptual framework along with a set of predictions that can be investigated with empirical data.FindingsThis study suggests that Covid-19 shapes both consumer needs and behavior and how retailers respond to these changes. Moreover, it suggests that this will not only affect market outcomes (i.e. retail sales and market share online) but also firm outcomes (i.e. customer experience, firm sales) and importantly the competition between online and offline retailers.Originality/valueIn the conceptual framework, this study aims to advance knowledge on longer-term outcomes (vs immediate outcomes such as panic buying) and how COVID-19 is changing the competitive landscape of retail.

Purpose While extant research has predominantly focused on outcomes of customer satisfaction that benefit the focal firm such as customer engagement behaviors (CEBs), little is done to understand human capital-related outcomes that directly benefit customers and thus benefit the firm indirectly. Drawing on the theory of reasoned action, broaden-and-build theory of positive emotions and human capital theory, this study aims to understand how and why a satisfied customer benefits the firm directly (CEBs) and indirectly (human capital-related outcomes). Design/methodology/approach Following a sequential mixed-methods approach, two studies are conducted in an extended service encounter context (higher education) where customers also constitute key human capital of the service firm. First, a qualitative study is conducted, which is then followed by a quantitative study. Survey data collected from students working as interns in organizations and their immediate managers resulted in 209 “intern–manager” dyads. Findings The findings demonstrate that customer satisfaction on its own does not substantially account for either human capital-related outcomes or CEBs (except word of mouth [WOM]). Both emotional and cognitive mechanisms play key and unique mediating roles in translating satisfaction into outcomes that benefit a service firm directly and indirectly by benefiting its customers. Research limitations/implications While much research demonstrates benefits of customer satisfaction for the focal firm, this research advances our understanding of the novel consequences of customer satisfaction by shedding light on human capital-related outcomes that directly benefit customers. It also aids in explicating prior inconsistent findings on the relationship between customer satisfaction and CEBs by uncovering the underlying mediating mechanisms. Practical implications This investigation provides a deeper understanding of the significance of customer satisfaction by demonstrating how and why satisfied customers increase firm value beyond purchase, for instance, by being direct (through positive WOM) and indirect (through enhanced human capital performance) promoters, consultants (through participation) or investors (through monetary giving). A key implication of this research is that simply enhancing customer satisfaction on its own may not suffice as the findings suggest that satisfaction translates into beneficial outcomes only when satisfaction is channeled toward enhancing customer perceptions of competence and their positive emotions. Originality/value This study contributes to the literature by providing a deeper understanding of how and why customer satisfaction influences outcomes that not only benefit the firm but also its customers in extended service encounter context.

By means of a meta-analysis, we synthesize the findings of over two decades of research from 88 empirical studies regarding four well established and theoretically rooted determinants on consumers’ attitude towards digital advertising: informativeness, entertainment, irritation, and credibility. Among other findings, we show that the effects of these determinants have changed over the past 20 years as the internet has developed. We also find that the effects differ depending on which type of online touchpoint was considered. In particular, we differentiate between the most prominent online touchpoints: email advertising, social media advertising, search engine advertising, web display banner advertising, electronic word-of-mouth communication, and corporate website advertising. Additionally, we extend the well-established determinants by more recent ones accounting for the ongoing digitalization and advances in online touchpoints (i.e. personalization, privacy concerns and interactivity). We also derive important managerial implications and several fundamental directions for future research.

Previous research shows mixed findings on whether stress increases or decreases novelty seeking. In three studies, using both archival and experimental data, and including more than 61,000 consumers from over 55 different countries, we show that it can do both, albeit for consumers differing in “life history strategies” (LHSs), that is, short-term, impulsive, and reward-sensitive (fast) versus long-term, reflective, and controlled (slow) strategies. We find that stress increases (helps) novelty seeking for fast, but decreases (hinders) novelty seeking for slow LHS consumers. Moreover, under baseline (low stress) conditions, fast LHS consumers display a lower tendency for novelty seeking than slow LHS consumers. Interestingly, these effects are present for acute stress but not for chronic (pandemic) stress. We discuss the implications of our findings for public policy and positioning strategies, specifying when and for whom novel (versus familiar) products and services might be most effectively and efficiently marketed.

Building barriers to lock in customers and improving the affective customer experience are two key strategies employed by firms to enhance customer retention. Although pursuing the same goal, these strategies work differently: the former relies more on a calculative, cost–benefit approach to the exchange, while the latter promotes affective aspects of the relationship. Integrating experiential learning theory with social exchange theory, we provide a conceptual framework to understand the impact of lock-in and affective customer experience on customer retention, and the moderating role of relationship depth. Using a comprehensive data set for a sample of 13,761 customers covering all firms in one telecom market for two different services, we empirically test the framework via multinomial logit modeling. The results offer novel insights into the interplay between the two strategies. For poor affective customer experience (i.e., a score below five on a 0–10 scale), lock-in helps firms reduce customer churn (between 49.03% and 47.86%). However, the impact of lock-in decreases when affective customer experience improves and turns to be insignificant once the experience reaches the “acceptable level” (i.e., a score above seven on a 0–10 scale). Importantly, the separate and joint effects of the two strategies are stronger when there is a low relationship depth, and weaker when heavy relationships are established. The findings offer useful practical advice to manage these strategies in an efficient and optimal way.

