Business Tendency Research Articles

Indicators For Measuring The Digital Environment Of Manufacturing Enterprises In Russia Based On Data From Business Tendency Surveys

The paper discusses various aspects of digital environment and activity of enterprises from the Russian manufacturing sector in 2020 using the evidence from business tendency surveys. Based on aggregate sectoral and industrial assessments, such as the Digital Climate Index (DCI), the Digital Intensity Index (DII), the Digital Employment Index (DEI) and the Digital Vulnerability index (DVI), the dynamics of digital development during the COVID-19 crisis in 2020 is described. In general, according to the results obtained, we can conclude that, despite all the negative consequences and uncertainty associated, 2020 became a very significant point in terms of the digital transformation in manufacturing. Manufacturing businesses were both relatively resilient to the adverse business trends caused by the pandemic and were able to absorb the positive digital momentum generated by the pandemic

Analisis Persepsi Bisnis Terhadap Persepsi Konsumen Melalui Indeks Tendensi Bisnis (ITB) dan Indeks Tendensi Konsumen (ITK) di Indonesia.

The condition of the global economy is greatly affected by the movements of economic agents itself. After the global crisis that happened years ago, 2018 the state of the global economy not fully recovered. In the moment the role of economic agents so influenced by the information received and how that information is processed, so that will affect the perception on an object of that information. And in the end will have an impact on decision making right or not. In this research
 will analyze perception on the impact of business to consumer perception shown through indicators of the business tendency index on consumer tendency index. The research was conducted using secondary data from the central bureau of statistics by focusing on a span of years the global crisis that is 2017-2019 or pre until post crisis. The method used is descriptive statistics analysis. The result of which is known that the perception business have a positive influence on consumer perception in the view through the business tendency index on consumer tendency index

Machine Learning and Nowcasts of Swedish GDP

The current article investigates if machine learning techniques, more specifically the nearest neighbor algorithm, can be used for nowcasting Swedish GDP growth utilizing business tendency survey data. The results show that the machine learning algorithm can work at least as well as the linear indicator models that have become standard workhorses in Swedish GDP growth nowcasting. This is an indication that nowcasting model suits could benefit from including also machine learning methods going forward.

Forecasting Employment In Small Businesses In Russia: The Relevance of Business Tendency Surveys

The Article Studies The Predictive Capabilities Of Qualitative Assessments Of Employment Expectations Obtained From Business Tendency Observations Of Entrepreneurial Activity, Which Are Currently A Widespread Source Of Economic Information Both In National And International Practice. The Study Is Based On Market Surveys Conducted By Rosstat, Which Characterize The Expected Level Of Business Activity In The Segment Of Small Enterprises From The 1st Quarter Of 2008 To The 2nd Quarter Of 2019. The Aim Of The Study Is To Prove The Existence Of A Stable Statistically Significant Relationship Between Predicted Estimates Of Employment With The Dynamics Of Growth Rate Cycles Of The Corresponding Quantitative Statistical Macro-Aggregates In Various Sectors And, Therefore, The Relevance Of Predictive Models Of Employment Change Based On The Results Of Business Surveys. It Is Shown That Entrepreneurial Assessments And Expectations Are Effective Predictive Indicators For Predicting Employment Dynamics In The Short Term (Two To Four Months) And Identifying Turning Points In Employment Dynamics In The Small Sector. Small Business, As One Of The Most Sensitive Segments, Is One Of The First To React To The Current Changes, Which Makes Forecasting In This Segment Especially Important.

