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Evaluation of the effectiveness of information system in optimizing warehouse processes
No full textThe aim of the article was to present research on the application of information systems in optimizing warehouse processes. The theoretical aspects describing the fundamentals of warehouse processes were discussed. The theoretical foundations of information systems were also developed, with particular emphasis on systems used in warehouse processes. The results of conducted research among manufacturing organizations with complex warehouse processes were presented, which declared the implementation of ERP, WMS, and SCM systems. Based on the research findings, conclusions were drawn along with the direction of development in the area of digitizing warehouse processes
Should risk-averse investors target the portfolios of socially responsible companies?
No full textResearch background: Companies are required to implement Corporate Social Responsibility (CSR) policies to mitigate the adverse social and environmental effects of their activities and gain legitimacy in the eyes of society. Sustainability initiatives are costly for companies but, at the same time, they are important value-creation drivers. Retail and institutional investors are increasingly choosing portfolios based on CSR performance. However, the relationship between CSR and market beta has hardly been studied at all in the literature, and no direct comparison of the U.S. and European markets has been conducted.
Purpose of the article: The two fundamental variables that define an investment are return and risk, and the appropriate risk-return combination depends on the profile of the investors. This research aims to analyze the relationship between CSR and market risk, understood as price volatility and measured by market beta in the U.S. and European markets.
Methods: Companies listed in the S&P 500 and Euro Stoxx 300 indexes from 2015 to 2019 were examined using OLS regressions with instrumental variables (IV) and fixed effects panel data.
Findings & value added: The results show that those companies with higher CSR have betas below the market index in the U.S. market as well as lower volatility, and are, therefore, more appropriate choices for risk-averse investors. However, this relationship was not confirmed in the European market. This difference may be justified by two reasons: 1) The non-adherence of the United States to the Kyoto Protocol, resulting in less strict legal regulations than in Europe; 2) In the U.S. market, betas are more aggressive, while in the European market they are more defensive, with little margin for reduction. This research contributes to the current state of knowledge by providing empirical evidence that social, environmental, and corporate governance sustainability practices reduce stock volatility in the U.S. capital market, which is highly relevant for private and institutional investors who make their investments based on moral criteria. The results are current and reliable since they cover a broad and recent period for two of the most important stock market indexes
Factors influencing structural power dynamics in buyer-supplier relationships: a power sources framework and application of the critical incident technique
No full textResearch background: Although the literature on power asymmetry and power dynamics has recognized the issue of factors that cause power shifts in business-to-business relationships, a more systematic approach and research framework regarding the identification of these factors is lacking. There are attempts in business-to-business literature to use the critical incident technique to study dynamic phenomena, but there are no studies on the factors that increase and decrease the power of suppliers in their relationships with dominant buyers.
Purpose of the article: The aim of this paper is to identify the factors that influence the most significant changes in suppliers? power in relationships with dominant buyers. An important objective is also to determine to which power sources the identified factors are assigned. This is crucial for business practitioners, who will be able to adjust their actions when managing a relationship with a dominating partner through knowledge of their own strengths as well as weaknesses.
Methods: The study is based on analysis of questionnaires with open-ended questions, and uses the critical incident technique to investigate the behaviour of dyadic parties at key moments in buyer-seller relationships. We have focused on investigation of manufacturing companies mainly from the furniture, construction, energy and printing industries. The analysis of the data was based on the abductive approach as a combination of inductive and deductive coding.
