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This study aims to evaluate the effectiveness of tax incentives provided by the Ethiopian government in spurring private investment and job creation, using unique administrative and survey data.

The study employs a dataset covering large- and medium-scale manufacturing in Ethiopia from 2012 to 2018, combined with administrative data on actual tax payments and statutory obligations to gauge the impact of tax incentives. Regression analysis using the generalized method of moments (GMM) is used to examine the relationship between tax incentives and employment, taking into account variations in production, distribution and financial costs.

The study finds that tax incentives do not significantly affect employment at conventional significance levels. The incentive elasticity of employment appears to diminish as production, distribution and financial costs increase. Consequently, the incentives provided by the government have not had a substantial impact on employment generation within the manufacturing sector.

This study is unique for its comprehensive analysis of tax incentives in the Ethiopian manufacturing sector using both administrative and survey data. It highlights that increasing production and financial costs can offset the employment benefits of these incentives, emphasizing the need for a more favorable business environment for private investors.

Small retail stores in the luxury market face significant challenges due to fluctuations in market demand. This task turns challenging as it requires effectively coordinating and translating customer needs into specific requirements that align with retail goals and available resources. However, limited empirical research exists investigating how managers can address service value and quality attributes in small retail stores. This article aims to bridge this gap by investigating the role of quality function deployment (QFD) in improving market and quality requirements management in small retail stores.

Based on the case study, a customer survey was initially conducted to gather information on critical characteristics valued in the luxury retail segment. QFD was used to assist the company in identifying and prioritizing key quality attributes to meet customer requirements effectively.

The findings demonstrate that implementing QFD in small luxury retail stores empowers managers to identify previously neglected product and service quality aspects. The article shows that QFD informs organizational adaptations that align with the demands of the retail market, leading to an improved ability to meet customer expectations and enhance customer value through the development of enhanced products and services. The study showcases the efficacy of the tested methodology in effectively capturing and prioritizing both tangible and intangible customer needs in retail.

Findings offer valuable insights to retail managers of small luxury stores, providing actionable market-oriented strategies. By implementing the recommended practices, managers can improve the store’s competitiveness and better cater to the customer base.

This study contributes to bridging persistent knowledge gaps by addressing the unique context of small luxury retail stores and introducing the application of QFD in this setting. The insights gained from this research are relevant to both retailing and quality management literature. Considering the growing prevalence of transformations in the retail industry, the study provides practical implications for retail managers in effectively navigating these changes.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

This study aims to identify the main challenges to achieving humanitarian logistics in the context of United Nations peace missions in sub-Saharan Africa and to present suggestions for overcoming the logistical gaps encountered.

The methodological approach of the work focuses on the comparative case study of the United Nations Mission in South Sudan, the United Nations Multidimensional Integrated Stabilisation Mission in the Central African Republic and The United Nations Organisation Stabilisation Mission in the Democratic Republic of Congo from 2014 to 2021. The approach combined a systematic literature review with the authors’ empirical experience as participant observers in each mission, combining theory and practice.

As a result, six common challenges were identified for carrying out humanitarian logistics in the three peace missions. Each challenge revealed a logistical gap for which an appropriate solution was suggested based on the best practices found in the case study of each mission.

This paper presents limitations when addressing the logistical analysis based on only three countries under the UN mission as a case study, as well as conceiving that certain flaws in the system, in the observed period, are already in the process of correction with the adoption of the 2016–2021 strategy by the UN Global Logistic Cluster. The authors suggest that further studies can be carried out by expanding the number of cases or using countries where other bodies (AU, NATO or EU) work.

To the best of the authors’ knowledge, this study is the first comparative case study of humanitarian logistics on the three principal missions of the UN conducted by academics and practitioners.

This paper analyses how firm births and deaths are influenced by previous firm births and deaths in related and unrelated sectors. Competition and multiplier effects are used as the theoretical lens for this analysis.

This paper uses 2008–2016 Irish business demography data pertaining to 568 NACE 4-digit sectors within 20 NACE 1-digit industries across 34 Irish county and sub-county regions within 8 NUTS3 regions. A three-stage least squares (3SLS) estimation is used to analyse the impact of past firm deaths (births) on future firm births (deaths). The effect of relatedness on firm interrelationships is explicitly modelled and captured.