Recent research views nostalgia as a valuable resource that can be accessed in times of distress and discomfort. The present work complements this literature by examining novel and previously uncovered triggers and downstream consequences of nostalgia in the consumer domain: disease-threat and protective behavior. The current paper argues that nostalgia functions as such a psychological resource with buffering qualities and is used as a coping mechanism to maintain comfort when experiencing disease threat—the perception of a potential threat posed by an infectious disease. Using an archival data set and five experiments, the authors demonstrate that when facing a disease threat, but not an actual occurrence of disease, consumers experience a higher need for nostalgia and show an increased preference for nostalgic products. That is, internet searches for nostalgic products rise during flu season as well as COVID-19 pandemic (Study 1), disease threat induces increased levels of experienced nostalgia (Study 2), which translate into increased preferences for nostalgic products (Study 3 and Study 5), mediated by disgust (Study 4). Finally, the authors show the resource value of product-induced nostalgia, demonstrating the ironic effect that it can compensate for disease-protective behavior (Study 6). The results provide important practical implications for marketers and policy-makers who could focus on promoting nostalgic products or incorporating nostalgic cues in product design and communication that would generate positive consumer evaluations when the threat of illness or disease is salient.

Multi-Tier Loyalty Programs (MTLPs) have become a popular marketing instrument to develop customer-firm relationships. Within a MTLP, customers are assigned to different tiers based on their purchase behavior. In this article, we examine whether and when tiers in the MTLP are effective in influencing customer purchase behavior, specifically share of wallet (SOW). A unique business-to-business dataset of a firm in the German agricultural market from 2009 to 2017 is used for the analysis. Data is available on the customer-specific tier level in the MTLP each year. We utilize a Tobit-style panel regression model for the analysis which is inspired by the Regression Discontinuity Design approach. This study makes several important contributions. First, it examines the effect of status in MTLPs and uses causal design to quantify the hitherto intangible effect of customer tiers. Second, this study reveals important insights on how the tier levels interact with other drivers of customer-firm relationships. Third, we use an interesting dataset from a B2B market and thereby contribute to the limited existing literature on the effectiveness of loyalty programs in B2B markets. Armed with a new understanding of how customers respond to tier levels or the negative effects of tenure especially in the highest tier, academics and managers gain new perspectives of whether and how loyalty programs affect customer behavior and drive desired outcomes in the marketplace. © 2022

This manuscript investigates if and how startups can utilize referral campaigns to increase Internet enabled software adoption. It is analyzed how geographic proximity, tie strength and status differences between referrer and referee and the sender's network position impact adoption success. This study complements a complete diffusion dataset of a startup launching Internet enabled software with user survey data on dyad characteristics. Using fuzzy-set Qualitative Comparative Analysis, we show that there are different combinations of network position and dyad characteristics that facilitate adoption success. Results reveal that referral campaigns provide a feasible go to market strategy for software startups.

In recent years, firms’ privacy practices have received increasing attention from consumers. While firms largely see this development as a threat, as consumers might prohibit collection or use of data, we suggest that it can also represent an opportunity for firms. On the “market for privacy,” firms can gain a competitive advantage by differentiating and actively promoting preferred privacy practices. In this context, the authors study how consumers trade off five privacy elements, three relating to distributive fairness (i.e., information collection, storage, use) and two relating to procedural fairness (i.e., transparency, control). Moreover, they analyze how the impact of these elements differs among four industries that vary in information sensitivity and interaction intensity. By using discrete choice experiments, the authors show that all privacy elements matter to consumers, even when in a trade-off with price. In highly sensitive industries, differences in information collection and use matter more, while storage matters less, for differentiation. When consumers have less frequent interactions with companies, they require more transparency about their privacy practices. The authors demonstrate empirically that optimizing privacy practices can lead to robust changes in market shares (Study 1) and higher revenues in equilibrium (Study 2) when firms embrace the market for privacy.

The present research extends findings on when and why consumers (fail to) adopt innovative food products by showing that consideration or consumption of such products (functional foods) can backfire when they entail an inherent and incompatible trade-off between healthiness and naturalness. Four experiments, examining consumers’ willingness to buy, try, and actually consume such foods, show that this trade-off yields a sense of ambivalence that spills over from single product exemplars to negatively affecting (unrelated members of) the parent category of functional foods. However, this effect is not invariant across consumers. Ironically, it is more pronounced for consumers that tend to be more open to novel experiences and also more open to ambivalent feelings to occur—consumers with lower levels of the Preference for Predictability. Implications for marketing practice are discussed.

Scholars and practitioners widely argue that strong, successful brands are built on consistent and unique positioning, which should be reflected in the brands’ advertising. Surprisingly, however, little empirical evidence supports this claim, especially with regard to advertising content. The authors investigate whether and to what extent brands’ advertising content consistency—the similarity in the firm's own advertising content over time—and commonality—the similarity between the firm's and competitors’ advertising content—affect brands’ sales. Insights emerge from the analysis of the impact on sales of the content of 247 television ads aired by 33 brands in six consumer packaged goods categories over a four-year period. Results indicate that more than advertising spending, both consistency and commonality in advertising content affect sales, especially with respect to long-term cumulative sales. However, brands differ considerably regarding the direction of the effects. While small brands tend to benefit from increased consistency and commonality in advertising content, large brands tend to suffer from increased consistency. Thus, whether consistency and commonality in advertising content will help or hurt depends on the size of the brand.

