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In 2007, Best Buy was the leading electronics retailer in the United States with more than 941 stores, revenue totaling $31 billion, and a market cap of $21 billion. In 2005, Best Buy had adopted a new business model, culture, and customer-segmentation template called Customer Centricity. This move created volatility in the price of Best Buy stock because of the higher-than-expected employee costs that went with this new way of doing business and the difficulty of executing the old and the new business models simultaneously while the new model was rolled out. Best Buy responded to Wall Street's short-term focus in a myriad of ways. It first asked for investor patience, and stressed the strong operating results achieved in Best Buy stores operating under the new model. But in June 2007, after the stock dropped again, the CEO knew he had to decide whether to open more Best Buy stores, increase the company's dividend, or increase the stock-repurchase program.

This study explores the awareness (AWN) levels of good governance amongst Thai credit union cooperatives' (CUCs) members and the factors hindering good governance practice in Thai CUCs.

This study used a survey questionnaire from 629 members of 36 selected CUCs in Thailand. This study analysed the determinants of governance AWN levels of Thai CUCs' members using the ordered probit model. The study also employs OLS estimation to investigate the factors hindering good governance practices.

The study shows that members of different CUC types and sizes have different levels of governance AWN. Members' characteristics, experiences, and perceptions significantly influence CUC members' AWN of governance issues. The findings also suggest that a lack of morality, transparency, participation, responsibility and accountability are key obstacles that hinder good governance practices of Thai CUCs.

This is the first study that attempts to assess the level of AWN amongst Thai CUCs' members in different CUC sizes and types. This is also the first research that identifies the factors that hinder good governance practice in Thai CUCs based on members' evaluations. The study's findings provide important reference and implications for Thai policy makers and CUCs' board of managers to enhance members' AWN and CUCs' governance performance, and thus increase income and living standard of CUCs' members in the long term.

The paper discusses how the management of a sports and fashion company, which we refer to as NULMA, successfully applied the neo/normative control technology “karma organisation” and gained employee engagement. Whereas other studies have documented employee resistance to organisational cultures when used for managerial control, our case demonstrates resistance to management practices that employees find inconsistent with the dominant karma culture.

The study is based on a six-year longitudinal organisational at-home ethnography conducted by one of the authors using methods of both participant and non-participant observation, semi-structured interviews and collaborative production of secondary data in the case organisation.

While our research shows that management can successfully apply neo/normative control which employees accept and support, we further show that employees mobilise the same values to resist management when it fails to deliver on the commitments and promises of the organisational culture.

The study contributes to the literature on organisational culture and, in particular, neo/normative control by theorising employee resistance as being by “accident”, by which we mean an inherent negative potentiality co-invented and released by managers establishing a “karma organisation”. Our theorising culminates in a discussion of the study’s implications for research and practice.

The purpose of the paper is to study how technology choice is affected by capital accumulation when there is unemployment and firms engage in oligopolistic competition.

In this infinite horizon model, unemployment results from the existence of efficiency wages. Consumers choose saving optimally, and there is capital accumulation. Firms producing intermediate goods engage in oligopolistic competition and choose technologies to maximize profits. A more advanced technology has a higher fixed cost but a lower marginal cost of production.

In the steady state, it is shown that an increase in population size or a decrease in the discount rate leads intermediate good producers to choose more advanced technologies and the wage rate increases. Interestingly, the equilibrium unemployment rate decreases with the size of the population.

In this model, unemployment results from the existence of efficiency wages and firms engage in oligopolistic competition. One difficulty with efficiency wage models is that saving is not allowed. However, in this model, consumers choose saving optimally, and capital accumulation is allowed. With oligopolistic competition, the authors show that an increase in population size or a decrease in the discount rate leads intermediate good producers to choose more advanced technologies and the wage rate increases. The equilibrium unemployment rate decreases with the size of the population.

This study aims to evaluate the efficiency of various techniques for enhancing indoor air quality (IAQ) in construction. It analyzed the alterations in the concentration of indoor air pollutants over time for each product employed in controlling pollution sources and removing it, which included eco-friendly substances and adsorbents. The study will provide more precise and dependable data on the effectiveness of these control methods, ultimately supporting the creation of more efficient and sustainable approaches for managing indoor air pollution in buildings.

