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The purpose of this paper is to discuss the application of a method for combining multiple criteria based on the transformation of numerical evaluations into probabilities of preference. It is applied to compare failure risks and to measure efficiency in the retail trade sector.

The main conceptual aspect of the method employed is taking into account uncertainty. Its other important feature is allowing for the combination of evaluations in terms of joint probabilities. This avoids the need of assigning weights to the criteria. In the context of failure modes and effects analysis (FMEA) it provides a probabilistic derivation for priority scores. An application of FMEA to the sector of services is discussed. Another area of application investigated is the assessment of efficiency.

Details of the application of the probabilistic composition in the evaluation of modes of failure and in the comparison of operational efficiencies of retail stores are evidenced.

The study is limited to the retail market. Other factors might be considered in the reliability analysis and other inputs and outputs might be added to the productivity evaluation. The extension of the study to other cases and sectors is straightforward.

Features of the evaluation of modes of failure and of productivity in the retail sector are revealed.

The main contribution of this paper is showing how to use a probabilistic framework to measure efficiency in services management.

Data mining registers of transactions allows for benchmarking customer's evaluation strategies. The purpose of this paper is to provide information on the application of different approaches to explore this kind of data.

Traditionally, heuristics based on variables such as recency, frequency, and monetary (RFM) value of transactions are used to determine the best customers. In this paper, a new form of directly combining the values of these variables is compared to an approach based on fitting a stochastic model. This last model is a mixture of a model for the number of transactions and another for the value spent. The new direct form of evaluation is based on computing the joint probability of maximizing quality indicators.

Good fit of the different models tested to the series of individual data as well as coherent predictions are registered. Patterns found provide empirical confirmation of results that theoretically should be expected.

These results are valid for a particular supermarkets network in a Brazilian city. The inner consistency of the results, nevertheless, and the coherence of the results obtained with what was expected, encourage application to other places and sectors of activity.

The results obtained show clearly the effectiveness of the approach based on RFM value measurement.

The models studied are applied for the first time for the kind of data treated, where determination of which customers remain active is a problem of special interest.

A growing body of research finds a consistently negative relationship between medical cannabis access and aggregate measures of opioid use. Nothing is currently known about the types of opioids that are being most impacted by cannabis access. Using the Callaway and Sant’Anna (2021) difference-in-differences (DID) estimator for the main analysis and data on all opioid shipments to every United States (US) pharmacy from 2006 to 2014, the authors found no evidence of overall change in the total number of morphine milligram equivalent (MME) units of opioids shipped to pharmacies, following the opening of medical cannabis dispensaries. However, across all opioids, the authors found a reduction in the highest MME dosage strengths (8.8% decrease in 50–89 MME doses and 11.3% decrease in 90+ MME doses). This decrease appears to be driven predominantly by commonly diverted opioids, where the authors found a reduction in the highest MME dosage strengths (12.2% in 50–89 MME doses and 13.8% in 90+ MME doses). Further, the authors see a 6.0% increase in low-to-moderate dose opioids (0–49 MMEs). This is consistent with patients using cannabis concomitantly with opioids in order to achieve a lower opioids dose.

The paper aims to propose a multi-criteria model for risk prioritisation associated to supply chain management involving multiple decision-makers.

The model integrates the composition of probabilistic preferences (CPP) on the failure modes analysis and its effects (FMEA) criteria. First, the authors carried out a probabilistic transformation of the numerical evaluations of the multiple decision-makers on the FMEA criteria regarding the internal risks that affect the chain of clothing pole in the Agreste region of Pernambuco. Then, the authors proposed the use of the Kendall's concordance coefficient W to aggregate these evaluations.

Contrary to expectations, the two main risks to be investigated as a model suggestion was related to the context of supply chain suppliers and not related to the raw material costs. Besides, a simulation with the traditional FMEA was carried out, and comparing with the model result, the simulation is worth highlighting seven consistent differences along the two rankings.

The focus was restricted to the use of only internal chain risks.

The proposed model can contribute to the improvement of the decisions within organisations that make up the chains, thus guaranteeing a better quality in risk management.

Establishing a more effective representation of uncertain information related to traditional FMEA treatment involving multiple decision-makers means identifying in advance the potential risks, providing a better supply chain control.

The financial crisis has been something of a turning point in the regulatory response to financial crime around the world. The failure of light‐handed regulation and risk assessment by both industry and regulators made the operation of financial regulatory agencies almost untenable, often leading to calls for their replacement by more effective agencies. The purpose of this paper is to assess the nature of this regulatory challenge.

The paper discusses some of the case studies that have emerged from the dark side of regulatory and enforcement policies in recent times.

A culture of minimal regulation of financial markets meant that many undesirable practices (such as insider trading, foreign corrupt practices, tax avoidance, money laundering and other frauds) were able to avoid detection until public outrage led to regulatory and prosecutorial agencies being prompted into action following the collapse of financial markets.

More detailed studies of particular institutions will be necessary; this will become possible as the current financial crisis subsides.

This paper explores some of the factors behind this state of affairs and makes policy recommendation in regard to the need for more effective internal controls and monitoring measures within the modern financial corporation.

Several sources have reported an increase in the opposition to the fifth-generation (5G) amongst local communities following the outbreak of Covid-19. In Italy, more than 300 municipalities banned 5G rollout from their territory between April and June 2020. Researchers have described this phenomenon as resulting from the infodemic caused by the pandemic, however, local protests also accompanied the rollout of the previous generation of mobile communications. This paper uses document analysis to explore the local debate on 5G municipal bans and map their evolution in an Italian region. This study aims to unravel the complexity of this phenomenon and inform future research on the actors and factors underlying the opposition of local communities towards 5G.