The evidence base connecting planetary and human health is growing, but thus far the research community has primarily focused on the physical health implications. This Voices asks: how does environmental degradation affect mental health, and what are the emerging needs and research priorities?

Although collecting personal information about consumers is crucial for firms and marketers, understanding of when and why consumers accept or reject information collection remains limited. The authors conceptualize a privacy calculus that represents a consumer’s trade–off of the valence and uncertainty of the consequences of the collection, storage, and use of personal information. For example, usage-based car insurance requires drivers to share data on their driving behavior in exchange for a discount (certain benefit) but at the risk of third parties intercepting location data for malicious use (uncertain disadvantage). Building on this conceptualization, the authors develop the privacy calculus (PRICAL) index. They empirically confirm the validity of the items (Study 1) and the index as a whole (Study 2). The PRICAL index is generally applicable and improves the explanation of behavioral intentions (Study 2) and actual behavior (Study 3), compared with currently used constructs (e.g., privacy concern, trust). Overall, the PRICAL index allows managers to understand consumers’ acceptance of information collection regarding financial, performance, psychological, security, social, and time-related consequences, which the authors demonstrate using the top five most valuable digital brands (Study 4).

This paper sets out a general framework for store sales evaluation and prediction. The sales of a retail chain with multiple stores are first decomposed into five components, and then each component is explained by store, competitor and consumer characteristics using random effects models for components observable at the store level and spatial error random effects models for components observable at the zip code level. We use spatial panel data over four years for estimation and a subsequent year for evaluating one-year-ahead predictions. Set against a benchmark model that explains total sales directly, the prediction error of our framework is reduced by 34% for existing stores during the sample period, by 5% for existing stores one year ahead and by 26% for new stores.

Algorithms make highly consequential decisions and, thereby, exercise considerable power. In this study I investigate how social power through algorithms is exercised in media consumption, particularly through curation algorithms. This conceptual paper then contributes to the understanding of social power through algorithms by suggesting the concept of algorithmic meta-capital. The concept derives from Bourdieu’s theory on meta-capital which has also been applied to legacy media. I then argue that this algorithmic meta-capital is an extension of the power traditionally held by the state and legacy media. The study also contributes to the understanding of meta-capital as it proposes how the meta-capital possessed by digital intermediaries functions. It does so by legitimating representations of the world and by creating a necessity for algorithmic visibility across different fields, thereby shaping habitus. This Bourdieusian approach enables researchers to take a balanced view on the power of algorithms on the structure/agency continuum.

Advertisers increasingly use personal information in social media advertisements as a strategy to promote positive brand attitudes. Personalized ads can be perceived as both positive and negative. This two-sided effect of personalization refers to the personalization paradox. An online experiment (N = 209), in which the level of personalization was manipulated in a Facebook setting, aimed to provide a potential explanation for this paradox. The findings showed that a highly personalized ad resulted in stronger perceived personalization than a less personalized ad. Furthermore, the stronger the perceived personalization, the stronger the relevance. The relevance of the ad positively influenced brand attitude and fully mediated the relationship between personalization and attitude. However, in line with the assumptions of the information boundary theory, the more the ad was perceived as intrusive, the weaker the relevance–attitude relationship, thereby showing a boundary condition for the effectiveness of personalized information when targeting consumers on Facebook.

Music is a key and heavily researched stimulus in tourism and hospitality service settings. However, this growing body of research has produced contradictory results in terms of direction, strength, and statistical significance, rendering conclusions and evidence-based decisions questionable and precarious. This meta-analysis of 56 studies and 209 effects quantitatively synthesizes empirical evidence regarding the influence of music in tourism and hospitality service settings. We consider five dimensions of music and assess their effects on a wide range of customers’ organismic reactions and behavioral responses. The results indicate that it is not so much the presence of music but the design of it that influences customers. In addition, the preferential dimensions of music have a much stronger influence on customers than the physical dimensions of music. The large number of relationships examined offers practical guidance to professionals on the effective use of music in tourism and hospitality settings.

Consumer information is an increasingly valuable resource in the digitally interconnected modern world. Globally, the number of firms collecting and exploiting consumer information to optimize their marketing efforts is increasing rapidly. The authors determine how four cultural dimensions—power distance, masculinity, uncertainty avoidance, and long-term orientation—affect consumers’ willingness to share their personal information with firms (WTS). The authors empirically test the direct effect of national culture on WTS, as well as its moderating effect on the link between WTS and two of its key drivers, privacy concerns and perceived benefits. Drawing on regulatory focus theory, the authors develop a conceptual framework and test it using multilevel modeling on data from 15,045 consumers across 24 countries. The empirical findings demonstrate that national culture directly affects WTS and moderates the effects of both privacy concerns and perceived benefits on WTS. These results highlight the need for managers and marketers to consider international cultural differences when collecting consumer information.

Item does not contain fulltext Interactivity has become a crucial aspect of marketing. It allows companies to connect with their customers, often resulting in positive outcomes. Based on a literature review, this chapter discusses ten of the most pioneering tools used in interactive marketing. First it will be explained how each tool relates to the three dimensions of interactivity (active control, two-way communication, synchronicity), and insights in what dimensions are the driving forces behind each interactive marketing tool are provided. Second, results showing that research on the ten interactive marketing tools generally finds positive effects on diverse outcome variables, such as enjoyment, urges, and behavioral intentions, are discussed together with conflicting outcomes (e.g., the effect on cognition) and the potential negative effects of the tools (e.g., privacy concerns and intrusiveness). It concludes with the recommendation for marketers and researchers to collaborate and actively try out (innovative) interactive marketing tools while closely monitoring their effects.

