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Algorithm bias refers to repetitive computer program errors that give some users more weight than others. The aim of this article is to provide a deeper insight of algorithm bias in AI-enabled ERP software customization. Although algorithmic bias in machine learning models has uneven, unfair and unjust impacts, research on it is mostly anecdotal and scattered.

As guided by the previous research (Akter et al., 2022), this study presents the possible design bias (model, data and method) one may experience with enterprise resource planning (ERP) software customization algorithm. This study then presents the artificial intelligence (AI) version of ERP customization algorithm using k-nearest neighbours algorithm.

This study illustrates the possible bias when the prioritized requirements customization estimation (PRCE) algorithm available in the ERP literature is executed without any AI. Then, the authors present their newly developed AI version of the PRCE algorithm that uses ML techniques. The authors then discuss its adjoining algorithmic bias with an illustration. Further, the authors also draw a roadmap for managing algorithmic bias during ERP customization in practice.

To the best of the authors’ knowledge, no prior research has attempted to understand the algorithmic bias that occurs during the execution of the ERP customization algorithm (with or without AI).

The purpose of this study is to develop a methodology which amalgamates quantitative and qualitative approaches to determine the best placement of mobile logistics hubs (MLH) to be established in different parts of Nepal as a part of real-life project, “Augmentation of National and Local-Level Emergency Logistics Preparedness in Nepal” (2017–2020), implemented by the World Food Programme in cooperation with the Government of Nepal.

The study develops a methodology using a combination of a modified version of the maximal covering location problem (MCLP) and focus group discussion. The MCLP model is used to determine the optimal number and spatial location of MLHs, and focus group discussion is used to identify the five first-priority strategic MLH locations using expert knowledge.

The authors identify the five first-priority locations for establishing MLHs using an amalgamation of quantitative approach (mathematical model) and qualitative approach (focus group discussion). By amalgamating mathematical model with expert knowledge, findings acceptable to a wide range of stakeholders are obtained. The focus group discussion helps to pinpoint the location of MLHs to city-level granularity which is otherwise impossible with data available on hand.

Although multiple experts’ judgements were obtained via focus group discussion, subjectivity and possible bias is inevitable. Overall, the quantitative results of the study are purely based on the data available during the study period; therefore, having updated data could possibly improve the quality of the results.

This study is the first of its kind that uses an amalgamation of mathematical model and expert knowledge to determine the strategic locations of MLHs and has been successful to an extent that the selected locations have been vetted by the government of Nepal for establishing MLHs and are undergoing implementation in real life. This study also considers multiple disaster scenarios and employs the concepts of human development, disaster risk and transportation accessibility to reflect Nepal's socioeconomic, geo-climatic and topographical features.

The paper aims to estimate the factors affecting Vietnam's export in rice and coffee, the two most important agricultural products, especially in exploring the role of “behind-the-border” constraints.

The paper applies the stochastic frontier gravity model, which models the aggregate effect of “behind-the-border” factors for Vietnam's export in rice and coffee.

The paper finds that the impact of “behind-the-border” constraints is statistically significant, suggesting that Vietnam's exports in rice and coffee may be prevented from reaching their export potential by such factors. Moreover, technical efficiency and potential export suggest that Vietnam has a lot of potential to increase its exports in rice and coffee with its major trading partners. The Association of Southeast Asian Nations group continues to be the major market of Vietnamese rice and coffee. Vietnam can also take advantage of the opportunity to export these commodities to the European Union (EU) (not including the UK), and Comprehensive and Progressive Agreement for Trans-Pacific Partnership, especially in coffee to the EU.

The study cannot identify specific “behind-the-border” factors due to the limitation of data availability.

Many existing studies suggest that export in agricultural products of Vietnam, especially in rice, is significantly affected by natural factors and “explicit beyond-the-border” constraints. They ignore the impact of “behind-the-border” constraints in Vietnam and its trading partners. My study proved the significant impact of such constraints. Therefore, Vietnam needs more policies to remove the “behind-the-border” constraints to promote export in rice and coffee.

