Search results

This paper aims to empirically investigate the sources of real exchange rate fluctuations in Egypt using structural vector autoregression (SVAR). The data covers the period between 1980 and 2016, where exchange regime has been changed more than once.

This paper investigates the source of real exchange rate fluctuations for the period between 1980 and 2016 using the SVAR method. The SVAR method will incorporate real gross domestic product (GDP), real effective exchange rate (REER) and price level in a multidimensional equations system. However, impulse response function (IRF) and error variance decompositions (EVDC) will be generated by the system to have a behavioral insight of real exchange rate in response to economic shocks.

The IRF and EVDC results indicate a significant impact of demand shocks over the real exchange rate relative to supply shocks and monetary shocks in the period between 1980 and 2016. On the other hand, monetary shocks will have a negligible effect on the real exchange rate in the short run and converging to its previous level in the covering period of the study.

In the best of the authors' knowledge, the topic of the source of the real exchange rate fluctuations in Egypt has not been discussed in a wide range due to the lack of time series data. However, this study provides constructed data for REER for Egypt with the published method in the International Monetary Fund (IMF). Furthermore, the study involves theoretical and econometric modeling to ensure the reliability of the economic results.

With access to the large-scale search data from Rightmove plc, the paper firstly indicated the possibility of using user-generated data from online property portals to predict housing market activities and secondly embraced a GIS approach to explore what people search for housing and what they chose and investigated the issue of mismatch between search patterns and revealed patterns. Based on the analysis, the paper contributes a visual GIS-based approach which may help planners and designers to make more informed decisions related to new housing supply, particularly where to build, what to build and how many to build.

The paper used the 2013 housing search data from Rightmove and the 2013 price data from Land Registry with transactions made after the search period and embraced a GIS approach to explore the potential housing demand patterns and the mismatch between searches and sales. In the analysis, the paper employed the K-means approach to group prices into five levels and used GIS software to draw maps based on these price levels. The paper also employed a simple analysis of linear regression based on the coefficient of determination to investigate the relationship between online property views and values of house sales.

The result indicated the strong relationship between online property views and the values of house sales, implying the possibility of using search data from online property portals to predict housing market activities. It then explore the spatial housing demand patterns based on searches and showed a mismatch between the spatial patterns of housing search and actual moves across submarkets. The findings may not be very surprising but the main objective of the paper is to open up a potentially useful methodological approach which could be extended in future research.

It is important to identify search patterns from people who search with the intention to buy houses and from people who search with no intention to purchase properties. Rightmove data do not adequately represent housing search activity, and therefore more attention should be paid to this issue. The analysis of housing search helps us have a better understanding of households' preferences to better estimate housing demand and develop search-based prediction models. It also helps us identify spatial and structural submarkets and examine the mismatches between current housing stock and housing demand in submarkets.

The GIS approach in this paper may help planners and designers better allocate land resources for new housing supply based on households' spatial and structural preferences by identifying high and low demand areas with high searches relative to low housing stocks. Furthermore, the analysis of housing search patterns helps identify areas with latent demand, and when combined with the analysis of transaction patterns, it is possible to realise the areas with a lack of housing supply relative to excess demand or a lack of latent demand relative to the housing stock.

The paper proves the usefulness of a GIS approach to investigate households' preferences and aspirations through search data from online property portals. The contribution of the paper is the visual GIS-based approach, and based on this approach the paper fills the international knowledge gap in exploring effective approaches to analysing user-generated search data and market outcome data in combination.

This study investigates the impact of the increasing proportion of older workers in the workforce by establishing a theoretical framework and estimating the degree of substitutability between them and their younger counterparts.

The first step is to establish a theoretical framework that combines older and younger workers with imperfect substitutability in the production of final goods within an aggregate production function. The author then derives an equation that relates the relative wage, relative supply and elasticity of substitution between the worker types, for use in estimation. Using data from Japan’s Basic Survey on Wage Structure and Population Census from 2010 to 2019 across 47 prefectures, the author estimates the elasticity of substitution between older and younger workers in Japan.