Economic, environmental, social and digital (r)evolutions have fundamentally transformed marketing theory and marketing practice. We are confronted with new concepts, methodologies, approaches and findings, and it is often difficult to see the wood from the trees. The aim of this paper is (1) to provide a coherent overview of recent developments, including the impact of the COVID-19 crisis, and the increasing attention paid to climate change, social inequality and, as a consequence, the need for sustainable consumption, (2) to link these developments to insights from academic research and responses of managers as cited in business journals, and (3) to elaborate on the marketing capabilities needed to survive in the current turbulent environment.

This study extends research on online innovation contests by focusing on the process of an innovation contest. The authors propose that the decision of a solver to join a contest and the likelihood that a solver will submit a high-quality solution are functions of the current number of solvers in a contest and of the current number of high-quality solutions. The hypotheses are tested in an empirical analysis using a unique data set of 1351 online innovation contests for graphic design projects. The study finds that solvers joining a contest and solvers submitting high-quality solutions are two dynamic and interacting processes that impact the outcomes of an innovation contest. More specifically, the results reveal that (1) a solver is less likely to join a contest that already has many solvers, and many high-quality solutions; (2) a solver is more likely to submit a high-quality solution in a contest if the contest has already many solvers or the focal solver has already submitted one or more high-quality solutions; (3) a solver is less likely to submit a high-quality solution if the contest already has many high-quality solutions developed by others. Organizers of online innovation contests need to understand these complex relationships when they manage contests and aim to improve contest performance. This article details the implications of these findings for the theory and practice of innovation contests.

In the hope of benefiting from the increasing focus on sustainability in Western markets, national brands are introducing new sustainable products. We investigate the success of new sustainable products with a unique dataset combining household panel data, consumer survey data, expert panel survey data, and advertising expenditure data. We show that sustainable new product introductions achieve lower sales than their conventional counterparts. Investing in corporate social responsibility activities compensates for this negative effect and is therefore a viable strategy to boost sales of new sustainable products. Importantly, making sustainable new products clearly innovative mitigates the negative effect of a sustainability claim on new product sales, whereas price promotions aggravate the negative effect. We furthermore caution that the negative effect of sustainability may not decrease as sustainability becomes more mainstream, even if our data covers a period before the currently increased interest in sustainability.

E-commerce has significantly reshaped consumers’ shopping processes and habits. The need to understand the key drivers of online shopping has received keen attention and fueled a rich strand of studies. To help managers and researchers synthesize this growing body of evidence, we conducted a comprehensive meta-analysis to unearth the factors that influence consumers’ online shopping. Our main takeaways reveal that the most important drivers of online shopping (a) conform to the TAM and TPB theories, in addition to (b) website characteristics and past experience. In particular, the multiple predictors are strongly related to online purchase intentions and purchase behavior, where attitude and convenience show the strongest impact. Furthermore, moderator analyses indicate that cultural traits have specific moderating effects on the links between purchase intention and some of its drivers. For instance, power distance and uncertainty avoidance have a positive effect, while individualism, indulgence and masculinity have a negative one. Finally, we apply meta-analytic structural equation modeling to test a conceptual framework including four groups of drivers (consumer–channel interactions, website characteristics, social influence, and consumer characteristics) and different aspects of online shopping. The findings provide valuable insights for online shopping research and practice.

In charitable advertisements, organizations often display the image of a person in need with different facial emotional expressions. Prior research showed the positive effect of using a sad- (vs. happy- or neutral-) faced image in evoking sympathy from viewers. Across five studies (N = 2141), we demonstrate that a sad-faced image evokes not only sympathy but also an inference about the organization's manipulative intent. Moreover, we show that inference of manipulative intent and sympathy simultaneously mediate the effects of facial expression on donation and on attitude toward the advertising campaign, but in opposing directions. While greater sympathy leads to larger donation, greater inference of manipulative intent lowers donation, together contributing to a null effect of facial expression on donation. In contrast, using a sad-faced image reduces attitude toward the advertising campaign because the mediating effect of inference of manipulative intent tends to be larger than the mediating effect of sympathy in absolute size. The negative effect of a sad-faced image on attitude toward the advertising campaign is attenuated when the prominence of the image is low (vs. high). Finally, we show that these effects also emerge in the cause-related marketing advertising context.

PANDA (anti-proton annihiliation at Darmstadt) is planned to be one of the four main experiments at the future international accelerator complex FAIR (Facility for Antiproton and Ion Research) in Darmstadt, Germany. It is going to address fundamental questions of hadron physics and quantum chromodynamics using cooled antiproton beams with a high intensity and and momenta between 1.5 and 15 GeV/c. PANDA is designed to reach a maximum luminosity of 2 × 1032 cm−2 s. Most of the physics programs require an excellent particle identification (PID). The PID of hadronic states at the forward endcap of the target spectrometer will be done by a fast and compact Cherenkov detector that uses the detection of internally reflected Cherenkov light (DIRC) principle. It is designed to cover the polar angle range from 5° to 22° and to provide a separation power for the separation of charged pions and kaons up to 3 standard deviations (s.d.) for particle momenta up to 4 GeV/c in order to cover the important particle phase space. This document describes the technical design and the expected performance of the novel PANDA disc DIRC detector that has not been used in any other high energy physics experiment before. The performance has been studied with Monte-Carlo simulations and various beam tests at DESY and CERN. The final design meets all PANDA requirements and guarantees sufficient safety margins.

