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This study examines the relationship between demand forecasting error and retail inventory management in an uncertain supplier yield context. Replenishment is segmented into off-season and peak-season, with the former characterized by longer lead times and higher supply uncertainty. In contrast, the latter incurs higher acquisition costs but ensures certain supply, with the retailer's purchase volume aligning with the acquired volume. Retailers can replenish in both phases, receiving goods before the sales season. This paper focuses on the impact of the retailer's demand forecasting bias on their sales period profits for both phases.

This study adopts a data-driven research approach by drawing inspiration from real data provided by a cooperating enterprise to address research problems. Mathematical modeling is employed to solve the problems, and the resulting optimal strategies are tested and validated in real-world scenarios. Furthermore, the applicability of the optimal strategies is enhanced by incorporating numerical simulations under other general distributions.

The study's findings reveal that a greater disparity between predicted and actual demand distributions can significantly reduce the profits that a retailer-supplier system can earn, with the optimal purchase volume also being affected. Moreover, the paper shows that the mean of the forecasting error has a more substantial impact on system revenue than the variance of the forecasting error. Specifically, the larger the absolute difference between the predicted and actual means, the lower the system revenue. As a result, managers should focus on improving the quality of demand forecasting, especially the accuracy of mean forecasting, when making replenishment decisions.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

This study analyzes the static and dynamic risk spillover between US/Chinese stock markets, cryptocurrencies and gold using daily data from August 24, 2018, to January 29, 2021. This study provides practical policy implications for investors and portfolio managers.

The authors use the Diebold and Yilmaz (2012) spillover indices based on the forecast error variance decomposition from vector autoregression framework. This approach allows the authors to examine both return and volatility spillover before and after the COVID-19 pandemic crisis. First, the authors used a static analysis to calculate the return and volatility spillover indices. Second, the authors make a dynamic analysis based on the 30-day moving window spillover index estimation.

Generally, results show evidence of significant spillovers between markets, particularly during the COVID-19 pandemic. In addition, cryptocurrencies and gold markets are net receivers of risk. This study provides also practical policy implications for investors and portfolio managers. The reached findings suggest that the mix of Bitcoin (or Ethereum), gold and equities could offer diversification opportunities for US and Chinese investors. Gold, Bitcoin and Ethereum can be considered as safe havens or as hedging instruments during the COVID-19 crisis. In contrast, Stablecoins (Tether and TrueUSD) do not offer hedging opportunities for US and Chinese investors.

The paper's empirical contribution lies in examining both return and volatility spillover between the US and Chinese stock market indices, gold and cryptocurrencies before and after the COVID-19 pandemic crisis. This contribution goes a long way in helping investors to identify optimal diversification and hedging strategies during a crisis.

This paper aims to obtain accurate forecasts of the hourly residential natural gas consumption, in Egypt, taken into consideration the volatile multiple seasonal nature of the gas series. This matter helps in both minimizing the cost of energy and maintaining the reliability of the Egyptian power system as well.

Double seasonal autoregressive integrated moving average-generalized autoregressive conditional heteroskedasticity model is used to obtain accurate forecasts of the hourly Egyptian gas consumption series. This model captures both daily and weekly seasonal patterns apparent in the series as well as the volatility of the series.

Using the mean absolute percentage error to check the forecasting accuracy of the model, it is proved that the produced outcomes are accurate. Therefore, the proposed model could be recommended for forecasting the Egyptian natural gas consumption.

The contribution of this research lies in the ingenuity of using time series models that accommodate both daily and weekly seasonal patterns, which have not been taken into consideration before, in addition to the series volatility to forecast hourly consumption of natural gas in Egypt.

The purpose of this study is to investigate the role of natural resources in economic growth by taking evidence from Pakistan.

Total five variables are used in this study, i.e. GDP, population density, water renewable resources, deforestation and the emissions of CO₂, based on time series data from 1972 to 2016. The annual data is collected from World Development Indicators, Food and Agriculture Organization and Pakistan Economic Survey. Vector error correction model technique is applied to find out the long-run results.

Results depict that all variables have a negative and significant relationship over the long run at 5% level of significance. It is observed that 1% increase in population accordingly will degrade GDP by 0.334496%. Correspondingly, 1% increase of water renewable resources will degrade GDP by 0.450647%. Findings are aligning with the study of. Moreover, 1% increase in deforestation will diminish GDP by 0.127821%. If we increase 1% of CO₂, GDP will be reduced by 0.802420%.

Results depict that all variables have a negative and significant relationship over the long run at 5% level of significance. It is observed that 1% increase in population accordingly will degrade GDP by 0.334496%. Correspondingly, 1% increase of water renewable resources will degrade GDP by 0.450647%. Findings are aligning with the study of. Moreover, 1% increase in deforestation will diminish GDP by 0.127821%. If we increase 1% of CO₂, GDP will be reduced by 0.802420%.

Family planning may be our last hope. Viable and fruitful family planning ought to be introduced. Status of ladies should be brought up in the society by providing education and employment opportunities. Time of marriage ought to be brought up to 25 years in case of males and 23 in case of females; this can help in decreasing the number of births. Having a large population will not automatically translate into economic prosperity. Investment in well-being, education, sound economic policies and good governance will bring about accelerated economic growth.