The author finds that workers aged 55 and over and their younger counterparts are gross substitutes, and the estimated elasticity of substitution is in the range of 2.33–2.86. This implies that a 10% increase in the relative number of workers aged 55 and older leads to a fall in their relative wage in the range of 3.5–4.3%. The study estimations suggest that since 2010, there has been a convergence in the relative wage of older workers across Japan’s prefectures.

Understanding the degree of substitutability between older and younger workers is essential for quantitatively assessing the impact of workforce aging, technological advancements and labor policies on the wage distribution. This study estimates the elasticity of substitution between the two worker types based on a theoretical model, and utilizes recent datasets and methodology not adequately addressed in previous literature.

Drawing on paradox theory and the category of the “performing-organizing” paradox, the study investigates the tensions firms experience in the context of organizing the processes involved in managing their indirect GHG emissions.

The authors develop hypotheses to explain why the paradox elements of supply chain transparency and supply chain coordination affect firms' ability to reduce their indirect supply chains GHG emissions. Using a two-stage method based on data from Refinitiv and CDP for 2002 to 2021, the authors test this study’s hypotheses through panel regression analyses.

While greater transparency experience with scope 3 emissions disclosure, GSCM practices and broader supply chain engagement are all associated with higher levels of scope 3 emissions levels, both long-term transparency experience and GSCM practices are also associated with relative reductions in scope 3 emissions over time.

Given growing pressures on firms to demonstrate both transparency and legitimacy regarding their scope 3 emissions, firms must understand the characteristics of this paradox as this has implications for how emissions performance is perceived and managed. This study's results suggested that firms need to take both a long-term perspective and effectively communicate the differences involved in reporting their emissions performance to avoid unwarranted criticism.

Filling a gap in sustainable OSCM studies by providing large-scale quantitative insights into the relationships between organizing and performing, the authors demonstrate that the processes involved in firms' efforts of measuring and managing their indirect scope 3 emissions are paradoxically affected by whether performance outcomes are specified as annual absolute levels of scope 3 emissions, or relative changes over time.

In the aftermath of disasters, humanitarian actors need to coordinate their activities based on accurate information about the disaster site, its surrounding environment, the victims and survivors and the supply of and demand for relief supplies. In this study, the authors examine the characteristics of radio frequency identification (RFID) technology and those of disaster relief operations to achieve information visibility and actor coordination for effective and efficient humanitarian relief operations.

Building on the contingent resource-based view (CRBV), the authors present a model of task-technology fit (TTF) that explains how the use of RFID can improve visibility and coordination. Survey data were collected from humanitarian practitioners in India, and partial least squares (PLS) analysis was used to analyze the model.

The characteristics of both RFID technology and disaster relief operations significantly influence TTF, and TTF predicts RFID usage in disaster relief operations, providing visibility and coordination. TTF is also a mediator between the characteristics of RFID technology and disaster relief operations and between visibility and coordination.

The many recent humanitarian disasters have demonstrated the critical importance of effective and efficient humanitarian supply chain and logistics strategies and operations in assisting disaster-affected populations. The active and appropriate use of technology, including RFID, can help make disaster response more effective and efficient.

Humanitarian actors value RFID technology because of its ability to improve the visibility and coordination of relief operations. This study brings a new perspective to the benefits of RFID technology and sheds light on its antecedents. The study thus expands the understanding of technology in humanitarian operations.

Integrating demand with supply has always been an evolving research area, which is affected by different factors including, but not limited to, sustainability, changing consumer demands and emerging supply chain practices. However, most of the research targeted developed countries due to better data access and enhanced information visibility. The research on supply and demand integration in Saudi Arabia is still in its infancy. This study explores this gap by providing a comprehensive analysis of demand and supply chain integration in the context of sustainability. This is done by first creating a developing countries-based research framework and then validating it through surveying 162 Saudi companies operating in multiple sectors like food, fashion and retail. Results suggest that there is more emphasis on supply-side factors relative to demand-side factors in the context of integration. Demand side factors only marginally impact waste reduction efforts. Similarly, the food sector is most sensitive to integration efforts attaching high importance to sustainability and efficiency initiatives. These results can be a useful guide for managers and policymakers who are planning and executing at the interface of demand and supply chains in developing countries.