Findings indicate that the multiplier effect operates mostly through related sectors, while the competition effect operates mostly through unrelated sectors.

This paper's findings show that firm interrelationships are significantly influenced by the degree of relatedness between firms. The raw data used to calculate firm birth and death rates in this analysis are count data. Each new firm is measured the same as another regardless of differing features like size. Some research has shown that smaller firms have a greater propensity to create entrepreneurs (Parker, 2009). Thus, it is possible that the death of differently sized firms may contribute differently to multiplier effects where births induce further births. Future research could seek to examine this.

These findings have implications for policy initiatives concerned with increasing entrepreneurship. Some express concerns that public investment into entrepreneurship can lead to “crowding out” effects (Cumming and Johan, 2019), meaning that public investment into entrepreneurship could displace or reduce private investment into entrepreneurship (Audretsch and Fiedler, 2023; Zikou et al., 2017). This study’s findings indicate that using public investment to increase firm births could increase future firm births in related and unrelated sectors. However, more negative “crowding out” effects may also occur in unrelated sectors, meaning that public investment which stimulates firm births in a certain sector could induce firm deaths and crowd out entrepreneurship in unrelated sectors.

This paper is the first in the literature to explicitly account for the role of relatedness in firm interrelationships.

Total productive maintenance consists of strategies and procedures that aim to guarantee the entire functioning of machines in a production process so that production is not interrupted and no loss of quality in the final product occurs. Planned maintenance is one of the eight pillars of total productive maintenance, a set of tools considered essential to ensure equipment reliability and availability, reduce unplanned stoppage and increase productivity. This study aims to analyze the influence of statistical reliability on the performance of such a pillar.

In this study, we utilized a multi-method approach to rigorously examine the impact of statistical reliability on the planned maintenance pillar within total productive maintenance. Our methodology combined a detailed statistical analysis of maintenance data with advanced reliability modeling, specifically employing Weibull distribution to analyze failure patterns. Additionally, we integrated qualitative insights gathered through semi-structured interviews with the maintenance team, enhancing the depth of our analysis. The case study, conducted in a fertilizer granulation plant, focused on a critical failure in the granulator pillow block bearing, providing a comprehensive perspective on the practical application of statistical reliability within total productive maintenance; and not presupposing statistical reliability is the solution over more effective methods for the case.

Our findings reveal that the integration of statistical reliability within the planned maintenance pillar significantly enhances predictive maintenance capabilities, leading to more accurate forecasts of equipment failure modes. The Weibull analysis of the granulator pillow block bearing indicated a mean time between failures of 191.3 days, providing support for optimizing maintenance schedules. Moreover, the qualitative insights from the maintenance team highlighted the operational benefits of our approach, such as improved resource allocation and the need for specialized training. These results demonstrate the practical impact of statistical reliability in preventing unplanned downtimes and informing strategic decisions in maintenance planning, thereby emphasizing the importance of your work in the field.

In terms of the originality and practicality of this study, we emphasize the significant findings that underscore the positive influence of using statistical reliability in conjunction with the planned maintenance pillar. This approach can be instrumental in designing and enhancing component preventive maintenance plans. Furthermore, it can effectively manage equipment failure modes and monitor their useful life, providing valuable insights for professionals in total productive maintenance.

Drawing insights from institutional theory, this paper aims to examine whether and to what extent banks have reconfigured their management control systems (MCSs) in response to growing institutional pressures towards sustainability, understood as environmental, social and governance (ESG) issues.

The authors conducted an exploratory study at the three largest Italian banking groups to shed light on changes made in MCSs to account for ESG issues. The analysis is based on 12 semi-structured interviews with managers from the sustainability and controls areas, as well as from other relevant operational areas particularly concerned with the integration process of ESG issues. Additionally, secondary data sources were used. The Malmi and Brown (2008) MCS framework, consisting of a package of five types of formal and informal control mechanisms, was used to structure and analyse the empirical data.

The examined banks widely implemented numerous changes to their MCSs as a response to the heightened sustainability pressures from regulatory bodies and stakeholders. In particular, with the exception of action planning, the results show an extensive integration of ESG issues into the five control mechanisms of Malmi and Brown’s framework, namely, long-term planning, cybernetic, reward/compensation, administrative and cultural controls.

