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The authors propose a semiparametric approach for testing independence between two infinite-order cointegrated vector autoregressive series (IVAR(∞)). The procedures considered can be viewed as extensions of classical methods proposed by Haugh (1976, JASA) and Hong (1996b, Biometrika) for testing independence between stationary univariate time series. The tests are based on the residuals of long autoregressions, hence allowing for computational simplicity, weak assumptions on the form of the underlying process, and a direct interpretation of the results in terms of innovations (or shocks). The test statistics are standardized versions of the sum of weighted squares of residual cross-correlation matrices. The weights depend on a kernel function and a truncation parameter. Multivariate portmanteau statistics can be viewed as a special case of our procedure based on the truncated uniform kernel. The asymptotic distributions of the test statistics under the null hypothesis are derived, and consistency is established against fixed alternatives of serial cross-correlation of unknown form. A simulation study is presented which indicates that the proposed tests have good size and power properties in finite samples.

The issues of development of decisions are very important during formation of the system of management of modern business systems in the conditions of turbulence of external conditions. The ideas of rational structuring of information flows, which are used for decision making, are related to the necessity for development of communicative culture of companies. Quality of interaction between persons that participate in decision making should be assessed by analyzing the ratio of probabilities that characterize quality of information and correctness of decisions and development of a special model.

Companies spend millions on training their sales representatives. Thousands of textbooks have been published; thousands of training videos have been recorded. Hundreds of good pieces of advice and tips for sales representatives have been presented along with hundreds of sales methods and techniques. Probably the largest number of indicators and measures are applied in sales and distribution. On the one hand, this is a result of the fact that sales provide revenue and profit to a company; on the other hand, the concept of management by objectives turns out to be most effective in regional sales teams with reference to sales representatives and methods of performance evaluation. As a result, a whole array of indices has been created which enable the evaluation of sales representatives’ work and make it possible to manage goods distribution in a better way.

The indices presented in this chapter are rooted in the consumer market and are applied most often to this type of market (particularly in relation to fast-moving consumer goods at the level of retail trade). Nevertheless, many of them can be used on other markets (services, means of production) and at other trade levels (wholesale).

Although the values of many indices presented herein are usually calculated by market research agencies and delivered to companies in the form of synthetic results, we have placed the emphasis on the ability to determine them independently, both in descriptive and exemplifying terms. We consider it important to understand the genesis of indices and build the ability to interpret them on that basis. What is significant is that the indices can be interpreted differently; the same index may provide a different assessment of a product’s, brand or company’s position in the market depending on the parameters taken into account. Therefore, we strive to show a certain way of thinking rather than give ready-made recipes and cite ‘proven’ principles. Sales and distribution are dynamic phenomena, and limiting them within the framework of ‘one proper’ interpretation would be an intellectual abuse.

This paper analyzes citations from the first 20 volumes of Advances in Management Accounting using Google Scholar in April and May, 2013.

This study assesses the success of the first 20 volumes of Advances in Management Accounting using citation analysis. Four citation metrics are used. The four citation metrics are: (1) total citations since year of publication until April and May, 2013, (2) citations per author since year of publication until April and May, 2013, (3) citations per year since year of publication until April and May, 2013, and (4) citations per author per year since year of publication until April and May, 2013.

The top 20 authors for each citation metric, the top 20 faculties for each citation metric, and the top 20 doctoral programs for each citation metric are determined. Furthermore, the top 20 articles are determined using two citation metrics and the H-index for Advances in Management Accounting is computed.

Potential doctoral students, current doctoral students, “new” Ph.D.s with an interest in management accounting, current management accounting faculty, department chairs, deans, other administrators, journal editors, and journal publishers will find these results informative.