Cross-sector analysis by survey questionnaire of 162. Descriptive statistical analyses were performed on the data for the study participants. Continuous variables were summarised using mean and standard deviation (SD), median and IQR; and proportions were used for nominal and ordinal variables. A total score measuring perception of employees towards supply–demand integration was analysed and compared by company-related factors (sector/industry, length of service in firm (years) and the number of employees). Comparisons were made using the chi-square test or ANOVA. A linear regression model was utilised to examine the independent effect of supply and demand side factors on employees' perception of integration. The model controlled for the sector, length of service and number of employees. Statistical significance was considered at p < 0.05.

The linear regression results showed that supply items significantly predicted integration. That is, higher supply–demand integration scores were significantly related to indicators for using supply variables in supply chain management (SCM) improves operational efficiency (OE), integrating supply variables at the execution stage reduces overall waste and including at least one supply-side variable in supply planning (p < 0.05). The indicator for integrating demand variables at the execution stage reduces overall waste was only marginally related to an increased integration scores (p = 0.089). Lastly, a significantly better perception of supply–demand integration was reported by employees in the food sector compared to those in the fashion sector (p = 0.018). Length of service or number of employees in the firm was not related to perception towards supply–demand integration.

Though accessing 162 companies in the Saudi market is a significant sample size given the fact that they are quite conservative in sharing supply and demand information. However, for better generalisation and richer insights, more sectors like manufacturing, oil and gas and hospitality should be added in future. Cross-country analysis from developing countries can be another interesting future direction.

This empirical paper draws its strength from the scale and depth of empirical data collected from Saudi companies belonging to multiple sectors to better understand demand and supply chain integration, especially from sustainability and waste reduction. This is true in the era of the pandemic and its associated risks for both upstream and downstream. The developing countries' perspective is important as not enough is written in the literature given the difficulties in accessing the information and subsequent analysis. The insights are bound to be unique as a consumer in these countries is undergoing significant socioeconomic changes affecting the supply chain of the companies.

The purpose of this study is to examine how US farm sector performed in 2020, the first year of the pandemic. There were significant supply and demand shocks due to the pandemic. Furthermore, there was significant fluctuation in commodity prices and record high government payments in 2020. This study aims to examine the performance and position of US farm sector (financially) to system (and global economy) wide shocks.

The authors examine 2020 values for farm sector financial ratios before and after the onset of the Coronavirus (COVID-19) pandemic using the data from the United States Department of Agriculture to understand the financial position and performance of the US farm sector.

The authors find solvency ratios (which are indicators of the sector's ability to repay financial liabilities via the sale of assets) worsened in 2020 relative to pre-pandemic expectations. Efficiency ratios (which evaluate the conversion of assets into production and revenue) and liquidity ratios (which are indicators of the availability of cash to cover debt payments) showed mixed outcomes for the realized results in 2020 relative to the pre-pandemic forecasts. Four profitability ratios were stronger in 2020 relative to pre-pandemic expectations. All solvency, liquidity and profitability ratios plus 2 out of 5 efficiency ratios for 2020 were weaker than their respective average ratios obtained from 2000 to 2019 data.

This research is one of the first papers to use financial ratios to examine how the US farm sector performed in 2020 compared to expectations prior to the pandemic.

This study aims to examine the impact of some real variables such as real effective exchange rates, real mortgage rates, real money supply, real construction cost index and housing sales on the real housing prices.

This study uses a nonlinear autoregressive distributed lag (NARDL) model in the monthly period of 2010:1–2021:10.

