All that glitters is not gold: An investigation into the undesired effects of gamification and how to mitigate them through gamification design

Although gamification has received considerable attention from both researchers and practitioners, its influence on consumers remains ambiguous. This paper proposes that a negative process through decreased attention and a positive process through increased enjoyment explain the effects of gamification on different outcome variables. Study 1 examines these two processes and gamification’s downstream consequences on purchase intention and product information recognition. For purchase intention, the two processes operate in parallel and produce a null effect of gamification. For product information recognition, only the negative process emerges, resulting in a negative effect of gamification. Studies 2 and 3 focus on the negative effect of gamification on product information recognition and show that the negative effect disappears in gamification designs that link the game elements with meaningful information about the product (Study 2) or make consumers aware of the distraction potential of game elements (Study 3). The studies’ findings provide managerial insights into why not all gamification endeavors yield the desired results; they also specify two boundary conditions (i.e., meaningfulness and disclosure) that may help managers avoid potentially detrimental effects of gamification.     

Engaging the unengaged customer: The value of a retailer mobile app

Mobile apps are becoming a go-to tactic for retailers because they offer the promise of highly convenient digital engagement. We hypothesize that two types of customers are best served by these apps — “offline-only” customers currently purchasing exclusively from the retailer's physical store, and “distant” customers who reside far from the physical store. For offline-only customers, the app complements the physical engagement they currently have. For distant customers, the app offers convenient engagement their remoteness currently precludes. We model app access and purchase behavior of 629 customers who downloaded a retailer's app. We find that apps generate more incremental sales among distant customers compared to near customers, and more incremental sales among offline-only customers compared to online customers. On an illustrative base of 100 K app users, we find accessing the app would generate $2.3 M in incremental sales. Consistent with our segmentation results, we find that the users with the greatest purchase lift (9.5%) due to app usage are those that are distant and offline-only. Our results confirm the economic value of retailer apps and their role as a segmentation strategy to enhance customer engagement.     

Making a first impression as a start-up: Strategies to overcome low initial trust perceptions in digital innovation adoption

High failure rates of digital innovations by start-ups indicate that consumers' initial trust perceptions are make-or-break for their survival. Hence, start-ups have to design adequate business models to manage consumers' initial trust perceptions of digital innovations. Five experiments explore how start-ups can signal trustworthiness in order to overcome low initial trust perceptions and boost adoption. We find three specific design strategies of start-ups' digital business models – customer ratings, benefit communication, and revenue model – to be effective to overcome low initial trust perceptions and to increase adoption of digital innovations. The findings demonstrate that initial trust serves as a critical mediator in the relationship between these design strategies and consumers' adoption intentions. Additionally, the chosen revenue model has differential effects on privacy concerns, which mediate the relationship between revenue model and initial trust. The present empirical insights help start-ups to craft business model design strategies for successful digital innovation launch.     

The distinct influence of power distance perception and power distance values on customer satisfaction in response to loyalty programs

In today's fiercely competitive environment, firms are increasingly relying on loyalty programs to influence customers' repeat purchase behavior. However, little is known about how customers' cultural values shape their satisfaction in response to loyalty programs. Such knowledge is important because it allows marketers to identify cultural segments that may be more or less likely to respond favorably to loyalty programs, and hence increase the effectiveness of such programs. In the current research, we propose that power distance perception — defined as the extent to which people observe power disparities in society — positively influences satisfaction of customers who hold loyalty status, but negatively influences satisfaction of customers who do not hold loyalty status with a firm. In contrast, power distance values — defined as the extent to which people endorse power disparities in society — negatively influences satisfaction of customers who hold loyalty status, but positively influences satisfaction of customers who do not hold loyalty status with a firm. A quasi-field study and several lab experiments support these propositions, shed light on the underlying mechanisms, and rule out alternative explanations. Our findings also uncover several distinct tools that marketers could use to influence non-loyalty status and loyalty status customers' satisfaction with businesses.     

Seeing the wood for the trees: How machine learning can help firms in identifying relevant electronic word-of-mouth in social media

The increasing volume of firm-related conversations on social media has made it considerably more difficult for marketers to track and analyse electronic word-of-mouth (eWOM) about brands, products or services. Firms often use sentiment analysis to identify relevant eWOM that requires a response to consequently engage in webcare. In this paper, we show that sentiment analysis of any kind might not be ideal for this purpose, because it relies on the questionable assumption that only negative eWOM is response-worthy and it is not able to infer meaning from text. We propose and test an approach based on supervised machine learning that first decides whether eWOM is relevant for the brand to respond, and then—based on a categorization of seven different types of eWOM (e.g., question, complaint)—classifies three customer satisfaction dimensions. Using a dataset of approximately 60,000 Facebook comments and 11,000 tweets about 16 different brands in eight different industries, we test and compare the efficacy of various sentiment analysis, dictionary-based and machine learning techniques to detect relevant eWOM. In doing so, this study identifies response-worthy eWOM based on the content instead of its expressed sentiment. The results indicate that these machine learning techniques achieve considerably higher accuracy in detecting relevant eWOM on social media compared to any kind of sentiment analysis. Moreover, it is shown that industry-specific classifiers can further improve this process and that algorithms are applicable across different social networks.     