In recent years, the issue of worldwide water shortage has attracted increasing consideration within scholarly community, non-administrative organizations and the media. Water shortage is a significant and ever-increasing danger to the environment, human well-being, advancement, energy security and the worldwide food supply. This work will introduce real issues and requirements relating to water, environmental changes and their impact on economic growth of Pakistan.

This study aims to prove the complexity of the relationship between CSR and financial performance (FP) and to decompose the complexity of the relationship using neo-institutional theory.

This research employs a meta-analysis that integrates 55 various contexts studied between 1998 and 2017 using correlation coefficient as the effect size.

This study proves that the nature of the relationship between CSR and FP is complex and suggests that the analysis of the relationship between the two variables includes institutional factors to produce generalizable conclusions. Country characteristics, forms and dimensions of CSR, CSR measurements and FP measurements explain the complexity of the relationship between CSR and FP.

Future research is expected to include industry characteristics and the corporate governance model in the analysis of the relationship between CSR and FP. Differences in industry characteristics affect the selection of CSR forms and dimensions, bringing it the potential to influence the relationship between CSR and FP. The corporate governance model adopted by developing countries and developed countries also has the potential to be an institutional factor to influence the relationship between CSR and FP.

This research proves that the complexity of the relationship between CSR and FP is nature given. This research explores the factors causing the complexity of the relationship using neo-institutional theory, which, to the author's knowledge, has not been done by other researchers.

This paper aims to identify what are the moderating factors affecting the relationship between firms’ adoption of international financial and reporting standards (IFRS) and the firm’s opacity.

This study uses the meta-analysis methodology from Hunter et al. (1982) to find if the mere IFRS adoption reduces firm’s opacity and a meta-regression from Stanley and Jarrell (1989) to identify the moderating factors that may influence this relationship.

Contrary to previous studies, this study finds a low, negative and nonsignificant correlation between IFRS adoption and firms’ opacity, but this relationship depends on the geographical region. Using 34 results from 28 studies from different continents published between 2005 and 2018 this study finds that IFRS adoption reduces opacity in countries with common law (COML) and with more authorities’ oversight and power to enforce the rules.

This study finds two institutional commonalities between different previous studies that intend to assess the impact of the IFRS adoption upon firms’ opacity: the legal system and the authorities’ oversight power.

This study examined the roles of public spending and population moderating characteristic structure of selected African economies on bank-based financial development through credit to private sector.

The study sampled 37 selected African economies for the years 1991–2018, and it applied a pooled mean group (PMG) estimator to account for short-run and long-run causal effects, and confirmed short-run adjustments towards the long-run convergences between the variables. Specific suitable tests were also applied.

Evidence confirms positive impacts of both capital formation and final consumption expenditures on financial development in the short run and long run. The moderation of population structures on expenditure structures help to speed up convergences.

This work attests its innovation by accounting for the separate effects of the expenditure types, the moderation effects of young and mature populations for capital and final consumption expenditure on financial development among selected economies in Africa.

The purpose of this paper is to understand the relation between the dimensions of employer brand (EB) attractiveness and the intention to submit a job application to the organisation. An increase of competitiveness in the business world has resulted in an increased effort by organisations to improve the processes of recruitment and retention of talented professionals, as the human capital of organisations is extremely important for their growth and sustainability. Regardless of an organisation’s size, the difficulties faced in recruiting and retaining highly qualified human capital are tangible. In this sense, the research problem identifies EB as being a strategic element for attracting future employees to work for an organisation.

This study used both quantitative (a questionnaire survey) and qualitative (in-depth interviews) data to investigate the perceptions of future and current employees.

Evidence from 281 respondents (of which almost 60 per cent belong to the millennial generation) who participated in the quantitative study supports the multi-dimensionality of EB attractiveness, highlighting the importance of economic factors, such as an above-average salary or opportunities for promotion, which are seen to be less important to millennials when considering future job prospects. Interestingly, the results of the qualitative research for current employees show slightly different concerns, in that career progression appears to be crucial.

The study findings not only offer a basis for research on the dimensions of employer attractiveness, but also, they serve as a managerial guide towards enhancing companies’ ability to attract, retain and motivate talented individuals.

Psychometric analyses of self-administered questionnaire data tend to focus on items and instruments as a whole. The purpose of this paper is to investigate the functioning of the response scale and its impact on measurement precision. In terms of the response scale direction, existing evidence is mixed and inconclusive.

Three experiments are conducted to examine the functioning of response scales of different direction, ranging from agree to disagree versus from disagree to agree. The response scale direction effect is exemplified by two different latent constructs by applying the Rasch model for measurement.

The agree-to-disagree format generally performs better than the disagree-to-agree variant with spatial proximity between the statement and the agree-pole of the scale appearing to drive the effect. The difference is essentially related to the unit of measurement.

A careful investigation of the functioning of the response scale should be part of every psychometric assessment. The framework of Rasch measurement theory offers unique opportunities in this regard.

Besides content, validity and reliability, academics and practitioners utilising published measurement instruments are advised to consider any evidence on the response scale functioning that is available.

The study exemplifies the application of the Rasch model to assess measurement precision as a function of the design of the response scale. The methodology raises the awareness for the unit of measurement, which typically remains hidden.