Search results

The purpose of this paper is to investigate the effect of selected organizational factors on the performance of employees charged with sales forecasting, and to compare this across the different organizational environments of Central-Eastern European (CEE) retail chains.

The research involves seven major pan-European retail chain companies, with a total number of 201 respondents. Data were collected via a questionnaire [computer-aided personal interview (CAPI) and human-aided personal interview (HAPI) method] with a five-point scale evaluation of both dependent (organizational factors) and independent (performance indicator) variables. Cluster analysis was then used to derive the characteristics of average organizational environments, and correlation analysis was used to investigate the direction and size of the performance effect.

The results confirmed that different organizational environments have differing effects on the performance of forecasters. It also showed that the “hard core” factors (performance evaluation and information systems) do not have a dominant effect on employee performance in any of the environments regardless of their quality, and are aggregately outclassed by “soft” factors (communication lines and management support). Finally, the research indicated that among the personal attributes related to individual forecasters, domain and forecasting work experience have significant, beneficial effects on forecasting performance, whereas formal education level was detected to have a negative effect and can be, at best, considered as non-contributor.

The research results along with available literature enable us to define four management theses (focus on system, less on people; soft factors are equal to hard ones; higher formal education does not contribute to forecasting performance; and do not overestimate the social and morale situation on the working place) as well as four stages of organizational development, creating a practitioner’s guide to necessary steps to improve an environment’s key factors, i.e. performance evaluation, information systems and forecasting work experience.

Although there are regular studies examining the effect of organizational factors on employee performance, very few have explored this relationship in a forecasting context, i.e. in the case of employees charged with sales forecasting. Furthermore, the paper brings evidence on this topic from the CEE area, which is not covered in most prominent forecasting management studies.

More frequent re‐forecasting is becoming an important topic on corporate agendas and is seen by many to be the only way to keep financial performance on track at a time when revenues are becoming less predictable. The paper aims to investigate this topic.

For the past four years ALG Software has commissioned a study of the re‐forecasting practices in a sample of the top organisations in the UK by revenue. The objective of the study is to benchmark how frequently the UK's leading organisations currently re‐forecast and what their goals are for the future.

The results show that the majority of organisations remain dissatisfied with the frequency with which they re‐forecast and wish to re‐forecast more frequently. However, the findings also show that many organisations feel that they cannot re‐forecast as often or as quickly as they would like. In fact, evidence suggests that little, if any, progress has been made during the last four years since this survey was first commissioned. This is due to either the amount of time it takes operational line managers to re‐forecast their resource requirements, or the amount of time it takes the finance function to complete a round of re‐forecasting. The type of application used for budgeting and re‐forecasting appears to make little difference to the time it takes organisations to produce an annual budget or complete a re‐forecast. Central to this issue is the use of non‐financial or “operational” data that predicts future resource requirements, and the limitations of the budgeting systems that organisations currently employ. Regardless of the type of application used for budgeting or re‐forecasting, much of this modelling is still done off‐line on spreadsheets.

The paper is of value to finance managers considering choosing a new budgeting application who will need to ensure that the type of operational modelling of non‐financial driver data, currently done offline on spreadsheets by line managers, can be seamlessly integrated into the central budgeting model.

In the last four years, since Volume I of this Bibliography first appeared, there has been an explosion of literature in all the main functional areas of business. This wealth of material poses problems for the researcher in management studies — and, of course, for the librarian: uncovering what has been written in any one area is not an easy task. This volume aims to help the librarian and the researcher overcome some of the immediate problems of identification of material. It is an annotated bibliography of management, drawing on the wide variety of literature produced by MCB University Press. Over the last four years, MCB University Press has produced an extensive range of books and serial publications covering most of the established and many of the developing areas of management. This volume, in conjunction with Volume I, provides a guide to all the material published so far.

The purpose of the paper is to better measure the risks and volatility of the Bitcoin market by using the proposed novel risk measurement model.

The joint regression analysis of value at risk (VaR) and expected shortfall (ES) can effectively overcome the non-elicitability problem of ES to better measure the risks and volatility of financial markets. And because of the incomparable advantages of the long- and short-term memory (LSTM) model in processing non-linear time series, the paper embeds LSTM into the joint regression combined forecasting framework of VaR and ES, constructs a joint regression combined forecasting model based on LSTM for jointly measuring VaR and ES, i.e. the LSTM-joint-combined (LSTM-J-C) model, and uses it to investigate the risks of the Bitcoin market.

Empirical results show that the proposed LSTM-J-C model can improve forecasting performance of VaR and ES in the Bitcoin market more effectively compared with the historical simulation, the GARCH model and the joint regression combined forecasting model.

The proposed LSTM-J-C model can provide theoretical support and practical guidance to cryptocurrency market investors, policy makers and regulatory agencies for measuring and controlling cryptocurrency market risks.