Stress Testing in Statistical Modeling of Business Activity in Conditions of Market Shocks

The authors proposed an original method of stress testing in statistical modeling of business activity based on the results of business tendency surveys to study possible scenarios for the development triggered by external unforeseen supply and demand shocks, as in the case of the COVID-19 pandemic. The article also provides an overview of existing approaches in the field of stress testing and the construction of stress indices with an emphasis on methods based on vector autoregressive models and their various modifications. Thus, the article aims to adapt existing methods of macro-level stress testing for their use based on the results of business tendency surveys.The basis for empirical calculations was the data from business tendency surveys of the leaders of Russian manufacturing enterprises, reflecting their combined estimates of the current state of business activity. The methods used in the article included: firstly, the formation of four composite indices based on the results of business tendency surveys from 2008 to March 2020, reflecting various aspects of business activity of enterprises (demand index, production index, financial index and employment index); secondly, the construction of the BVAR (Bayesian vector autoregression) model and its application for studying and comparing various forecast scenarios of index reactions to market shocks.The results of the study, forecasts of the dynamics of indices were obtained as a reaction to four possible shock scenarios: short-term, V-, W-, and U-shaped. Moreover, for each of the scenarios, cases of shocks from the side of demand, production and their simultaneous impact are presented.The conclusions based on the results of this study point to the key role of demand in the dynamics of all the considered indices and to the relatively greater sensitivity of the employment index in relation to the demand index and the finance index in relation to the production index. W-shaped shock was the worst of the four scenarios considered.Conclusions based on the study results indicate the vital role of demand in the dynamics of all the indices under consideration, the Wshaped shock, as the worst of the considered scenarios, as well as the relatively higher sensitivity of the employment index to the demand index and the finance index to the production index.

Investigating the Housing Market Bubbles and the Predictive Nature of Returns in Turkey

This paper investigates the housing market bubbles and the predictive nature of returns in Turkey by employing the Fully Modified OLS and the Dynamic OLS on time series data from January 2010-January 2019.The study provides new evidence on the long run boom in Turkish house prices. The drivers behind changes in house prises are discussed, ranging from accommodation services, construction and business tendency to changes in rent for housing. The results reveal a positive relationship between accommodation services and house prices at a significance level of 1%. Accordingly, a positive association exists amid construction and business tendency with house sales price. On a final note, average housing rents show a negative and insignificant response to changes in house sale prices in Turkey.

The Role of Barriers to the Activity of Industrial Enterprises in the Evaluation of the Business Tendency in Poland

Abstract Research background: Surveys of entrepreneurs regarding the assessment of conditions for conducting business activity are carried out by several institutions. They focus on business climate indicators but in parallel they report on numerous barriers to economic activity. The paper examines the barriers that hinder business operations to manufacturing enterprises in Poland. Purpose: The purpose of the paper is to analyse the barriers to business activity and their role in entrepreneurs’ assessment of their general economic situation. It has been hypothesized that statistically significant barriers to economic activity that affect the assessment of the general economic situation by entrepreneurs can be determined. Research methodology: The analysis was based on the Central Statistical Office data from the business tendency survey in manufacturing enterprises spanning the period 2003–2019, broken down into groups of small, medium-sized and large enterprises. Correlation measures and regression models were used. Results: The results allow indicating several barriers that have a significant impact on the assessment of the current economic situation by entrepreneurs. This impact varies depending on the size of the enterprise. No significant relationship was found between the barriers and the assessment of the expected economic situation. Novelty: The paper contributes to studies on business tendency surveys. It develops a detailed analysis of the barriers to economic activity, takes into account the size of enterprises and examines the influence of business barriers on the assessment of the economic situation by entrepreneurs.

Stress Testing as a Tool for Monitoring and Modelling the Dynamics of Business Activity of Manufacturing Enterprises in Russia in the Face of Market Shocks: Short-term Scenarios of Industry Tendencies