Findings & value added: In comparison to previous studies, which did not distinguish the level of importance of each factor, we have obtained only those factors with the greatest impact on power dynamics. We have also obtained factors which can decrease suppliers? power, whereas the literature focuses mostly on factors increasing suppliers? power. The research results reveal the factors that affect an increase and decrease in the power of weaker suppliers in relationships with dominant buyers. First- and second-order factors were identified, and subsequently 3 overarching dimensions for each increase and decrease in supplier power were deduced from the results. The most important overall dimension for the increase in power was the building of suppliers\u27 power capabilities, while the decrease in suppliers\u27 power was most influenced by transactional changes and changes in buyer\u27s expectations. The results can be helpful for managers in focusing their attention on expert power in order to gain knowledge and prepare a practical background for managing asymmetric relationships. It is important to mention that the critical incident technique used in this study has not yet been used to represent power dynamics in B2B relationship literature
Segmentation of e-customers in terms of sustainable last-mile delivery
No full textResearch background: A rapidly developing e-commerce market and growing customer expectations regarding the speed and frequency of deliveries have made the last mile of the supply chain more challenging. The expectations of e-customers increase every year. They choose those companies that deliver goods faster and cheaper than others. A significant group of customers in Poland still selects home delivery. Many of them frequently return products to the retailer. These expectations and behaviour pose a challenge for the transport companies to deliver parcels to individual customers soon after the purchase, sometimes even on the same day. In addition, increasingly frequent deliveries contribute to environmental pollution, congestion, and accidents, as well as more expensive deliveries.
Purpose of the article: The paper aims to identify e-customers? preferences and assess their impact on sustainable last-mile delivery (LMD) in the e-commerce market. The authors have also identified factors influencing e-customers? behaviour to make last-mile delivery more sustainable.
Methods: The conjoint analysis was applied to evaluate a set of profiles defined by selected attributes in order to investigate the overall preferences for the profiles created by the respondents to the survey.
Findings & value added: The segmentation of e-customers according to their preferences connected with last-mile delivery was presented. The added value of the paper is the presentation of the methodology to assess the impact of customer preferences on sustainable last-mile delivery. The obtained results may contribute to the formulation of recommendations for e-commerce and logistics companies regarding the preferences of e-customers to improve the sustainability of last-mile delivery
Impact of enterprise ambidexterity capability and experience learning on cross-border M&A performance: evidence from China
No full textResearch background: Through cross-border mergers and acquisitions (M&A), enterprises in China can improve their technological innovation and organizational management capabilities to make up for the disadvantages of outsiders and enhance their international competitiveness. However, due to the lack of experience, the success rate of cross-border M&A of China enterprises is low, and the performance changes after M&A differ. How to maximize the advantages of cross-border M&A in obtaining technical resources and how to improve the performance of cross-border M&A are important issues that China?s cross-border M&A enterprises and academic circles need to solve.
Purpose of the research: The aim of this study is to analyze the mechanism and boundary conditions of firms? capability to exploit resources (RTC) and capability to explore resources (REC) with regard to cross-border M&A performance from the perspective of experience learning based on organizational learning theory and resource-based theory.
Methods: With 173 China A-share listed companies with cross-border M&A events from 2010 to 2020 as samples, this study uses hierarchical regression analysis to test the impact of REC and RTC on cross-border M&A performance and its mechanism. In the robustness test, this study adopts the measures of changing dependent and independent variables lagged for one year for analysis. In the mechanism test, this study uses intermediary and mediation effect models.
Findings & value added: The results show that RTC and REC have positive effects on the performance of cross-border M&A. Prior experience learning (PE) and vicarious experience learning (VE) increase the probability of companies making cross-border M&A decisions and have positive effects on cross-border M&A performance. Moreover, PE and VE play a partial mediating role in the positive impact of REC and RTC on cross-border M&A performance, respectively. Formal and informal institutional distance weaken the positive effects of REC and RTC on the performance of cross-border M&A. Enterprises in emerging economies should adapt to the institutional environment of the host country to reduce the negative impact of institutional distance while taking advantage of experience learning when carrying out cross-border M&A.
The distribution of wage inequality across municipalities in Mexico: a spatial quantile regres-sion approach
No full textResearch background: According to classical labor economics, wage differences among regions of a country that has free-factor mobility should eventually vanish. However, the level of wage inequality among Mexican territories is increasing. The nature and causes of this discrepancy are worth identifying.