The real effective exchange rate has a positive and symmetric effect. The decreasing effect of negative changes in real money supply on real housing prices is higher than the increasing effect of positive changes. Only positive changes in the real construction cost index have an increasing and statistically significant effect on real house prices, while only negative changes in housing sales have a small negative sign and a small increasing effect on housing prices. The fact that the positive and negative changes in real mortgage rates are negative and positive, respectively, indicates that both have a reducing effect on real housing prices.

This study suggests the first NARDL model that investigates the asymmetric effects on real housing prices instead of nominal housing prices for Turkey. In addition, the study is the first, to the best of the authors’ knowledge, to examine the effects of the five real variables on real housing prices.

The novel COVID-19 supply chain disruption has globally altered the environmental needs of society. Against this backdrop, this paper aims to examine how top managers are environmentally committed to integrating green supply chain management (GSCM) practices in the operational performance of small- and medium-scale enterprises (SMEs) in Ghana, within the post-pandemic economy.

The study used a cross-sectional survey to obtain data from 270 SMEs in Ghana, using partial least squares (PLS) structural equation modelling to test seven hypothesized relationships.

The outcome of the analysis revealed that top management environmental commitment has a significantly positive effect on supply chain operational performance. The structural model also revealed that top management environmental commitment has a positive and significant effect on both internal and external GSCM practices. The results further revealed that both internal and external GSCM practices have positive and significant effects on supply chain operational performance. Finally, both internal and external GSCM practices mediate the path between top management environmental commitment and supply chain operational performance.

The study provides a novel framework which contributes to both theoretical studies and managerial decisions on COVID-19 related supply chain management issues. However, the study was limited to the Ghanaian context, thus, further related studies are required in other contexts.

This study provides a novel framework by elucidating the intervening role of GSCM practices in the path between top management environmental commitment and supply chain operations in an emerging post-pandemic world context.

The authors' work aims to identify the employer-specific drivers of the college (or university) wage gap, which has been identified as one of the major determinants of the dynamics of overall wage and income inequality in the past decades. The authors focus on three employer-level features that can be associated with asymmetries in the employment relation orientation adopted for college and non-college-educated employees: (1) size, (2) the share of standard employment and (3) the pervasiveness of incentive pay schemes.

The authors' establishment-level analysis (data from the Basic Survey on Wage Structure (BSWS), 2005–2018) focusses on Japan, an economy characterised by many unique economic and institutional features relevant to the aims of the authors' analysis. The authors use an adjusted measure of firm-specific college wage premium, which is not biased by confounding individual and establishment-level factors and reflects unobservable characteristics of employees that determine the payment of a premium. The authors' empirical methods account for the complexity of the relationships they investigate, and the authors test their baseline outcomes with econometric approaches (propensity score methods) able to address crucial identification issues related to endogeneity and reverse causality.

The authors' findings indicate that larger establishment size, a larger share of regular workers and more pervasive implementation of IPSs for college workers tend to increase the college wage gap once all observable workers, job and establishment characteristics are controlled for. This evidence corroborates the authors' hypotheses that a larger establishment size, a higher share of regular workers and a more developed set-up of performance pay schemes for college workers are associated with a better capacity of employers to attract and keep highly educated employees with unobservable characteristics that justify a wage premium above average market levels. The authors provide empirical evidence on how three relevant establishment-level characteristics shape the heterogeneity of the (adjusted) college wage observed across organisations.

The authors' contribution to the existing knowledge is threefold. First, the authors combine the economics and management/organisation literature to develop new insights that underpin the authors' testable empirical hypotheses. This enables the authors to shed light on employer-level drivers of wage differentials (size, workforce composition, implementation of performance-pay schemes) related to many structural, institutional and strategic dimensions. The second contribution lies in the authors' measure of the “adjusted” college wage gap, which is calculated on the component of individual wages that differs between observationally identical workers in the same establishment. As such, the metric captures unobservable workers' characteristics that can generate a wage premium/penalty. Third, the authors provide empirical evidence on how three relevant establishment-level characteristics shape the heterogeneity of the (adjusted) college wage observed across organisations.