The article proposes a methodology for using macro-level stress testing based on the results of business tendency surveys to study possible scenarios for the development of crisis dynamics triggered by external unforeseen supply and demand shocks, as in the case of the COVID-19 pandemic, as well as a review of existing approaches in the field of stress testing and building stress indices with an emphasis on methods based on vector autoregressive models and their various modifications. The basis for empirical calculations is data from business tendency surveys of the leaders of Russian manufacturing enterprises, reflecting their combined estimates of the current state of business activity. Based on the results of business tendency surveys, four composite indices were formed reflecting various aspects of business activity of enterprises: demand index, production index, finance index and employment index. Index values calculated monthly from 2008 to March 2020 were used to build the Bayesian vector autoregressive model (BVAR). This model was used to predict the dynamics of indices under the condition of four possible shock scenarios: short-term shock, V-shaped shock, W-shaped shock and U-shaped shock. Moreover, for each of the scenarios, cases of a shock of demand, a shock of production, and a simultaneous shock of demand and production were separately considered. The results indicated the key role of demand in the dynamics of all the indices under consideration, the W-shaped shock, as the worst of the considered scenarios, as well as the relatively greater sensitivity of the employment index to the demand index and the finance index to the production index.

Using Economic Barometers to Analyze the Impact of the COVID-19 Pandemic on the National Economies

Bearing in mind a number of factors, well-known analytical companies and individual economists have been warning over a long time about the impending recession of the global economy. But the unexpected powerful impact on it from the pandemic can aggravate even the worst projections. Analysts are attempting to predict the economy development at global, regional and country level, in order to grasp and prevent future negative effects of the pandemic in all the spheres of human life. 
 Now there exists a variety of qualitative indicators based on information from Business Tendency Survey and Consumer Sentiment Survey. Respectable international and national institutions use these indicators to quickly assess the current economic situation and predict its change for the several forthcoming quarters. These indicators are considered as very sensitive to any kind of events taking place in the economic and social life, because they are capable to provide the earliest signals of future change in the economy.
 The article contains a review of the dynamics of changes in the Global Economic Barometers computed and analyzed by well-known analytical institutions, and the barometers’ capacity to reflect the new pandemic’s impact on the global economy. The barometers provide up-to-date information about changes in the economy in the current month, with a strong lead over the official quantitative information.
 To estimate the pandemic’s impact on the development of Ukrainian economy, the author proposes to use Economic Sentiment Indicator and Business Confidence Indicators in the industry and the retail trade (for investigating the supply and demand), which are computed by the official statistics on the basis of qualitative information obtained from the surveys. These indicators are harmonized from the analogous European indicators, but issued with the quarter periodicity now. The conclusion is made about the urgent need to adopt the monthly periodicity for these and other barometers, created according to the European methodology, to enable for quick demonstration of the pandemic’s impact on the development of the Ukrainian economy. Also, it is proposed to search for new barometers that would be capable of providing for a more accurate reflection of change in the Ukrainian economy.

Peculiarities of Predicting Business Cycles in the Ukrainian Economy

It is argued in the article that any common person is able to get an idea about the economy’s conditions and its forthcoming change, if he/she learns information Business Tendency Surveys (BTS), i. e. with combination indicators computed on the basis of indicators from these surveys.
 A review of the methods for constructing several types of integral composite indicators, based on indicators of BTS of enterprises by selected economic activities, is provided. Indicators of business climate, computed by the methodology of ifo-Institute and European Commission, and indicators of confidence by economic activity are analyzed. Being ahead of the curve, these indicators give good signals on change in the phases of business activity cycles in European economies and allow one to have rather precise short-term predictions of change in GDP and output by economic activity. 
 The analysis covers dynamic series of these indicators for the Ukrainian economy, with making the conclusion that now only the indicators of confidences for four economic activities can be used for predicting the business cycle for 2 to 3 quarters. The Business Climate Indicator, computed by the European methodology, has good correlation with GDP, but it is only one quarter ahead of it. The Business Climate Indicator, computed by the methodology of ifo-Institute, did show rather good correlation with GDP, but could not demonstrate its good qualities as for the German economy. Unfortunately, this indicator could be computed only for the period before 2013, because subsequently its components were withdrawn from survey questionnaires. 
 One of the main recommendations given in the article is as follows: an organization performing BTS of enterprises (namely, the State Statistics Service of Ukraine) needs to more actively propagate the information about various composite indicators that can obviously be demanded by a broad range of statistical information users. These indicators should be, inter alia, displayed on the home page of the official web-site of the State Statistics Service of Ukraine together with hot news (probably, in a graph form together with macroeconomic indicators).