Purpose of the article: To identify the spatial relationship of wage inequality that existed in the Mexican metropolitan system during the years 2010 and 2015.
Methods: We develop a model of wages that considers the interaction between spatial units within a region. Then, we specify a spatial autoregressive model with the average wage per municipality as a dependent variable. This variable is spatially lagged along with other controls such as productivity, schooling, and migration. We combine data from population and economic censuses. Then, we perform a quantile regression to estimate the spatial effect of wage in a region upon quartiles of the wage distribution.
Findings & value added: Wage inequality increases within a given region when the average wage increases in one of said region?s municipalities. This phenomenon occurs because in municipalities that are neighbors of the one that enjoys a wage increase, the average wage tends to decrease. The impact is larger in those municipalities whose average wage is in the lower range of the regional wage distribution. Wage inequality is also increased by internal migration and increased productivity. These latter findings are some of the first for Mexico at this aggregation level. A novel aspect of our study is its use of territory as an observation unit for which statistics from population and economic censuses are combined to draw inferences about spatial inequality
Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies
No full textResearch background: The Russian invasion on Ukraine of February 24, 2022 sharply raised the volatility in commodity and financial markets. This had the adverse effect on the accuracy of volatility forecasts. The scale of negative effects of war was, however, market-specific and some markets exhibited a strong tendency to return to usual levels in a short time.
Purpose of the article: We study the volatility shocks caused by the war. Our focus is on the markets highly exposed to the effects of this conflict: the stock, currency, cryptocurrency, gold, wheat and crude oil markets. We evaluate the forecasting accuracy of volatility models during the first stage of the war and compare the scale of forecast deterioration among the examined markets. Our long-term purpose is to analyze the methods that have the potential to mitigate the effect of forecast deterioration under such circumstances. We concentrate on the methods designed to deal with outliers and periods of extreme volatility, but, so far, have not been investigated empirically under the conditions of war.
Methods: We use the robust methods of estimation and a modified Range-GARCH model which is based on opening, low, high and closing prices. We compare them with the standard maximum likelihood method of the classic GARCH model. Moreover, we employ the MCS (Model Confidence Set) procedure to create the set of superior models.
Findings & value added: Analyzing the market specificity, we identify both some common patterns and substantial differences among the markets, which is the first comparison of this type relating to the ongoing conflict. In particular, we discover the individual nature of the cryptocurrency markets, where the reaction to the outbreak of the war was very limited and the accuracy of forecasts remained at the similar level before and after the beginning of the war. Our long-term contribution are the findings about suitability of methods that have the potential to handle the extreme volatility but have not been examined empirically under the conditions of war. We reveal that the Range-GARCH model compares favorably with the standard volatility models, even when the latter are evaluated in a robust way. It gives valuable implication for the future research connected with military conflicts, showing that in such period gains from using more market information outweigh the benefits of using robust estimators
Impact of European structural and investment funds absorption on the regional development in the EU-12 (new member states)
No full textResearch background: European Structural and Investment Funds (ESIF) as the main instruments of cohesion policy (CP) in the EU, provide a broad source of financing opportunities for the EU member states. The biggest amount in the CP budget is oriented to convergence NUTS 2 regions that have GDP p.c. below 75% of the EU average. The new members of the EU (accessed in 2004 and 2007) had available 176.3 billion EUR in the period 2007?2013 and 217 billion EUR in the period 2014?2020. Even the absorption rate (in 2007?2013) of available ESIFs is high (above 90%), the real implications on their economies don?t come automatically and they represent the area for examination.
Purpose of the article: The research aims to analyse the impact of ESIFs absorption in EU new member states in the period 2008?2016 on their GDP p.c.
Methods: As the sample has time and cross-sectional dimension, the panel data in static and dynamic form is employed. The analysis covers the major part of the financial framework 2007?2013 and a part of financial perspective 2014?2020 (depending on the available data).
