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This study aims to propose a new method to predict retail store performance using publicly available satellite imagery data and machine learning (ML) algorithms. The goal is to provide manufacturers and other practitioners with a more accurate and objective way to assess potential channel members and mitigate information asymmetry in channel selection and negotiation.

The authors developed an open-source approach using publicly available Google satellite imagery and ML algorithms. A computer vision algorithm was used to count cars in store parking lots, and the data were processed with a CNN. Linear regression and various ML algorithms were used to estimate the relationship between parked cars and sales.

The relationship between parked cars and sales was nonlinear and dependent on the type of channel member. The best model, a Stacked Ensemble, showed that parking lot occupancy could accurately predict channel member performance.

The proposed approach offers manufacturers a low-cost and scalable solution to improve their channel member selection and performance assessment process. Using satellite imagery data can help balance the marketing channel planning process by reducing information asymmetry and providing a more objective way to assess potential partners.

This research is unique in proposing a method based on publicly available satellite imagery data to assess and predict channel member performance instead of forward-looking sales at the firm and industry levels like previous studies.

Using the Canadian Census of 2016, the present study examines the Black and White gap in compensating differentials for their commute to work.

The data are from the Canadian Census of 2016. The standard Mincerian wage regression, augmented by commute-related variables and their confounders, is estimated by OLS. The estimations use sample weights and heteroscedasticity robust standard errors.

In the standard Mincerian wage regressions, Black men are found to earn non-negligibly less than White men. No such gap is found among women. When the Mincerian wage equation is augmented by commute duration and its confounders, commute duration is revealed to positively predict wages of White men and negatively associate with wages of Black men. At the same time, in the specifications including commute duration and its confounders, the coefficient for the dummy variable identifying Black men is positive with a non-negligible size. The latter pattern indicates wage discrepancies among Black men by their commute duration. Again, no difference is found between Black and White women in these estimations.

The main caveat is that due to data limitations, causal estimates could not be produced.

For the Canadian working men, the uncovered patterns indicate both between and within race gaps in the impact of commuting on wages. Particularly, Black men seem to commute longer towards relatively lower paying jobs, while the opposite holds for their White counterparts. However, Black men who reside close to their work earn substantially more than both otherwise identical White men and Black men who live far away from their jobs. The implications for research and policy are discussed.

This is the first paper focused on commute compensating differentials by race using Canadian data.

This study aims to assess the robustness and accuracy of the face-centred finite volume (FCFV) method for the simulation of compressible laminar flows in different regimes, using numerical benchmarks.

The work presents a detailed comparison with reference solutions published in the literature –when available– and numerical results computed using a commercial cell-centred finite volume software.

The FCFV scheme provides first-order accurate approximations of the viscous stress tensor and the heat flux, insensitively to cell distortion or stretching. The strategy demonstrates its efficiency in inviscid and viscous flows, for a wide range of Mach numbers, also in the incompressible limit. In purely inviscid flows, non-oscillatory approximations are obtained in the presence of shock waves. In the incompressible limit, accurate solutions are computed without pressure correction algorithms. The method shows its superior performance for viscous high Mach number flows, achieving physically admissible solutions without carbuncle effect and predictions of quantities of interest with errors below 5%.

The FCFV method accurately evaluates, for a wide range of compressible laminar flows, quantities of engineering interest, such as drag, lift and heat transfer coefficients, on unstructured meshes featuring distorted and highly stretched cells, with an aspect ratio up to ten thousand. The method is suitable to simulate industrial flows on complex geometries, relaxing the requirements on mesh quality introduced by existing finite volume solvers and alleviating the need for time-consuming manual procedures for mesh generation to be performed by specialised technicians.

Income from investment properties can fluctuate depending on the state of the economy. The idea that there is always a potential exit (sale) value whenever the property stops performing at its optimum or deflation in the economy will always appeal to investors. To determine housing prices, investors would rely on a direct comparison approach (DCA) of recent substitute sales in the open market. Appraisers use this approach to develop an opinion of value when there is a plethora of recent sales to analyse.