Economic Development and Cyclical Sentiment of Russian Entrepreneurs After the Recession in 2014-2016

The core objective of the study, results of which are summarized in this article, is to determine the effectiveness of using assessments of economic agents in the analysis of sectoral and macroeconomic development. The paper tests the hypothesis of the cross impact of economic growth and entrepreneurial behavior. It is assumed that economical cyclicity is produced not only by macroeconomic shocks, but also by the impulses generated in the business environment. The sentiment and expectations of entrepreneurs are considered in this case both as a consequence of the ongoing economic events, and as a warning factor affecting the economic decision-making.To test the hypothesis, the authors used results of all sectoral business tendency monitoring of the HSE and Rosstat, which reflect the aggregate sentiment and expectations of about 24 thousand entrepreneurs and 5 thousand consumers. The monitoring results are combined into the Economic Sentiment Indicator (ESI), which calculation algorithm is based on the generally accepted international methodology and is updated taking into account the specifics of the Russian economy.The joint decomposition of the time series of the ESI and the reference series of GDP growth with extracting growth cycles and the dating turning points confirms the cyclical correspondence of the dynamics of the analyzed indicators. An empirical consistency of ESI and GDP time series is revealed based on cross-correlations, a long-term linear regression and through a two-dimensional vector autoregression model. This model is used for short-term forecasting; the forecasting results indicate an unstable and slow acceleration of GDP growth in 2020.Given the ESI calculation efficiency and a noticeable advance in its publication compared to publication of official data on GDP growth, as well as ESI statistical effectiveness, it can be concluded that the aggregate estimates of entrepreneurial and consumer sentiment accumulated over a 20-year period are acceptable and reliable as leading information on economic growth in the country.

Information Content of Russian Services Surveys

This paper explores the information content of a business tendency survey on the service sector in Russia from 2012 to 2018. Two alternative survey-based indices were developed: a traditional confidence indicator as a simple arithmetic mean of the balance statistics of three respondents’ replies and a business climate indicator (BCI) as the first component of five balances. The latter indicator is expected to perform better in terms of tracking a reference quantitative variable (GDP growth). The survey results reveal a six-year negative trend in two composite indicators and the other balances of the respondents’ opinions. Despite a slight improvement in 2017 and 2018, the business climate in the service sector remains unfavourable. The dynamics of confidence and business climate indicators have a lagging nature relative to GDP growth; however, BCI performs slightly better in terms of a synchronous correlation. The shock in BCI in the framework of the bivariate VAR model produces a statistically significant positive response of GDP, which reaches a peak in the second quarter after the shock. The insufficient time series of survey results limits the cyclical analysis of BCI; however, BCI can be used as a main composite indicator for analysing the development of the service sector.

Digital Transformation In Manufacturing: Drivers, Barriers, And Benefits

This paper investigates the drivers, barriers, and benefits that can be associated with management decisions regarding the implementation of digital technologies in Russian manufacturing enterprises. The empirical basis of the study is the results of the business tendencies surveys for 2018 and 2019. Potential factors for the introduction of digital technologies were divided into three groups: drivers of business activity (production and economic parameters), drivers of digital activity (parameters characterizing the level of enterprise involvement in digital processes) and barriers, preventing the enterprise from transitioning to digital transformation. In the first part, regression analysis is used to identify the relevant factors among the drivers and barriers. In the second part, the benefits expected by enterprise managers from the implementation of individual digital technologies are revealed. Significant drivers are the number of specialists working in the enterprise in the field of information and communication technology (ICT), the presence of a developed strategy in the field of digital technologies, involvement in the government’s digital agenda, and a positive perception of the economic situation at the enterprise by its management. Among the expected benefits, the most important are the optimization of production and logistics operations, increasing the level of customer service and expanding the customer base.