The research investigates the impact of eco-friendly materials and adsorbents on improving indoor air quality (IAQ) in Dubai's tall apartment buildings. Field experiments were conducted in six units of The Gate Tower, comparing the IAQ of three units built with “excellent” grade eco-friendly materials with three built with “good” grade materials. Another experiment evaluated two adsorbent products (H and Z) in the Majestic Tower over six months. Results indicate that “excellent” grade materials significantly reduced toluene emissions. Adsorbent product Z showed promising results in pollutant reduction, but there is concern about the long-term behavior of adsorbed chemicals. The study emphasizes further research on household pollutant management.

The research studied the effects of eco-friendly materials and adsorbents on indoor air quality in Dubai's new apartments. It found that apartments using “excellent” eco-friendly materials had significantly better air quality, particularly reduced toluene concentrations, compared to those using “good” materials. However, high formaldehyde (HCHO) emissions were observed from wood products. While certain construction materials led to increased ethylbenzene and xylene levels, adsorbent product Z showed promise in reducing pollutants. Yet, there is a potential concern about the long-term rerelease of these trapped chemicals. The study emphasizes the need for ongoing research in indoor pollutant management.

The research, while extensive, faced limitations in assessing the long-term behavior of adsorbed chemicals, particularly the potential for rereleasing trapped pollutants over time. Despite the study spanning a considerable period, indoor air pollutant concentrations in target households did not stabilize, making it challenging to determine definitive improvement effects and reduction rates among products. Comparisons were primarily relative between target units, and the rapid rise in pollutants during furniture introduction warrants further examination. Consequently, while the research provides essential insights, it underscores the need for more prolonged and comprehensive evaluations to fully understand the materials' and adsorbents' impacts on indoor air quality.

The research underscores the importance of choosing eco-friendly materials in new apartment constructions for better IAQ. Specifically, using “excellent” graded materials can significantly reduce harmful pollutants like toluene. However, the study also highlights that certain construction activities, such as introducing furniture, can rapidly elevate pollutant levels. Moreover, while adsorbents like product Z showed promise in reducing pollutants, there is potential for adsorbed chemicals to be rereleased over time. For practical implementation, prioritizing higher-grade eco-friendly materials and further investigation into furniture emissions and long-term behavior of adsorbents can lead to healthier indoor environments in newly built apartments.

The research offers a unique empirical assessment of eco-friendly materials' impact on indoor air quality within Dubai's rapidly constructed apartment buildings. Through field experiments, it directly compares different material grades, providing concrete data on pollutant levels in newly built environments. Additionally, it explores the efficacy of specific adsorbents, which is of high value to the construction and public health sectors. The findings shed light on how construction choices can influence indoor air pollution, offering valuable insights to builders, policymakers and residents aiming to promote public health and safety in urban living spaces.

This research seeks to understand whether employer branding (EB) and internal marketing (IM) are fundamental to the challenge of attracting and retaining talent and how these strategies can help companies to overcome the difficulties related to the talent shortage, from the perspective of a SME Portuguese metallurgical industry.

The research resorts to a case study of a qualitative nature, through a semi-structured interview with the head of the human resources (HR) training and development area of the Navarra Group, and quantitative, through surveys to its employees. Based on the literature, a conceptual model was constructed, whose application allowed us to perceive the relationships between the practices of EB and IM; satisfaction, motivation and commitment; attraction and retention.

The exploratory interview concluded that organizations consider EB and IM essential for an effective talent management strategy. The quantitative results demonstrate that IM and EB practices implemented in the organization contribute to the satisfaction, motivation and involvement of employees, which results in a decrease in the intention to leave. It is also noted that these practices promote an increase in the perception of organizational attractiveness, which represents a positive impact on its ability to attract.

From a theoretical perspective, the research contributes to the development of knowledge about IM, EB and talent management, providing relevant data that can help define the best strategies for attraction and retention, from the point of view of IM and EB.