We conducted a preregistered multilaboratory project ( k = 36; N = 3,531) to assess the size and robustness of ego-depletion effects using a novel replication method, termed the paradigmatic replication approach. Each laboratory implemented one of two procedures that was intended to manipulate self-control and tested performance on a subsequent measure of self-control. Confirmatory tests found a nonsignificant result ( d = 0.06). Confirmatory Bayesian meta-analyses using an informed-prior hypothesis (δ = 0.30, SD = 0.15) found that the data were 4 times more likely under the null than the alternative hypothesis. Hence, preregistered analyses did not find evidence for a depletion effect. Exploratory analyses on the full sample (i.e., ignoring exclusion criteria) found a statistically significant effect ( d = 0.08); Bayesian analyses showed that the data were about equally likely under the null and informed-prior hypotheses. Exploratory moderator tests suggested that the depletion effect was larger for participants who reported more fatigue but was not moderated by trait self-control, willpower beliefs, or action orientation.

This paper examines the influence of a permanent discount strategy on customer purchase behavior, i.e., purchase incidence in each week, purchase quantity (in units), and total order spending (in CNY). Permanent discounts are defined as discounts continuously provided by retailers. We identify two types of permanent discounts, namely, product-specific price discounts (PD) and order coupons (OD, which can be redeemed for a total order). We collect transactional data from a Chinese online retailer and empirically examine the effects of the two types of permanent discounts and customers’ expectations of PD and OD. We find nonlinear relationships between permanent discounts and customer purchase behavior. PDs negatively influence spending when they are lower than 19% but show a positive effect beyond this threshold, hence depicting a U-shaped relationship. They also affect purchase quantity positively but at a decreasing rate. Customer expectations of PD influence purchase incidence, spending, and purchase quantity following a U-shaped patter with a positive influence appearing when PD expectations are high than 31%, 27%, and 18% respectively. On the other hand, ODs influence spending and purchase quantity positively at an increasing rate. Customer expectations of OD influence purchase incidence, spending, and purchase quantity following a U-shaped relationship where the positive influence on purchase incidence shows beyond OD expectations of 426 CNY, and the positive effect appearing on spending and purchase quantity when these expectations are higher than 34 CNY. We also find that customer expectations of discounts interact with current discount levels in their influence on spending. Combining these results and considering that order coupons negatively affect the profit margin of the total basket, we suggest that retailers should offer order coupons with relatively low value but product-specific price discounts with high discount depth.

Despite the rise of digital, direct mailing as a marketing communication tool remains relevant and widely applied in practice. Nevertheless, research into the effectiveness of direct mailing in the online environment is scant. Key questions that remain entail how direct mails affect different online and offline consumer activity metrics throughout the purchase funnel and how they interact with digital marketing communication tools. The current paper, therefore, investigates these two questions by conducting two studies. First, we focus on the effect of direct mailing on zip-code level upper, middle, and lower funnel performance metrics over time by analyzing quasi-experimental data from a large European insurance firm. The results reveal that direct mailing significantly influences consumer activity metrics in the online channel (i.e., online search and clicking behavior), in support of cross-channel effects of direct mailing. Moreover, direct mailing is shown to be effective throughout the purchase funnel, both directly and indirectly, with a positive net sales effect. Second, we study the joint effect of direct mailing and display advertising by analyzing field experiment data from the same insurance firm. The results show positive synergy between direct mailing and display advertising. Therefore, despite the rise of digital, direct mailing still serves as an effective marketing tool, both by itself and in combination with digital marketing.

Background: Financial incentive interventions for improving physical activity have proven to be effective but costly. Deposit contracts (in which participants pledge their own money) could be an affordable alternative. In addition, deposit contracts may have superior effects by exploiting the power of loss aversion. Previous research has often operationalized deposit contracts through loss framing a financial reward (without requiring a deposit) to mimic the feelings of loss involved in a deposit contract. Objective: This study aimed to disentangle the effects of incurring actual losses (through self-funding a deposit contract) and loss framing. We investigated whether incentive conditions are more effective than a no-incentive control condition, whether deposit contracts have a lower uptake than financial rewards, whether deposit contracts are more effective than financial rewards, and whether loss frames are more effective than gain frames. Methods: Healthy participants (N=126) with an average age of 22.7 (SD 2.84) years participated in a 20-day physical activity intervention. They downloaded a smartphone app that provided them with a personalized physical activity goal and either required a €10 (at the time of writing: €1=US $0.98) deposit up front (which could be lost) or provided €10 as a reward, contingent on performance. Daily feedback on incentive earnings was provided and framed as either a loss or gain. We used a 2 (incentive type: deposit or reward) × 2 (feedback frame: gain or loss) between-subjects factorial design with a no-incentive control condition. Our primary outcome was the number of days participants achieved their goals. The uptake of the intervention was a secondary outcome. Results: Overall, financial incentive conditions (mean 13.10, SD 6.33 days goal achieved) had higher effectiveness than the control condition (mean 8.00, SD 5.65 days goal achieved; P=.002; ηp2=0.147). Deposit contracts had lower uptake (29/47, 62%) than rewards (50/50, 100%; P, Journal of Medical Internet Research, 24 (10), ISSN:1438-8871