A novel risk measurement model, namely LSTM-J-C model, is proposed to jointly estimate VaR and ES of Bitcoin. On the other hand, the proposed LSTM-J-C model provides risk managers more accurate forecasts of volatility in the Bitcoin market.

The purpose of this paper is to study the economic benefits of a pro-active disclosure strategy in a dynamic environment. More specifically, the paper explores the relationships between customer value disclosure, analyst following, and earnings forecasts, taking into account environmental dynamism as captured by R&D intensity, sales variability, and the reverse of industry concentration.

The paper considers the possibility that a firm's information dynamics may simultaneously affect disclosure strategy, analyst following, and analyst forecasts. Regression models are used in the testing of the hypotheses.

First, results show that customer value disclosure is positively associated with analyst following and consensus in analyst earning forecasts. Second, environmental dynamism enhances the association between customer value disclosure and analyst following as well as consensus among analysts. Those results suggest that customer metrics attract analysts and improve their ability to forecast earnings. Moreover, customer value disclosure appears particularly relevant for forecasting earnings of firms involved in dynamic environments.

Customer value disclosure would allow financial analysts to better assess future earnings in a context of uncertainty. Moreover, analysts may be reluctant to follow a firm facing high environmental dynamism without a clear corporate disclosure commitment. In such a context, managers may consider disclosing strategic information in an attempt to attract financial analysts.

The findings reveal that the relations between customer value disclosure, analyst following, and analyst forecasts are not straightforward but are affected by a firm's environmental uncertainty.

This paper applies the variable forgetting factor and the fixed forgetting factor to financial time-series analysis, and establishes the linkage for the first time between the variable forgetting factor approach and kernel smoothing. We then demonstrate the use of the proposed variable forgetting factor approach to undertake forecasting of the Euro's exchange rates and the CRSP monthly net asset values (NAV). For both applications, the findings show that the kernel bandwidth so determined can improve the forecasting performance.

This chapter considers financial instability as a phenomenon endogenous to the functioning of capitalism. Consequently, it seeks to identify the main sources and different forms of the latter in financialised capitalism. According to Keynes, capital assets prices are conceived as the expression of financial conventions. It is, therefore, important to distinguish between the returns expected by company directors, bankers, holders of equity titles, risk-takers and, in contrast, risk-averse holders of debt securities. Minsky enriches the analysis by attributing a decisive role to the leverage effect, at the origin of an accumulation of financial weaknesses in the balance sheets of non-financial agents during the expansion phases preceding financial crises. Regulation theory leads to the introduction of a distinction between the financial accelerator and the leverage effect. The first establishes a procyclical relationship at the macroeconomic level between the price of capital assets and the debt ratio of non-financial agents; the second acts at the microeconomic level through shareholder corporate governance, which determines the institutional conditions inciting firm directors to integrate shareholder expectations into their return forecasts. The empirical analysis identifies three forms of financial instability in financialised capitalism: the long-term financial cycle governed by the debt ratio of non-financial agents; the business cycle governed by the impact of stock prices on investment; and the short-term or even very short-term expected return revisions of financial actors. Its originality is to show that these three forms of instability acquire different characteristics depending on the national economy considered.

The literature on financial statement analysis attempts to improve fundamental analysis and to identify market inefficiencies with respect to financial statement information.

In this paper, the author reviews the extant research on financial statement analysis.

The author then provides some preliminary evidence using Chinese data and offer suggestions for future research, with a focus on utilising unique features of the Chinese business environment as motivation.

The author notes that there has been no work that the author could locate specifically on Chinese FSA research. The unique business environment in China, relative to the US where the vast majority of this work has been conducted, should motivate any studies, especially given the author documents the robust finding in terms of the mean reversion in profitability.

Examines various models of retail branch performance. Relates branch success to the various characteristics of its marketing environment. Suggests that these assist decision making not only in planning for new branch development, but also in evaluating the performance of existing branches.

The purpose of this paper is to explore the role of accounting in shaping charities' financial resilience during the COVID-19 crisis.

A case study of a charity was conducted. The financial resilience framework (Barbera et al., 2017) was applied to explore how accounting contributes to charities' capacity to cope with crises.

The results show how the accounting practices of budgeting, forecasting and performance reporting (financial and nonfinancial), as well as “accounting talk,” form part of the anticipatory and coping capacities that provided the charity the financial resilience to navigate the COVID-19 crisis.

The paper evidences the important role accounting plays in establishing financial resilience to help charities cope with crises, particularly the importance of having accounting practices established prior to a crisis and accounting information forming part of managers' discussions. The study also demonstrates that financial reserves have an important buffering capacity role.

This is the first paper to examine the role of accounting within a charity during an economic crisis. The authors explore the role of accounting in shaping a charity's financial resilience and demonstrate the applicability of the financial resilience framework to a sudden, unexpected crisis such as COVID-19. They extend the accounting talk literature by highlighting its importance to a charity and during a crisis.