Ad wearout wearout: How time can reverse the negative effect of frequent advertising repetition on brand preference

This paper reports a surprising reversal in the effect of advertising repetition over time. A field study shows higher annoyance with a more frequently advertised brand at the time of advertising, but greater preference for this same brand several weeks later. A longitudinal online experiment replicates the reversal in brand preference across four time points and tests an underlying mechanism for this reversal. It shows that initial annoyance with frequent ad repetition is highly susceptible to decay over time, whereas brand memory remains relatively stable. Through these two processes, brands with heavier advertising exposure move over time from lower preference to higher preference. Finally, a third experiment demonstrates a crucial condition for this reversal — product relevance at the time of consideration. This study shows that the reversal occurs only if at the later time the product category is relevant. We discuss the substantial implications of these findings for marketing theory and practice.     

Online marketing: When to offer a refund for advanced sales

Advance selling is a marketing strategy commonly used by online retailers to increase sales by exploiting consumer valuation uncertainty. Recently, some online retailers have started to allow refunds on products sold in advance. On the one hand this reduces the net advance sales, but on the other hand it allows a higher advance sales price. This research is the first to explore the overall effect of allowing a refund on profits from advance sales, identifying conditions where advance selling with or without refunds (or no advance selling at all) is best. We analytically compare the profits of three advance selling strategies: none, without refund, and with refund. We show that selling in advance and allowing a refund is optimal for products with a relatively small profit margin and small strategic market size, and that the added profit can be considerable. Our results guide managers in selecting the right advance selling strategy. To facilitate this, we graphically display, based on the two dimensions of regular profit margin and strategic market size, under what conditions the different strategies are optimal.     

Counter-arguing as barriers to environmentally motivated consumption reduction: A multi-country study

This research extends previous literature on environmentally motivated consumption reduction (EMCR) with a cross-cultural investigation across 28 European countries. The paper elucidates how European consumers' knowledge and perceived seriousness of climate change inhibit the activation of counter-arguments, with implications for EMCR. More specifically, counter-arguing is a critical barrier to reduce EMCR. The developed model is based on the novel premise that the contingency variables, which qualify the impeding role of this barrier, are anchored at different levels. To account for individual and societal aspects simultaneously, multi-level analysis combines large-scale data from a Eurobarometer (n = 16,095) with secondary data at the societal level (n = 28). The results confirm that counter-arguments as barriers for EMCR and their attenuation through knowledge and perceived seriousness substantially varies across societies. Our results reveal that the collectivism/individualism dimension is most relevant in qualifying the impact of counter-arguments on EMCR. Building on our findings, impact-level-maps of counter-arguments and country clusters aid international marketers of environmentally friendly products to flexibly tailor their marketing campaigns. For policy-makers, our results further highlight that rather than raising knowledge with educative campaigns, perceptions of seriousness should be targeted to foster EMCR and inhibit counter-arguing.     

A spatial approach to the FDI-growth nexus in Spain: Dealing with the headquarters effect

This paper examines the effects of inward FDI on economic growth across the Spanish regions over the period 1996–2013, paying particular attention to the ‘headquarters effect’, namely that FDI is not always registered where it is effectively made but in the region in which the firm’s headquarters is located. By estimating a panel Spatial Durbin Model to allow for the detection of spatial spillovers, two main findings are reported. First, FDI does foster economic growth. Second, only when the headquarters effect is properly addressed do spatial spillovers arise. Hence, this effect is masking the impact of regional FDI spillovers on growth, which affects the reliability of the results and, consequently, FDI policies choice. Importantly, the results are: a) robust to the way of computing the headquarters effect; b) independent of the spatial weight matrix specification; and c) confirmed when splitting FDI into different industrial and service branches.     

Customizing calories: How rejecting (vs. selecting) ingredients leads to lower calorie estimation and unhealthier food choices

Customization of food products has increased substantially in recent years while the desire for healthiness and an emphasis on understanding and providing calorie information continues to dynamically change the landscape of restaurant retail. The authors report four studies demonstrating that different customization routes (i.e., rejecting alternatives from a full product offering versus adding alternatives to a basic product offering) lead to systematic, but predictable, differences in consumers’ estimations of calories. In particular, this research finds that a rejection (vs. selection) customization process leads consumers to persistently estimate lower calories in the final product, which then improves evaluations of the retailer and leads to unhealthier food choices. These findings occur when consumers estimate calories of the exact same final product using the different paths to customization as well as when they create their own customized final product, while accounting for differences in the quantity and type of ingredients selected, suggesting a very general difference in estimations. This research has important implications for consumers who want to manage their weight and for firms that need to manage consumers’ health perceptions.