The research presents preliminary insights that can be an auxiliary tool for HR managers and professionals in the context of industrial SMEs.

Although risk culture is a key determinant for an effective risk management, identifying the risk culture of a firm can be challenging due to the abstract concept of culture. This paper proposes a novel approach that uses unsupervised machine learning techniques to identify significant features needed to assess and differentiate between different forms of risk culture.

To convert the unstructured text in our sample of banks' 10K reports into structured data, a two-dimensional dictionary for text mining is built to capture risk culture characteristics and the bank's attitude towards the risk culture characteristics. A principal component analysis (PCA) reduction technique is applied to extract the significant features that define risk culture, before using a K-means unsupervised learning to cluster the reports into distinct risk culture groups.

The PCA identifies uncertainty, litigious and constraining sentiments among risk culture features to be significant in defining the risk culture of banks. Cluster analysis on the PCA factors proposes three distinct risk culture clusters: good, fair and poor. Consistent with regulatory expectations, a good or fair risk culture in banks is characterized by high profitability ratios, bank stability, lower default risk and good governance.

The relationship between culture and risk management can be difficult to study given that it is hard to measure culture from traditional data sources that are messy and diverse. This study offers a better understanding of risk culture using an unsupervised machine learning approach.

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

The paper aims at studying the effect of management practices on the extensive and intensive export margins of Egyptian manufacturing firms.

The study relies on the 2020/2021 Egyptian Industrial Firm Behavior Survey (EIFBS) which comprises 2,383 manufacturing firms representing small, medium, and large sized firms located in different regions of Egypt: Urban Governorates, Lower Egypt, and Upper Egypt. It constructs an overall management z score for each firm to estimate its effect on a firm’s probability of exporting and value of exports using Ordinary Least Squares (OLS) regressions.

Results indicate that good management is associated with a higher probability of firm exporting as well as higher export revenues conditional on exporting, robust to controlling for the level of domestic sales. These effects do not differ by firm ownership or type of sector, but rather by firm size, with managerial competence raising the probability of exporting more for large-sized firms. Additionally, good management is associated with higher firm productivity, innovation and worker training propensities which gives evidence that it is both an efficiency and a quality enhancer. Moreover, monitoring and targeting practices have significant positive effects on both margins, while incentives are only significant for the extensive margin.

Firms that aim at enhancing their export prospects and revenues should devote resources to review and upgrade their management systems to boost their product quality and production efficiency. Policy-wise, the government should create a competitive market environment that is open to both domestic and foreign firms’ entry to stimulate the adoption of better management practices.

The paper is the first to explore the link between firm management practices and export outcomes for a MENA country (Egypt). It makes use of a recent survey, the 2020/2021 Egyptian Industrial Firm Behavior Survey (EIFBS). The findings shed light on the importance of different management components (monitoring, targeting and incentives) in driving a manufacturing firm’s export performance.

The purpose of this paper is to study the effects of sports sponsorship on brand equity using two managerially related outcomes: price premium and market share.

This study uses a best–worst discrete choice experiment (BWDCE) and compares the outcome with that of the purchase intention scale, an established probabilistic measure of purchase intention. The total sample consists of 409 fans of three soccer teams sponsored by three different competing brands: Nike, Adidas and Puma.

With sports sponsorship, fans were willing to pay more for the sponsor’s product, with the sponsoring brand obtaining the highest market share. Prominent brands generally performed better than less prominent brands. The best–worst scaling method was also 35% more accurate in predicting brand choice than a purchase intention scale.

Future research could use the same method to study other types of sponsors, such as title sponsors or other product categories.

Sponsorship managers can use this methodology to assess the return on investment in sponsorship engagement.

Prior sponsorship studies on brand equity tend to ignore market share or fans’ willingness to pay a price premium for a sponsor’s goods and services. However, these two measures are crucial in assessing the effectiveness of sponsorship. This study demonstrates how to conduct such an assessment using the BWDCE method. It provides a clearer picture of sponsorship in terms of its economic value, which is more managerially useful.