The impact of Islamic bank financing on business

From the test results concluded that the Local Number Index (LNI) variable (business tendency index) affects Local Number Portability (LNP) variable (Islamic bank financing). The LNP variable (Islamic bank financing) does not affect this variable (business tendency index). So, there is one-way causality from the LNI (business tendency index) to LNP (Islamic bank financing). Other statistical test results showed that there is a long-term relationship between Islamic bank financing and business tendency. This is clarified by the results obtained from Johansen cointegration test. The result of cointegration test in this research is there is long-term relationship between syariah bank financing and business tendency. From the test results can be seen that the trace statistic is greater than the critical value of 5%. So in the long term, Islamic financing variables and business tendencies will affect each other. This shows that the financing of sharia banks whose allocation of financing is directed to the real sector, even forbidden to finance riba investments and speculation, will drive the business nationally, and vice versa, business that runs well and smoothly, will contribute to the development of Islamic banking performance.

Economic uncertainty in South Africa

The idea that heightened uncertainty among firms contributed to the Great Recession and the lacklustre subsequent recovery has inspired a substantial literature examining the impact of changes in uncertainty on output and investment decisions. Yet to date there has been little research on business uncertainty in emerging markets. This paper is one of the first to develop a set of survey-based proxies for business uncertainty for an emerging market, South Africa, based on micro-data from business tendency surveys. These survey-based proxies are combined with more common measures of uncertainty, based on financial data and text mining, to obtain a composite measure of economic uncertainty. The paper then examines whether the uncertainty indicators have plausible and significant relationships with real economic activity, even after controlling for other economic variables. The indicators exhibit a significant negative correlation with real GDP growth, consistent with the findings for developed countries, and a positive shock to uncertainty is generally followed by a significant decrease in real activity growth.

Features of the Conjuncture Measurement of Entrepreneurs’ Digital Activity in Russia: Approach, Indicators, Pilot Results

The process of the digitalization of economic activity currently raises many questions of economic and social policy in Russia that need to be solved with relevant statistical and analytical data.In this case, it is important to significantly increase the sources of efficient, accessible and comparable data on sectoral digitalization. The authors believe that the opinions and assessments of direct participants of digital events (economic agents from various kinds of economic activity) should also be taken into account when forming targeted decisions of policymakers aimed at the inclusive growth of the national economy, including through such force as digitalization.Therefore, in 2018 the Centre for Business Tendencies Studies at National Research University Higher School of Economics launched the pilot project focused on measuring the digital activity of Russian enterprises of main types of economic activity. The authors define the main task of the study as the development of such criteria for measuring the industry’s digital market conditions, sample requirements for respondents and a system of indicators that together with the results of the pilot surveys would allow the expert community to actually provide effective data and analytical support to entrepreneurs with forming of sectoral digital platforms.The main idea of the study is that the success of the country in promoting digital technologies is largely related to the possibilities of collecting large-scale qualitative data on digital trends, barriers and effects comparable to international counterparts.The review presents the main methodological principles and first results of pilot market surveys among industrial and commercial enterprises in Russia and outlines criteria for selecting indicators for the first pilot sampling. As an example, the section of the article devoted to key results of the 2018 pilot survey of industry uses analysis of digital transformation in medium-size and large manufacturing enterprises.Innovations in the 2019 pilot survey are addressed as an independent direction. In this regard the article notes that the survey program involves measuring ICTs capabilities and potential to increase resource and environmental efficiency in industry, evaluating investment activities related to green growth and aimed at the development and dissemination of green technologies and achieving environmental goals, assessing final consumption (demand) for environmental goods in trade, accounting for the development ICT technologies aimed at greening and resource efficiency by organizations.The article concludes that taking into account the first results of the market survey, the basic requirements for a system of market indicators were determined. These requirements reflect the level, directions, intensity, dividends, and effectiveness of digital transformation of the main kinds of economic activities for a more representative consideration of the digital contribution to GDP growth.