The purpose of this paper is to analyze a variety of factors that can explain the differences in commercial bank efficiency among 17 countries in Latin America (LatAm).

In a first stage, data envelopment analysis (DEA) and conditional efficiency analysis techniques are used to assess the relative efficiency level of 409 banks for the 2014-2016 period. The conditional efficiency approach considers environmental variables (that are beyond the manager’s control), which could influence the shape and the level of the boundary of the attainable set. In the second stage, the resulting conditional efficiency scores are correlated with internal variables (those that are under the manager’s control), which might affect the distribution of the inefficiencies. For this purpose, an econometric approach developed by Simar and Wilson (2007) is used.

First stage scores reveal the heterogeneity of average efficiency within the region. Regarding the factors that may explain the differences in performance in the LatAm banking sector, the results allow us to state that certain internal variables such as bank size, the ratio of loans to total assets and the ratio of non-performing loans show the expected relationship to efficiency, in line with much of the previous literature.

This is the first time that conditional efficiency and Simar and Wilson (2007) approaches have been applied at the same time to analyse the LatAm banking industry.

Three scenario-based experiments were conducted to explore the influence of the base option’s price format (just-at vs just-below) on tourists’ upgrade intention. The findings of this research indicated that tourists are more inclined to upgrade the option when the base option’s price is presented in a just-at condition due to the mediating role of tourists’ price perceptions of the upgrade option. This study discovered that the just-at (vs just-below) pricing strategy can lower tourists’ price perceptions of the upgrade choice. This research further explored the moderating of tourists’ mindsets. It was found the threshold-crossing effect will disappear for tourists with fixed mindsets. This study also provides practical implications for travel service providers to set up appropriate pricing strategies to attract tourists to make upgrade decisions.

This study aims to analyze to what extent distance education is feasible and efficient with the limited technological infrastructure in Egypt. The study answers this question from the perspective of households' preparedness level regarding possessing information and communication technologies (ICTs). In addition, it assesses whether the pattern of students' ICT ownership is influenced by disability- and socioeconomic-based inequality in education and whether the pattern of ICT ownership exacerbates such biases.

A three-stage probit model with double sample selection (PMDSS) was applied to estimate the factors likely to influence ICT possession, considering the selection process for school enrollment and education continuation. The authors utilized nationally representative data from the Egypt Labor Market Panel Survey 2018.

About 40% of students aged 12–25 did not have ICTs. Most socioeconomically poor households, particularly those living in Upper Egypt, were the least likely to obtain ICTs and rely on distance education. In addition, female students, particularly those with disabilities, had the lowest chance of benefitting from distance learning.

The persistent structural deprivation of school enrollment and educational progression has led to the positive selection of well-off children in education, which is extended to ICT possession and internet use. Without addressing these structural biases, the study suggests that distance education will likely exacerbate educational inequalities.

The study analyzed the extent to which Egyptian families were prepared in 2018 regarding ICT possessions for distance education for their children, particularly those with disabilities. Furthermore, it investigated whether access to distance learning was influenced by disability- and socioeconomic-based inequalities in education.

The purpose of this study is to examine whether and how analysts’ foreign ancestral origins would have an effect on analysts’ earning forecasts in particular and ultimately on firms’ information environment in general.

By inferring analysts’ ancestral countries based on their surnames, this study empirically examines whether analysts’ ancestral countries affect their earnings forecast errors.

Using novel data on analysts’ foreign ancestral origins from more than 110 countries, this study finds that relative to analysts with common American surnames, analysts with common foreign surnames tend to have higher earnings forecast errors. The positive relation between analyst foreign surnames and earnings forecast errors is more likely to be observed for African-American analysts and analysts whose ancestry countries are geographically apart from the USA. In contrast, this study finds that when analysts’ foreign countries of ancestry are aligned with that of the CEOs, analysts exhibit lower earnings forecast errors relative to analysts with common American surnames. More importantly, the results show that firms followed by more analysts with foreign surnames tend to exhibit higher earnings forecast errors.