Recent technological advances allow artificial intelligence (AI) to perform tasks that require high warmth, such as caring, understanding others' feelings, and being friendly. However, current consumers may be reluctant to accept AI for such tasks. This research investigates the impact of required warmth to conduct a task on consumer acceptance of AI service and the moderating role of AI-human collaboration. A series of choice-based conjoint experiments and one survey yield two main findings. First, consumers tend to refuse AI for tasks that require high warmth due to the low perceived fit between AI and the task at hand. Second, an AI-human collaboration of AI supporting a human employee increases consumer acceptance of AI service for tasks that require high warmth. This is not the case for AI-human collaboration in which AI performs a task that is supervised by a human employee. Theoretically, this study increases our understanding of how consumer acceptance of AI service varies across tasks and how AI-human collaboration can advance AI acceptance. These findings provide insightful suggestions for managers regarding designing AI service and framing AI-human collaboration.

Current carbon-intensive lifestyles are unsustainable and drastic social changes are required to combat climate change. To achieve such change, moral rebels (i.e., individuals who deviate from current behavioral norms based on ethical considerations) may be crucial catalyzers. However, the current literature holds that moral rebels may do more harm than good. By deviating from what most people do, based on a moral concern, moral rebels pose a threat to the moral self-view of their observers who share but fail to uphold that concern. Those observers may realize that their behavior does not live up to their moral values, and feel morally inadequate as a result. Work on “do-gooder derogation” demonstrates that rebel-induced threat can elicit defensive reactance among observers, resulting in the rejection of moral rebels and their behavioral choices. Such findings suggest that advocates for social change should avoid triggering moral threat by, for example, presenting nonmoral justifications for their choices. We challenge this view by arguing that moral threat may be a necessary ingredient to achieve social change precisely because it triggers ethical dissonance. Thus, instead of avoiding moral justifications, it may be more effective to harness that threat. Ethical dissonance may offer the fuel needed for observers to engage in self-improvement after being exposed to moral rebels, provided that observers feel capable of changing. Whether or not observers feel capable of changing, however, depends on how rebels communicate their moral choices to others—how they talk about change. This article is categorized under: Perceptions, Behaviour and Communication of Climate Change > Behaviour Change and Responses.

In this paper, I discuss some reflections on the emerging literature on multi- and omni-channel retailing. I discuss four important area’s of prior research and briefly describe some general findings. Next, I consider three important emerging trends: 1) digital only, 2) Covid-19 effects and 3) New Technologies. I discuss the implications of these trend for omni-channel retailing and provide some ideas for future research on these trends.

Online retailers are increasingly using third-party online marketplaces (e.g., Amazon, Taobao) as an alternative sales channel to their website. While cross-channel sales elasticities have been established for many sales channel combinations (e.g., adding bricks to clicks), we lack an understanding of whether the use of third-party marketplaces grows or cannibalizes a retailer's sales. Practitioners argue that firms can build their e-commerce business through acquiring customers by selling on the marketplace. Indeed, a marketplace could complement a retailer's offering (e.g., acquiring new customer segments), although inventory effects might mitigate this complementarity. Alternatively, cannibalization might occur from losing customers from one's website to the online marketplace. The present research investigates which of the two opposing forces prevails using a time series of category sales data from one of the largest global marketplace sellers. The authors use vector autoregressive modeling to show that marketplace sales increase sales on a retailer's website (0.014% for every 1% in marketplace sales). This effect is strongest for categories with large choice and low product prices. Acquiring customers through the marketplace might be cheaper than through other sources (estimated at 24% of initial sales). However, online retailers should be aware that this strategy strengthens the marketplace and may have potential negative long-term consequences (e.g., through marketplace control of the customer relationship).

This review synthesizes recent research on consumer self-control, self-regulation, and wellbeing using a perspective rooted in evolutionary theorizing-the notion of Life History Strategies (LHSs), derived from Life History Theory. We discuss both correlational and experimental research that has informed our understanding about how individual differences in LHSs may shape the 'self-regulatory toolkit' and how this, in turn, affects downstream consequences for consumer health and wellbeing. We also offer a counterpoint to the prevailing notion that fast LHSs mostly have negative, and slow LHSs positive consequences and we highlight promising future avenues to boost fast LHS consumers' self-control.

Among the dark sides of contemporary multi-channel retailing are the vast amounts of product returns, especially in the online channel. High product returns not only put pressure on the retailers’ profitability, but also come at high societal and environmental costs. A central question then is whether multi-channel retailers can use their offline stores to help reduce product returns in the online channel without harming online sales. In an empirical study, we address this issue using data from a large Dutch shoe retailer. We develop a novel spatial model to estimate the influence of proximate retail stores on customers’ online shopping behavior, while controlling for spatial and customer heterogeneity. Results demonstrate that an increased offline channel presence indeed reduces online returns, depending on the product’s risk profile, without significantly lowering online sales. Offline stores can thus be an effective and appealing way for retailers to mitigate the negative impact of online shopping related to product returns.

Some companies design processed foods to contain aesthetic imperfections such as non-uniformities in shape, color, or texture. Simultaneously, consumers annually discard millions of pounds of unprocessed, safe-to-eat fruits and vegetables owing to aesthetic imperfections. Why design processed foods with aesthetic imperfections when people discard unprocessed foods because of them? Seven studies, including a choice study at a grocery store and an incentive-compatible study, show that the effect of aesthetic imperfections on consumer preferences depends on whether foods are unprocessed or processed. While imperfections negatively influence preferences for unprocessed foods, they positively influence preferences for processed foods. We attribute this preference shift to consumers making opposing inferences about the human care involved in producing aesthetically imperfect processed and unprocessed foods. Building on research highlighting the positive effects of human presence in production, we thus show that perceived care drives food choice. We discuss implications for product design, retail promotion, and sustainability.