The analysis focusses on Marche, a region in Italy where, by July 2020, 25% of the municipalities had banned 5G rollout. This analysis is based on secondary data, retrieved from multiple online sources (articles from the local press, public statements and press releases, minutes from local council meetings and resolutions from local councils).

The analysis revealed that concerns on the safety of electromagnetic fields predated the pandemic, although these concerns may have increased the sensitivity of local communities towards health issues. The local debates on 5G involved many actors from the civil society, including environmentalists that had long campaigned against wireless technologies and local politicians playing a proactive role in leading and coordinating the adoption of resolutions against 5G.

This paper addresses an emerging phenomenon, such as municipal bans against 5G, that has not yet been explored in academic literature. Researchers have recently investigated the propagation of conspiracy theories on 5G on social media, but little has been said on the factors and actors shaping the debate on 5G within local communities.

This study aims to develop a risk prioritization process using failure mode and effect analysis (FMEA) in association with composition of probabilistic preferences (CPP) and weighting the risk analysis criteria. It seeks to develop decision-making considering the fast response necessary to achieve project objectives in complex scenarios, such as the pandemic of COrona VIrus Disease 19 (COVID-19).

After identifying the risks, the prioritization process was applied to a project in the oil and gas area, in which a focus group assessed these risks. This evaluation took place employing traditional FMEA, FMEA with CPP by axes considering four points of view and FMEA with CPP by weighted sum with the use of a multicriteria method to weight the criteria. These approaches were compared to understand their differences and benefits, with a flow chart being developed, consolidating the procedure.

The methodologies that showed the greatest benefits were FMEA with CPP by axes PO (progressive-optimistic) and by weighted sum. Essentially, this was mainly related to the interrelationship between risks and to the importance of prioritization.

This procedure can consider company's views on what is critical and the interrelationship between risks. It provides a clear segmentation of what should and should not be prioritized. It was also developed in a practical case, showing a possible alternative to support fast responses in decision-making.

This paper aims to examine the impact of the mandatory adoption of (International Financial Reporting Standards [IFRS] 9) on loan provisions, nonperforming loans (NPL) and impairment loan loss in Gulf banks. This study also investigates potential variations in outcomes compared to prior models and explores the use of the Callaway and Sant’Anna (2021) estimator for difference-in-differences (DiD) with multiple time periods.

The research is based on a sample of 53 Gulf banks covering the period from 2012 to 2020. The study analyzes the changes in loan provisions, impairment loss and NPL following the implementation of IFRS 9. It uses statistical analysis and the DiD method to compare the outcomes between the experimental group (treated by IFRS 9) and the control group (not treated).

The findings reveal a statistically insignificant increase in loan provisions, impairment loss and NPL after the adoption of IFRS 9. These results align with previous studies and suggest that Gulf banks were proactive in anticipating and mitigating the impact of the new standard. The study also observes a synchronization of provisioning practices across Gulf countries and a certain level of consistency in recognizing loan losses.

The practical implications of this study suggest that Gulf banks have successfully absorbed the impact of IFRS 9 and have implemented collaborative approaches.

The study offers some new sight into IFRS9 outcomes in developing countries and opens the door for implementing a novel DiD estimation in future research studies.

A historical analysis of Sikhism demonstrates that Sikh thinking on ethical management has long predated academic thinking and research pertaining to this subject. It also demonstrates the relationship between good management and peace. Sikhism with its relatively secular orientation promoted both profits by working and the peaceful society that was necessary to obtain these. Hence the concept of ‘Sikh Peace management’ became a reality. Its foundation is the idea that working and management for the common good acts as a spiritual experience and that it interacts with and reinforces a peaceful environment. Despite its similarities with Calvin’s work ethics Sikhism did not lead to religious warfare like in 16th and 17th century Europe. It did result however in ‘defensive’ characteristics, which, just like work, became part of a new spirituality.

The efficiency-enhancing and performance-boosting benefits of lean six sigma (LSS) practices have been advocated in both academia and industry. However, their mediating and moderating effects remain unclear and the impact of LSS practices is underdeveloped in the Chinese context. Therefore, by focusing on publicly listed companies in China, this study aims to investigate whether, how and when LSS practices link to organizations’ innovation and financial performance.

Data from 66 Chinese publically listed companies spanning a period of 25 years (2000–2024) was analyzed using the difference-in-difference method which compared the changes in outcomes over time between a treatment group and a control group.

This research found that LSS practices are positively related to firm-level outcomes including innovation and financial performance. The authors also confirm the mediating effect of operational capability on these relationships. Moreover, the empirical evidence suggests that implementing the quality management systems (QMS) standard, ISO 9001, moderates the relationships between LSS practices and innovation and financial performance such that these relationships are stronger for firms in organizations with higher maturity levels in implementing the standard.

This study sheds light on LSS theory and offers valuable recommendations for lean managers on how to leverage LSS practices to improve their innovation and performance capabilities.

This research provides novel insights into the influence of LSS practices on firm-level outcomes such as the level of innovation and financial performance. To the best of the authors’ knowledge, this study is the first to theoretically propose and empirically validate how and when LSS practices influence firm outcomes by introducing the mediating mechanism of operational capability and the boundary condition of QMS standards.