Some properties of the distribution of an operational ridge estimator

Metrika - The present paper investigates the properties of the sampling distribution of an operational general ridge estimator. Exact expression are given for the moments and their approximations...     

Multiple hypothesis evaluation in auditing

In many audit tasks, auditors evaluate multiple hypotheses to diagnose the situation. Research suggests this is a complex task that individuals have difficulty performing. Further, there is little guidance in professional standards or literature dealing with the many complexities present in the audit environment. Using probability theory, this study derives the appropriate revision of likelihoods for multiple hypotheses given different realistic audit conditions. The analysis shows that the relationships among the hypotheses dramatically impact the use of audit evidence and the resulting pattern of probability revisions. We also identify testable hypotheses to guide future research and discuss practice implications regarding ways to improve the effectiveness of analytical procedures.     

Announcement

In this paper we obtain a small-disturbance approximation to the moment matrix of the limiting distribution of an operational generalized least squares (OGLS) estimator of the mean response vector in a random coefficient model.It is shown that for small samples the moment matrix of the limiting distribution underestimates the small-disturbance approximate moment matrix of the limiting distribution of the OGLS estimator. This suggests that for small samples the ‘standard errors’ of the OGLS estimates should be obtained from the small-disturbance approximate moment matrix of the limiting distribution rather than from the conventional asymptotic moment matrix.     

Impact of component supplier branding on profitability

In recent years, many business-to-business (B2B) component supplier (CS) firms have added branding to their marketing toolbox. By extending the logic of ingredient branding to B2B components, they aim to create “pull” from B2B end customers by building a strong CS brand image among their customers' customers. In contrast with the established “push” approach of building strong relationships with original equipment manufacturers (OEMs), it is unclear whether and under which conditions CS branding is a worthy strategy. On the one hand, anecdotal evidence suggests that suppliers can leverage strong CS brand image in negotiations with increasingly powerful OEMs to enhance their financial performance. On the other hand, many B2B managers believe that branding does not work in their industry context and erodes profitability. We build a data set consisting of survey measures and archival data across a broad set of industries. Our results indicate that the financial outcomes of CS branding largely depend on the characteristics of the CS and OEM industries. Unlike dyadic OEM–CS relationships, which enhance profitability invariably across industry contexts, CS branding is effective only in well-defined situations. CS branding initiatives can enhance return in CS industries with substantial levels of product differentiation and technology intensity. However, unfavorable results may arise in industry contexts in which OEM–end customer relationships or OEM brands are important.     

Product recalls and the moderating role of brand commitment

We assess attenuating and augmenting effects of brand commitment on consumer responses when product recalls occur. Consistent with our theorization, results from a laboratory experiment and an event study show that high levels of brand commitment attenuate negative consumer responses in low-severity product recalls but augment them in high-severity product recalls. Thus, while brand commitment seems to provide a reservoir of goodwill in the former case, it acts as a liability in the latter. These findings add to the extant brand and product recall literature by demonstrating that brand commitment has a complex effect on consumer responses when product recalls occur. Because product recalls are widespread, these findings also have managerial relevance.     

Reexamining dual-class stock

Snapchat’s initial public offering, which provided shares with no voting rights, is a culmination of the growing trend of dual-class shares. It contradicts the precept of one-share, one-vote that is essential for corporate democracy. Snapchat’s action caused an uproar among influential investors. In January 2017, a coalition of the world’s biggest money managers, which together control more than $17 trillion in assets, demanded a total ban on dual-class shares. We reason that the increasing prominence of dual-class stock is explained by the confluence of three economic trends: the growing importance of intangible investments, the rise of activist investors, and the decline of staggered boards and poison pills. A dual-class structure offers immunity against proxy contests initiated by short-term investors. It enables managers to ignore capital market pressures and to avoid myopic actions such as cutting research and development, which hurt companies in the long term. Thus, a dual-class structure is optimal in certain scenarios. We put forth alternatives to dual-class structure that enable managers to maintain control while retaining focus on sustainable value creation.     

Detection of Management Fraud: A Neural Network Approach

The detection of management fraud is an important issue facing the auditing profession. A major contributor to this issue is the Loebbecke and Willingham (1988) conceptual model for the detection of management fraud. A cascaded Logit approach using the Loebbecke and Willingham model was developed in Bell et al. (1993). The present study offers an alternative approach using Artificial Neural Networks (ANNs). This paper develops a successful discriminator of management fraud using both the generalized adaptive neural network architectures (GANNA) and the Adaptive Logic Network (ALN) approaches to designing neural networks. The discriminant functions can distinguish between fraudulent and non-fraudulent companies with superior accuracy to the cascaded Logit results of Bell et al. (1993). Finally, the discriminant function provides a parsimonious set of questions useful for detecting management fraud.     

Understanding the intention to use mobile banking by existing online banking customers: an empirical study

The Indian banking sector can take advantage of the proliferation of smartphones as well as the government’s encouragement of cashless transactions to accelerate the use of mobile and online banking. The purpose of this study is to understand the initial acceptance of mobile banking by existing online banking users. Few studies have focused on online banking users’ behavioural intention to use similar services (such as mobile banking) in India. To this end, a theoretical model was developed using the technology acceptance model, which was extended to cover the adoption factors that influence users of online banking to use mobile banking. These adoption factors comprise perceived ease of use, perceived security, mobile self-efficacy, social influence and customer support. The dependent variable is customers’ behavioural intention to use mobile banking. A partial least squares structural equation modelling analysis was used to test the theoretical model with sample data from 420 online banking customers of various public, private, foreign and co-operative banks in India. The study found that the adoption factors had a significant impact on customers’ behavioural intention to use mobile banking. The findings of this study provide insight into digital banking channels, contribute to existing research on digital banking adoption and will educate banks and financial institutions on the adoption of mobile banking in India.

     

Impact of Socio-Economic factors on Consumption Expenditure through Public Distribution System in rural India

Impact of public distribution system (PDS) on poverty in rural India is established; however, how the households from different socio-economic backgrounds are procuring through PDS, relatively, needs study. With this objective, influence of factors like poverty status, family size, social group, religion, gender and occupation on probability of household incurring consumption expenditure through PDS has been studied by using unit level data of consumer expenditure survey of National Sample Survey Office (NSSO) and multinomial logistic regression technique. The study is restricted to food grains rice and wheat and reveals that probability of consumption, through PDS, of minorities, economically and socially backward classes are higher, in general.

     

On Lindley-like mean correction in the improved estimation of linear regression models

The risks of estimators incorporating the correction to the sample mean in the spirit of Stein and Lindley are approximated in the case of small disturbances.