Firms are increasingly offering engagement initiatives to facilitate firm–customer interactions or interactions among customers, with the primary goal of fostering emotional and psychological bonds between customers and the firm. Unlike traditional marketing interventions, which are designed to prompt sales, assessing returns on engagement initiatives (RoEI) is more complex because sales are not the primary goal and, often, direct sales are not associated with such initiatives. To assess RoEI across varying institutional contexts, the authors propose and empirically implement a methodological framework to investigate a business-to-business mobile app that a tool manufacturer provides for free to engage its buyers. The data include sales by buyer firms that adopted the app over 15 months, as well as a control group of buyers that did not adopt. The results from a difference-in-differences specification, together with selection on observables and unobservables, show that the app increased the manufacturer's annual sales revenues by 19.11%–22.79%; even after accounting for development costs, it resulted in positive RoEI. This RoEI was higher when buyers created more projects using the app, so customer participation intensity appears to underlie RoEI. This article contributes to engagement literature by providing a methodological framework and empirical evidence on how the benefits of engagement initiatives materialize.

Manpreet Singh Gillis Faculty Marketing at LGC Ludhiana. His primary research interest is in theoretical and empirical modeling focusing on branding and advertising. As a part of his research for PhD, he has developed an interesting model in the area of advertising effectiveness. Jagrook Dawrais a PhD from ICFAI Business School, Hyderabad (India). He worked in the industry for about 6 years, before his teaching assignment with ICFAI. His research interest lies in the area of product and brand management, with special emphasis on store brands. He has some national and international publications to his credit.ABSTRACT Brand equity has been defi ned and measured by different researchers in different ways. While one school of thought measures brand equity as the additional preference a consumer has for a branded product over a similar no-name product, another school of thought led by Aaker defi nes it in terms of a set of assets, popularly called the sources of brand equity. This study measures brand equity using both methods and tries to establish the extent to which they reconcile. We fi rst measure brand equity using conjoint, establishing the part-worths of attribute ' brand ' as brand equity. We then go on to measure Aaker ' s sources of brand equity. Regressing brand equity on these sources of brand equity, we found that Aaker ' s sources were inadequate in explaining brand equity fully. Moreover, some of these sources were highly correlated. Factor analyzing Aaker ' s sources resulted in two factors -cognitive factor and image factor. Further analysis revealed that the image factor plays a mediating role between awareness and brand equity.

The unprecedented number of product recalls in recent years and subsequent low consumer recall compliance raise questions about the role of regulatory agencies in ensuring safety. In this study, the authors develop a conceptual framework to test the impact of a regulator-initiated digital marketing campaign (DMC) on consumer recall compliance. The empirical context is the launch of a nationwide DMC by the U.S. automobile industry’s regulator. The analysis utilizes recall completion data from 296 product recalls active both before and after the DMC’s launch. The results show that the DMC improves consumer recall compliance. In the first four quarters after it was introduced, the DMC increased the number of vehicles fixed, on average, by 20,712 per recall campaign over what was to be expected without the DMC. Regarding boundary conditions, the study finds that the DMC is more effective for recall campaigns with greater media coverage and for those with older recalled products. However, the DMC’s effect is weaker as the time needed to repair a defective component increases. The findings should help regulators make compelling cases for greater resource allocation toward digital initiatives to improve recall compliance.

Crowdfunding has emerged as a market-based solution to give frontline complex public service employees the opportunity to acquire resources by advertising project proposals for donor patrons on crowdfunding platforms. However, whether crowdfunded resources can improve offline service outcomes, and if so, how and when, remains murky. Focusing on the context of public education crowdfunding and applying theories from crowdfunding and services marketing literature, the authors conceptualize that the combination of two factors—namely, teachers' request for resources meant to satisfy unmet heterogeneous (i.e., diverse and evolving) intellectual needs of students and donors' screening and approval (i.e., crowd screening) of promising projects—helps improve student academic achievement. Collating novel panel data from DonorsChoose and California Department of Education, the authors show that (1) crowdfunded resources positively affect student academic achievement, (2) student academic achievement improves with the increase in the heterogeneity of intellectual needs that crowdfunded resources likely satisfy, (3) crowd screening of project proposals plays a critical role in the offline effectiveness of crowdfunded resources, and (4) crowd screening effectiveness depends on the type of project.

Cloud computing is a concept of providing user and application oriented services in a virtual environment. Users can use the various cloud services as per their requirements dynamically. Different users have different requirements in terms of application reliability, performance and fault tolerance. Static and rigid fault tolerance policies provide a consistent degree of fault tolerance as well as overhead. In this research work we have proposed a method to implement dynamic fault tolerance considering customer requirements. The cloud users have been classified in to sub classes as per the fault tolerance requirements. Their jobs have also been classified into compute intensive and data intensive categories. The varying degree of fault tolerance has been applied consisting of replication and input buffer. From the simulation based experiments we have found that the proposed dynamic method performs better than the existing methods.