Findings & value added: The results indicate that increase in ESIF p.c. for 1% will contribute to the GDP p.c. increase for 0.0053 to 0.0064 % (static model) and for 0.008% (dynamic model). Although the impact of ESIFs is significant and positive, it is quite (and unexpectedly) small, and consequently new EU member states should not rely too much on them as the source of economic progress. It is necessary that countries should focus on channeling funds into specific segments (sectors, policies) that will result in increased competitiveness of their economies. The contributions lie in creating GDP p.c. determination function; in including all new EU member states; in including more recent available data and by observing ESIFs as a part of growth model
Credit cycles and macroprudential policies in emerging market economies
No full textResearch background: Excessive credit expansions have an important role in the generation and amplification of business cycles in emerging market (EM) economies. Macroprudential policies can be beneficial in restraining excessive credit growth and safeguarding financial stability. Despite recent theoretical advances in understanding of the benefits of macroprudential policies, empirical evidence on their effect on the credit cycle is still scarce.
Purpose of the article: This paper studies the effectiveness of macroprudential measures in the sample of major EM economies focusing on the broad credit measure and using an empirical framework which aims to alleviate several concerns in the previous literature. We examine the effectiveness of four categories of measures which are granular enough to provide relevant policy perspectives, whilst mitigating data sparsity issues. By exploiting both time-series and cross-country variation in the tightness of macroprudential regulation in the construction of policy variables we also mitigate some of the common reverse causality concerns.
Methods: We use panel data and employ several (fixed effect, bias corrected LSDV and dynamic interactive fixed effect) estimators to ensure that the results are not sensitive with respect to the estimation method while, together with our construction of the policy variables, alleviating other endogeneity concerns.
Findings & value added: We uncover the heterogeneity in the effects of macroprudential measures on the credit cycle. While measures related to bank capital and credit activity are found to be effective in leaning-against the credit cycle, the measures targeting bank liquidity and FX exposures fail to have statistically significant effect. Our results provide the rationale for mixed evidence in the empirical literature studying the effectiveness of the broadly defined macroprudential measures. From the policy perspective, our findings provide evidence that the measures which address excessive credit expansion and strengthen the resilience of the financial system are effective in the EM economies
Multifrequency-based non-linear approach to analyzing implied volatility transmission across global financial markets
No full textResearch background: The contagious impact of the COVID-19 pandemic has heightened financial market\u27s volatility, nonlinearity, asymmetric and nonstationary dynamics. Hence, the existing relationship among financial assets may have been altered. Moreover, the level of investor risk aversion and market opportunities could also alter in the pandemic. Predictably, investors in the heat of the moment are concerned about minimizing losses. In order to determine the level of hedge risks between implied volatilities in the COVID-19 pandemic through information flow, it is required to take into account the increased vagueness of economic projections as well as the increased uncertainty in asset values as a result of the pandemic.
Purpose of the article: The study aims to examine the transmission of information between the VIX-implied volatility index for S&P 500 and fifteen other implied volatility indices in the COVID-19 pandemic.
Methods: We relied on daily changes in the VIX and fifteen other implied volatility indices from commodities, currencies, and stocks. The study employed the improved complete ensemble empirical mode decomposition with adaptive noise which is in line with the heterogeneous expectations of market participants to denoise the data and extract intrinsic mode functions (IMFs). Subsequently, we clustered the IMFs based on common features into high, low, and medium frequencies. The analysis was carried out using Rényi transfer entropy (RTE), which allowed for the evaluation of both linear and non-linear, as well as varied distributions of the market dynamics.
Findings & value added: Findings from the RTE revealed a bi-directional flow of negative information amid the VIX and each of the volatility indices, particularly in the long term. We found this behavior of the markets to be consistent at varying levels of investors\u27 risk aversion. The findings help investors with their portfolio strategies in the time of the pandemic, which has resulted in fluctuating levels of risk aversion. Our findings characterize global financial markets to be ?non-linear heterogeneous evolutionary systems?. The results also lend support to the emerging delayed volatility of market competitiveness and external shocks hypothesis