Exploring the dynamics of business survey data using Markov models

Business tendency surveys are widely used for monitoring economic activity. They provide timely feedback on the current business conditions and outlook. We identify the unobserved macroeconomic factors behind the distribution of quarterly responses by Austrian firms on the questions concerning the current business climate and production. The aggregate models identify two macroeconomic regimes: upturn and downturn. Their dynamics is modeled using a regime-switching matrix. The micro-founded models envision dependent responses by the firms, so that a favorable or an adverse unobserved common macroeconomic factor increases the frequency of optimistic or pessimistic responses. The corresponding conditional transition probabilities are estimated using a coupling scheme. Extensions address the sector dimension and introduce dynamic common tendencies modeled with a hidden Markov chain.

Corporate water management systems and incentives to self-discipline

Purpose Water management is an emerging practice. This paper aims to propose a theoretical model of a corporate water management system (WMS) and empirically explores whether superior water management improves water use performance. Design/methodology/approach Our model of WMS consists of 10 structural elements. We draw on self-discipline theory to predict the results and use archival data from the Carbon Disclosure Project to measure and evaluate the overall quality and effectiveness of the water management of our sample companies. Findings Companies motivated to adopt self-discipline tend to proactively implement high-quality WMSs. However, further analyses suggest that water management without regulatory sanctions appears insufficient for reducing water usage, at least in the short term. Overall, this study reveals a clear and growing tendency for businesses to manage water risks and a corresponding momentum toward more rigid control of water consumption. Research limitations/implications Corporate participation in the Carbon Disclosure Project survey is voluntary. Thus, the data in this paper are subject to self-selection bias, and what the companies claim concerning their behavior may not reflect the reality of their business practices. In addition, the inferences drawn here are based on data from only large firms. Future researchers could investigate whether and how corporate WMS continued to develop or decline in recent years, and how such practices integrate with other aspects of management (including carbon and energy). Practical implications This paper responds to water scarcity by exploring how the development of corporate WMS is driven by self-discipline motivation. This study sets out an agenda for the future of water accounting and management which can be used to guide research and stimulate extension in practice. Governments and non-governmental organizations may utilize the results to guide and bind corporations to achieve sustainability. Social implications The efficient use of freshwater is essential for sustainability, but limited studies have addressed the issue. The current paper explores this important issue, and our findings suggest regulatory institution is necessary to effectively enhance water usage. Originality/value This paper represents an early attempt to model corporate water management practices. A WMS should facilitate resilience in water management, measurement of water performance, and comparability among firms. This study contributes to the conceptualization and empirical assessment of self-discipline in motivated water management and enhances the validity and applicability of the theory of self-disciplining in sustainability research.

A Multifold Perspective of Knowledge Sharing and Virtual Teams: The Development of An IMOI Model

Knowledge has been recognized as an asset for the competitive advantage of organizations. Finding avenues for augmenting the organization’s value represents a continuous endeavor for managers. Although business tendencies emphasize the core role of teams in the development and implementation of knowledge management strategies, there is limited research on how virtual teams may contribute to the acquisition and distribution of knowledge through sharing dynamics. Accomplishing this shift in perspective requires comprehension of the necessary components leading to these opportunities in virtual teams. This review employs a systems thinking approach and develops an input-mediator-outcome-input (IMOI) model to guide the identification of the factors that organizations must possess to promote and facilitate knowledge-sharing strategies. By building this model based on a literature review from various fields, this study provides practitioners with a multidisciplinary scheme to strengthen the organizational structure and promote innovations based on the exploration and exploitation of this essential resource.

A Multidimensional Classification for the Information Technology Market

This paper expands the existing informational and analytical opportunities of application of the results of business tendency surveys which solve the problem of the loss of valuable statistical information in its traditional aggregation into simple and composite indicators. Based on methods of multidimensional classification, an algorithm of statistical analysis significantly raises the analytical opportunities for the more wide measurement of trajectories of development and short-term fluctuations of branch of the information technology (IT) is developed and discussed. This allows the construction of behavioral models of business tendency data which improve the understanding of the business cycle in more detail. Furthermore the empirical results confirm the possibility of receiving various information which increases the analytical potential of business tendency surveys.