The study was designed to establish the use of the analytical hierarchy process (AHP) approach as a support tool for deciding property appraisals. A case study of an industrial single-storey stand-alone building with grade-level parking in the south-east of Calgary, Canada, was investigated with the AHP approach. The result was cross-referenced with the DCA.

Using a consistency index of 0.077321 and a consistency ratio of 0.085912, the matrix multiplication was determined to be 0.456706. The average valuations derived from the adjusted price per square foot using the direct comparison method and the unadjusted price per square foot using the AHP were deemed the best value estimate in the light of available comparables. The implications of the findings suggest that AHP, as a quantitative technique, can support and validate the use of similar non-recent sale comparables when appraising investment properties with the DCA.

AHP is an alternative aid in quantitatively deciding the most significant value attribute for comparison before subjective adjustments. When intuitively applied in the DCA, these subjective adjustments almost always lead to an overvaluation of properties.

The goal of this article is two-fold. The first is to contribute new insights to inform education policies for addressing the underlying educational inequalities and injustices that are caused by lack of epistemic access in the context of Fiji higher education. The second is to explore how the Grounded Theory Methodology can be applied to longitudinal language testing research that seeks to reverse epistemic injustices and educational inequalities in Fiji and other comparable multilingual countries.

To explore how the Grounded Theory Methodology can be applied to longitudinal language testing research that seeks to reverse epistemic injustices and educational inequalities in Fiji and other comparable multilingual countries. The study was conducted at a university in Fiji where 120 students were sampled at the beginning of the first year and at the end of their first year of university programme. The same cohort was tracked throughout the project, out of which 30 students were interviewed at the end of the first year.

The four indicators include: (1) lack of teaching and learning resources, (2) language barriers, (3) problems with the medium of instruction and (4) shortage of experienced teachers.

Although widely acknowledged in previous studies from elsewhere, the indicators of educational inequalities identified in this study are worth reporting on due to the unique socio-cultural and linguistic context of Fiji.

This paper examines the ways in which Chinese university middle managers evaluate subordinate performance in response to the Chinese Double First-Class University Plan, a national project that ranks the performance of universities. In exploring compromise arrangements, the hybridised valuing activity of middle managers is found to be shaped by emergent and extant macro-foundations.

The qualitative data from 49 semi-structured interviews at five Chinese public universities were conducted. Drawing on macro-foundational studies and the sociology of worth (SW) theory, the analysis helps to identify socially shared patterns of actions and outcomes.

The findings elucidate the interplay between diverse economic, social, political and institutional values and the compromise-making by middle managers. The authors find that contextual factors restrict Chinese academic middle managers' autonomy, preventing workable compromise. Through the selective adoption of international and local management practices, compromise has evolved into a private differential treaty at the operational level.

A nuanced explanation reveals how the macro-foundations of Chinese society influence middle managers who engage with accounting when facilitating compromise. This study helps outsiders better understand the complex convergence and divergence of performance evaluative practices in Chinese universities against the backdrop of global market-based forces and the moral dimensions of organisational life. The findings have wider implications for the Chinese government in navigating institutional steps and developing supportive policies to enable middle managers to advance productive but also sustainable compromise.

Nicolas Dupont, the owner of Chateau de Montana, a struggling (and old) boutique hotel in Crans-Montana Ski Resort, Switzerland, wished to renovate and reposition his family-owned hotel to target higher room rates. Dupont commissioned Olga Mitireva and Yulia Belopilskaya as consultants to assess the proposition. The consultants had to extract cues for the room rate of the repositioned hotel from comparable hotels. However, the room rates varied significantly across similar hotels due to their differing characteristics and locations. It was a cognitive challenge to read the patterns from a few comparable hotels. They collected the data of 200 hotels from similar locations and simulated room prices using hedonic regression models.

This study aims to investigate the effect of risk tolerance on the individual choice of adopting Bitcoin in the form of making and receiving payment and receiving compensation.