Despite significant research and progress in examining the effects of loyalty programs on consumer behavior and firm performance, the firm value implications of these programs are still unclear. The article investigates whether loyalty program introduction affects firm value, as measured by abnormal stock returns. The authors test the hypotheses empirically by conducting an event study of 260 announcements which cover 110 firms in the United States across different industries for 18 years from 2000 to 2017. Findings reveal that the introduction of loyalty programs, on average, positively influences firm value. The results of this study also reveal the existence of contingencies including synergies with complementary market-based assets and market conditions of lower uncertainty in determining the value of loyalty programs. The authors conclude that the value of loyalty programs is greater when the perceived risks of purchase are lower.

As extant literature on social media has generally focused on investigating the psychological factors, which makes a person more susceptible to social media addiction, it has not yet investigated how social media addiction is portrayed by the media. However, the media framing of addictions can have considerable implications for consumers, as extant literature has shown them to use media texts as cultural resources through which they attempt to understand and justify their behaviour. The media can also have more indirect effects by, for instance, driving stigmatization or public policy initiatives. Thus, this study compares the media framing of social media addiction in the United Kingdom and the United States through longitudinal, mixed-methods frame analysis. It then extends the extant literature by showing how social media addiction has been framed in both the United Kingdom and United States. It shows that concern regarding the issue has increased in both countries. In addition, the findings show that while previously social media addiction has been seen as an individual, psychological problem, concerns about the addictiveness and, thereby, about the lacking public policy measures have also increased in both countries. Implications for individual consumers, public policy and managers are considered.

This research investigates how the timing of the promotional encounter, whether consumers encounter a promotion in isolation or at the moment of choice alongside other products, influences how consumers evaluate and redeem a promotional offer. Three studies demonstrate that isolated promotions for premium brands are more effective than traditional shelf promotions in persuading consumers to purchase the promoted product as these promotions alter how consumers evaluate and justify purchasing the promoted products. Specifically, isolated promotions lead consumers to focus relatively less on the price of the promoted product compared to its quality. This reduced focus on price assuages the negative effect of guilt associated with purchasing a more expensive, premium brand. These findings offer insights into consumer response to promotions, the most effective timing for promotions, and the best ways to optimize promotional strategies.

Data is considered the new oil of the economy, but privacy concerns limit their use, leading to a widespread sense that data analytics and privacy are contradictory. Yet such a view is too narrow, because firms can implement a wide range of methods that satisfy different degrees of privacy and still enable them to leverage varied data analytics methods. Therefore, the current study specifies different functions related to data analytics and privacy (i.e., data collection, storage, verification, analytics, and dissemination of insights), compares how these functions might be performed at different levels (consumer, intermediary, and firm), outlines how well different analytics methods address consumer privacy, and draws several conclusions, along with future research directions.

In this study, we investigate the effects of an enabling versus a coercive performance measurement system on how employees perceive the procedural quality of such systems. In particular, we examine the design characteristics and the development process of performance measurement systems. We hypothesize that an enabling design and an enabling development process, as compared to a coercive design and a coercive development process, lead to perceptions of greater procedural fairness and less red tape. To test our hypotheses, we conduct an experiment with two different samples (a student laboratory sample and an online sample). In general, our results indicate that an enabling performance measurement system design and an enabling system development process both independently increase procedural fairness and decrease red tape. These findings imply that organizations interested in improving the procedural quality of their performance measurement system should focus on designing and developing a system that is enabling rather than coercive.

Digital transformation and resultant business model innovation have fundamentally altered consumers’ expectations and behaviors, putting immense pressure on traditional firms, and disrupting numerous markets. Drawing on extant literature, we identify three stages of digital transformation: digitization, digitalization, and digital transformation. We identify and delineate growth strategies for digital firms as well as the assets and capabilities required in order to successfully transform digitally. We posit that digital transformation requires specific organizational structures and bears consequences for the metrics used to calibrate performance. Finally, we provide a research agenda to stimulate and guide future research on digital transformation.

We propose that digital technologies and related data become increasingly prevalent and that, consequently, ethical concerns arise. Looking at four principal stakeholders, we propose corporate digital responsibility (CDR) as a novel concept. We define CDR as the set of shared values and norms guiding an organization's operations with respect to four main processes related to digital technology and data. These processes are the creation of technology and data capture, operation and decision making, inspection and impact assessment, and refinement of technology and data. We expand our discussion by highlighting how to managerially effectuate CDR compliant behavior based on an organizational culture perspective. Our conceptualization unlocks future research opportunities, especially regarding pertinent antecedents and consequences. Managerially, we shed first light on how an organization's shared values and norms regarding CDR can get translated into actionable guidelines for users. This provides grounds for future discussions related to CDR readiness, implementation, and success.

