Search results

The purpose of this paper is to investigate the association between bargain purchase gains (BPGs) booked by the acquirer and smoothing of acquirers’ earning performance across time.

The authors use a sample of 122 bargain purchase acquisitions in non-financial industries from 2009 to 2012 and a pair-match control group of 122 goodwill acquisitions.

The authors find that BPGs, and in particular, the Level-3 fair value estimates of intangible assets acquired, have consistently been used to smooth earnings but that such smoothing activities are not associated with long-term market returns.

This study is the first one to investigate bargain purchase acquisitions in a broad range of non-financial industries and suggests that managers are using the valuation of intangibles to avoid unfavorable earnings even though these valuations are not credible to investors.

Acquisitions of bankrupt firms can be beneficial because the bankrupt targets may be more receptive to acquisition offers for the purpose of survival, courts can override any resistance that may occur, information on the target is disclosed within the formal reorganization plan, acquirers can accrue tax benefits, and acquirers may assume favorable debt contracts. However, two disadvantages of acquiring a bankrupt firm are higher costs of completing the conversion and the high degree of uncertainty about the target's future cash flows. Results of our analysis suggest that firms announcing acquisitions of bankrupt targets experience favorable wealth effects. Thus, the market appears to anticipate that the present value of future cash flows derived from the target will exceed the cost of the acquisition. Our analysis also found that acquisitions of bankrupt firms yield more favorable wealth effects than acquisitions of healthy firms. The acquisitions of bankrupt firms were especially well received by the market when the acquirer was the sole bidder and when the target's business was closely related to that of the acquirer.

The products of some firms emerge neither from new technology developments nor from attempting to address articulated consumers’ needs, but from a company-internal design-driven approach. To explore this design-driven approach, we propose a construct, design orientation, as a firm’s ability to integrate functionality, aesthetics, and meaning in its new products. We hypothesize relationships between a firm’s design orientation, customer orientation, technological orientation, and willingness to cannibalize on its new product performance.

We use data from surveys of senior marketing executives entrusted with design in 252 US firms, we validate the construct of design orientation and establish its distinctiveness from related constructs of creativity, technological orientation, and customer orientation. Using a structural equation modeling approach, we test the hypotheses and find support for them.

Individually, design orientation, technological orientation, and customer orientation improve new product performance. In addition, customer orientation decreases the positive effect of design orientation while willingness to cannibalize increases the positive effect of design orientation on new product performance.

More than two-thirds of respondents (69%) perceive that their firm can improve its new product performance by increasing its design orientation, an overlooked organizational capability.

Although practitioners have acknowledged the importance of design as a strategic marketing issue, there is little in the literature on how firms can benefit from building capabilities in the design domain, the issue we focus on in this research.

While Big Data offer marketing managers information that is high in volume, variety, velocity, and veracity (the 4Vs), these features wouldn’t necessarily improve their decision-making. Managers would still be vulnerable to confirmation bias, control illusions, communication problems, and confidence issues (the 4Cs). The authors argue that traditional remedies for such biases don’t go far enough and propose a lean start-up approach to data-based learning in marketing management. Specifically, they focus on the marketing analytics component of Big Data and how adaptations of the lean start-up methodology can be used in some combination with such analytics to help marketing managers improve their decision-making and innovation process. Beyond the often discussed technical obstacles and operational costs associated with handling Big Data, this chapter contributes by analyzing the various learning and decision-making problems that can emerge once the 4Vs of Big Data have materialized.

This paper examines the environmental disclosure decisions of New Zealand firms in response to political costs arising from the enactment of the Resource Management Act (RMA) in 1991. Unlike prior disclosure studies, this study provides a more rigorous test of the political cost hypothesis by identifying firms that were directly affected by RMA and by measuring the change in environmental disclosures over the pre‐ to post‐RMA period. We hypothesise that the increase in environmental disclosures will be a positive function of the firm's political visibility. Using six different measures of political visibility and three composite measures derived from a factor analysis of the individual measures, the evidence indicates that, in general, politically visible firms were more likely to increase their environmental disclosures after RMA whether the change was measured on a dichotomous or continuous basis. Overall these results provide support for the political cost hypothesis.

This paper has two purposes: to use polarisation to identify variations in loyalty and to apply polarisation to an important non‐brand attribute, price.

A comprehensive revealed preference data set of wine purchases is used to apply polarisation. Polarisation was defined in two ways: as a function of the beta binomial distribution (BBD) to give a measure of loyalty for an alternative; and as a function of the Dirichlet multinomial distribution (DMD) to give a baseline level of loyalty. Variations were identified by analysing the differences between the BBD and DMD.

Polarisation was shown to be one way of identifying variation across price tiers. In the empirical example used, the DMD model is violated with the price tiers not being directly substitutable with one another. Buyers show excess loyalty towards the lowest and highest price tier levels. One tier shows “change‐of‐pace” loyalty. Small brands do better when they focus on high loyalty tiers, middle brands compete in the change‐of‐pace tier and large brands do well across all tiers.

Very little work has been undertaken into price tier loyalty and no known empirical research has been undertaken into behavioural loyalty to price tiers in wine. Very little empirical research has considered the association between excess loyalty for attribute levels (such as price tiers) and the existence of niche, change‐of‐pace and reinforcing brands.