The study uses data collected from an anonymous survey of 225 undergraduate and graduate students to measure their risk attitude using the general risk-taking propensity scale proposed by Zhang et al. (2018) and the risk-taking index, proposed by Nicholson et al. (2018). After controlling for a variety of personal traits, the study uses logistic regression to identify the predicted probabilities and marginal effects on individual choice of adopting Bitcoin.

The findings of this study suggest that individuals with a higher risk-seeking attitude are more likely to choose to receive payment for goods they sell in Bitcoin and more likely to choose to receive a portion of their compensation in cryptocurrency. Individuals in the higher-income groups are more likely to adopt Bitcoin 46% and 65% than their lower 14% and 45% and middle income 4% and 18% counterparts. While there was no statistically significant difference between males and females in adopting Bitcoin, respondents between the age of 26 and 29 were more likely to adopt Bitcoin. The effect on receiving gold was slightly smaller but highly comparable to that of receiving Bitcoin, which highlights a similar perception of risk toward the Bitcoin and gold.

The study uses a new data set collected by surveying 225 individuals and two different risk measurements to identify the relationship between perceived risk and Bitcoin adoption.

The purpose of this paper is to design a simple and accurate a-posteriori Lagrangian-based error estimator is developed for the class of backward differentiation formula (BDF) algorithms with variable time step size, and the adaptive time-stepping in BDF algorithms is demonstrated for efficient time-dependent simulations in fluid flow and heat transfer.

The Lagrange interpolation polynomial is used to predict the time derivative, and then the accurate primary result is obtained by the Gauss integral, which is applied to evaluate the local error. Not only the generalized formula of the proposed error estimator is presented but also the specific expression for the widely applied BDF1/2/3 is illustrated. Two essential executable MATLAB functions to implement the proposed error estimator are appended for practical applications. Then, the adaptive time-stepping is demonstrated based on the newly proposed error estimator for BDF algorithms.

The validation tests show that the newly proposed error estimator is accurate such that the effectivity index is always close to unity for both linear and nonlinear problems, and it avoids under/overestimation of the exact local error. The applications for fluid dynamics and coupled fluid flow and heat transfer problems depict the advantage of adaptive time-stepping based on the proposed error estimator for time-dependent simulations.

In contrast to existing error estimators for BDF algorithms, the present work is more accurate for the local error estimation, and it can be readily extended to practical applications in engineering with a few changes to existing codes, contributing to efficient time-dependent simulations in fluid flow and heat transfer.

This paper aims to examine sites of dissonance or consensus between global investor responses to the draft standards, International Financial Reporting Standards S1 (IFRS) (General Requirements for Disclosure of Sustainability-related Financial Information) and IFRS S2 (Climate-related Disclosures), issued by the International Sustainability Standards Board (ISSB).

A thematic content analysis was used to capture investor views expressed in their comment letters submitted in the consultation period (March to July 2022) in comparison to the ex ante position (issue of draft standards, March 2022) and ex post summary feedback (ISSB staff papers, September 2022) of the ISSB.

There was investor consensus in support of the ISSB and the development of the draft standards. However, there were sites of dissonance between investors and the ISSB, notably regarding the basis and focus of reporting (double or single/financial materiality and enterprise value); definitional clarity; emissions reporting; and assurance. Incrementally, the research further highlights that investors display heterogeneity of opinion.

The ISSB standards will provide a framework for future sustainability reporting. This research highlights the significance of such reporting to investors through their responses to the draft standards. The findings reveal sites of dissonance in the development and alignment of draft standards to user needs. The views of investors, as primary users, should help inform the development of sustainability-related standards by a global standard-setting body apposite to current policy and future reporting requirements, and their usefulness to users in practice.

To the best of the authors’ knowledge, this paper makes an original contribution to the comment letter literature, hitherto focused on financial reporting with a relative lack of investor engagement. Using thematic analysis, sites of dissonance are examined between the views of investors and the ISSB on their development of sustainability reporting standards.