Hedonic consumption is pleasant but can interfere with the capacity to self-regulate. In stressful moments, when self-regulation is arguably still important, individuals often indulge in hedonic consumption. In two experiments, we investigate whether hedonic consumption negatively affects self-regulation under moderately stressful conditions and whether selecting hedonic consumption under moderately stressful conditions is driven by high or low self-control. In both studies, participants were randomly exposed to a mental arithmetic task that was either completed under time pressure with performance feedback (moderate stress) or without time pressure and without feedback (no stress). Experiment 1 assigned participants to a hedonic (vs. neutral) consumption task and then measured impulse control via a color-word Stroop task. Experiment 2 measured self-control as a second independent variable and recorded hedonic (vs. neutral) consumption. The results show that moderate stress buffered the negative effect that hedonic consumption has on self-regulation under no stress conditions and that high rather than low self-control predicts hedonic over neutral consumption under stress. These findings indicate that hedonic consumption in response to moderate stress may be a strategic choice to reap the pleasure benefit of hedonic consumption while the costs to self-regulation are low.

The penetration of mobile devices has reshaped consumers’ shopping journeys, drawing the attention of both scholars and practitioners. Over the last two decades, a rich strand of empirical studies across disciplines has been conducted on the factors underlying mobile shopping behavior. We provide and test a comprehensive framework for both the key drivers of consumers’ initial adoption and the continuance intention to use mobile devices for purchasing. To achieve this goal, we conduct a meta-analysis, in which we integrate the findings from the literature and apply a structural equation modeling approach. Our work builds on the existing theories (Technology Acceptance Model, Theory of Planned Behavior, and Unified Theory of Acceptance and Use of Technology) and offers an extensive understanding of the variables that shape mobile shopping behavior. Based on 207 articles, with 228 studies, 4,354 effect sizes, a total sample size of 68,944 shoppers, our findings show that mobile shopping is influenced by variables that reflect the evolution of technological innovations and the consequent improvement of the functionality and convenience of mobile devices (previous digital experience and ubiquity). Managerially, based on these findings, we provide a future research agenda and the key implications for firms to develop for a successful marketing strategy throughout the mobile customer journey. Companies should focus on both utilitarian and hedonic variables to stimulate the intention to use the mobile for the first time. In addition, to increase continuance intention to use mobile for shopping, they improve customer satisfaction, through enjoyment and the three dimensions of quality of the mobile channel.

Assessing market structure by deriving a brand positioning map and segmenting customers is essential for supporting brand-related marketing decisions. We propose adaptive multidimensional scaling (ADMDS) for simultaneously deriving a brand positioning map and market segments using customer data on cognitive decision sets and brand dissimilarities. In ADMDS, the judgment task is adapted to the individual customer where dissimilarity judgments are collected only for those brands within a customers’ awareness set. Thus, respondent fatigue and unfamiliarity with the brands are circumvented thereby improving the validity of the dissimilarity data obtained, as well as the multidimensional spatial structure derived from them. Estimation of the ADMDS model results in a spatial map in which the brands and derived segments of customers are jointly represented as points. The closer a brand is positioned to a segment’s ideal brand, the higher the probability that the brand is considered and chosen. An assumption underlying this model representation is that brands within a customers’ consideration set are relatively similar. In an experiment with 200 respondents and 4 product categories, this assumption is validated. We illustrate adaptive multidimensional scaling model on commercial data for 20 midsize car brands evaluated by 212 members of an on-line consumer panel. Potential applications of the method and future research opportunities are discussed.

International migration implies the coexistence of different ethnic and cultural groups in the receiving country. The refugee crisis of 2015 has resulted in critical levels of opinion polarization on the question of whether to welcome migrants, causing clashes in receiving countries. This scenario emphasizes the need to better understand the dynamics of mutual adaptation between locals and migrants, and the conditions that favor successful integration. Agent-based simulations can help achieve this goal. In this work, we introduce our model MigrAgent and our preliminary results. The model synthesizes the dynamics of migration intake and post-migration adaptation. It explores the different acculturation outcomes that can emerge from the mutual adaptation of a migrant population and a local population depending on their degree of tolerance. With parameter sweeping, we detect how different acculturation strategies can coexist in a society and in different degrees among various subgroups. The results show higher polarization effects between a local population and a migrant population for fast intake conditions. When migrant intake is slow, transitory conditions between acculturation outcomes emerge for subgroups, e.g., from assimilation to integration for liberal migrants and from marginalization to separation for conservative migrants. Relative group sizes due to speed of intake cause counterintuitive scenarios, such as the separation of liberal locals. We qualitatively compare the processes of our model with the German portion sample of the survey Causes and Consequences of Socio-Cultural Integration Processes among New Immigrants in Europe (SCIP), finding preliminary confirmation of our assumptions and results., Comment: 24 pages, plus supplemental material, 11 figures

COVID-19 mitigating practices such as 'hand-washing', 'social distancing', or 'social isolating' are constructed as 'moral imperatives', required to avert harm to oneself and others. Adherence to COVID-19 mitigating practices is presently high among the general public, and stringent lockdown measures supported by legal and policy intervention have facilitated this. In the coming months, however, as rules are being relaxed and individuals become less strict, and thus, the ambiguity in policy increases, the maintenance of recommended social distancing norms will rely on more informal social interactional processes. We argue that the moralization of these practices, twinned with relaxations of policy, may likely cause interactional tension between those individuals who do vs. those who do not uphold social distancing in the coming months: that is, derogation of those who adhere strictly to COVID-19 mitigating practices and group polarization between 'distancers' and 'non-distancers'. In this paper, we explore how and why these processes might come to pass, their impact on an overall societal response to COVID-19, and the need to factor such processes into decisions regarding how to lift restrictions.