Taken together, findings of this study are consistent with the conjecture that geographical, social and ethnical proximity between managers and analysts affect firms’ information environment. Therefore, this study contributes to the determinants of analysts’ earnings forecast errors and adds to the literature on firms’ information environment.

This paper aims to explore the drivers behind the accuracy of self-reported home valuations in the Warsaw (Poland) housing market.

In order to achieve the research goal, firstly, unique data on subjective residential property values estimated by their owners were compared with market-justified ones. The latter was calculated using geographically weighted regression, which allowed for taking into account spatially heterogeneous buyers' housing preferences. An ordered logit model was then used to identify the factors influencing the probability of the occurrence of bias towards over or undervaluation.

The results of the study revealed that, on average, homeowners overvalued their properties by only 1.94%, and the fraction of interviewees estimating their properties accurately ranges from 20% to 68%, depending on the size of the margin of error adopted. The drivers of the valuation bias variation were the physical, locational and neighbourhood attributes of the property as well as the personal characteristics of the respondents, for which their age and employment situation played a key role.

In contrast to previous studies, this is the first to examine drivers behind the accuracy of self-reported home valuations in a Central and Eastern Europe country. In addition, this work is the first to consider heterogeneous housing preferences when calculating objective property values.

This study aims to shed light on the relationship between gender diversity and group performance by considering the moderating role of relative cultural distance. Drawing from the categorization–elaboration model (CEM), the authors hypothesize that gender-diverse collaborative learning groups perform better when a low level of relative cultural distance in country-level individualism–collectivism or power distance exists among group members.

To test this hypothesis, the authors conducted a study on 539 undergraduate students organized into 94 groups. The assessment of group performance was based on scores given by external raters.

The authors found that relative cultural distance significantly moderated the gender diversity–group performance relationship such that gender diversity was positively related to group performance when the collaborative learning group included members who similarly valued individualism–collectivism or power distance (i.e. relative cultural distance was low) and was negatively related to group performance when the collaborative learning group comprised members who differently valued individualism–collectivism or power distance (i.e. relative cultural distance was high).

This study contributes to understanding when gender diversity is positively associated with group performance by expanding the range of previously examined diversity dimensions to include relative cultural distance in country-level individualism–collectivism and power distance.

This study aims to examine the multidimensional nature of institutional distance as a driver of acquisition decisions in emerging markets. Then, this study aims to offer a nuanced perspective on the role of its various formal and informal dimensions by taking into account the potential contingency role played by a firm’s context experience.

Building on institutional economics and organizational institutionalism, this study explores the heterogeneity of institutional distance and its effects on the decision to enter emerging versus advanced markets through cross-border acquisitions. Thus, institutional distance is disentangled into its formal and informal dimensions, the former being captured by regulatory efficiency, country governance and financial development. Furthermore, our framework examines the moderating effect of an acquiring firm’s experience in institutionally similar environments, defined as context experience. The hypotheses are analyzed on a sample of 496 cross-border acquisitions by Italian companies in 41 countries from 2008 to 2018.

Findings indicate that at an increasing distance in terms of regulatory efficiency and financial development, acquiring firms are less likely to enter emerging markets, while informal institutional distance is positively associated with such acquisitions. Context experience mitigates the negative effect of formal distance and enhances the positive effect of informal distance.

This study contributes to institutional distance literature in multiple ways. First, by bridging institutional economics and organizational institutionalism and second, by examining the heterogeneity of formal and informal dimensions of distance, this study offers a finer-grained perspective on how institutional distance affects acquisition decisions. Finally, it offers a contingency perspective on the role of context experience.