By identifying the approaches banks followed in reconfiguring traditional MCSs, this research sheds light on how adequate MCSs can promote banks’ “sustainable behaviours”. The results can, thus, contribute to defining best practices on how MCSs can be redesigned to support the integration of ESG issues into the banks’ way of doing business.

Overall, the findings support the theoretical assertion that institutional pressures influence the design of banks’ MCSs, and that both formal and informal controls are necessary to ensure a real engagement towards sustainability. More specifically, this study reveals that MCSs, by encompassing both formal and informal controls, are central to enabling banks to appropriately understand, plan and control the transition towards business models fully oriented to the integration of ESG issues. Thereby, this allows banks to effectively respond to the increased stakeholder demands around ESG concerns.

In this paper, the authors examine the strategies used to reduce labour costs in three public hospitals in South Africa, which were effective and why. In the democratic era, after the revelations of large-scale corruption, the authors ask whether their case studies provide lessons for how public service institutions might re-make themselves, under circumstances of austerity.

A comparative qualitative case study approach, collecting data using a combination of interviews with managers, focus group discussions and interviews with shop stewards and staff was used.

Management in two hospitals relied on their financial power, divisions between unions and employees' loyalty. They lacked the insight to manage different actors, and their efforts to outsource services and draw on the Extended Public Works Program failed. They failed to support staff when working beyond their scope of practice, reducing employees' willingness to take on extra responsibilities. In the remaining hospital, while previous management had been removed due to protests by the unions, the new CEO provided stability and union–management relations were collaborative. Her legitimate power enabled unions and management to agree on appropriate cost cutting strategies.

Finding an appropriate balance between the new reality of reduced financial resources and the needs of staff and patients, requires competent unions and management, transparency and trust to develop legitimate power; managing in an authoritarian manner, without legitimate power, reduces organisational capacity. Ensuring a fair and orderly process to replace ineffective management is key, while South Africa grows cohorts of competent managers and builds managerial experience.

This work conducts a comprehensive analysis of how to incorporate resilience and sustainability into capacity expansion strategies for business-to-business (B2B) chemical supply chains. This study aims to guide both researchers and managers on ensuring profitability in B2B chemical supply chains while minimizing environmental impacts, complying with regulations and mitigating disruptions and risks.

A systematic literature review is conducted to analyze the interplay between sustainability and resilience in chemical B2B supply chains, specify the quantitative and qualitative methods used to tackle this challenge and identify the drivers and barriers concerning capacity expansion. In addition, a comprehensive conceptual framework is suggested to outline a compelling research agenda.

The findings emphasize the increasing importance of modeling and resolving decision-making challenges related to sustainable and resilient supply chains, particularly in capital-intensive chemical industries. Yet, there is no standardized strategy for addressing these challenges. The predominant solution methods are heuristic and metaheuristic, and the selection of performance metrics tends to be empirical and tailored to specific cases. The main barriers to achieving sustainability and resilience arise from resource limitations within the supply chain. Conversely, the key drivers of performance focus on enhancing efficiency, competitiveness, cost effectiveness and risk management.

This work offers practitioners a conceptual framework that synthesizes the knowledge and tackles the challenges of designing sustainable and resilient supply chains as well as managing their operations in the context of B2B chemical supply chains. Results provide a practical guide for navigating the complex interplay of sustainability, resilience and chemical supply chain expansion.

The key concepts and dimensions associated with capacity expansion planning for a resilient and sustainable chemical supply chain are identified through structured and comprehensive analyses of existing literature. A conceptual framework is proposed for delineating the intersections among sustainability, resilience and chemical supply chain expansions. This mapping endeavor aims to facilitate a future characterized by the deployment of a nexus of resilience and sustainability in chemical supply chains. To this end, a promising future research agenda is accordingly outlined.

The adoption of energy-efficient systems is crucial for Pakistan to meet its growing energy demand and address its energy challenges. However, adoption of these systems in Pakistan is hindered by several barriers, including economic constraints, lack of awareness and social attitudes toward sustainable development. Therefore, the purpose of this study is to explore adoption of energy-efficient household systems and the associated social influence.

The study incorporates social influence as a mediating factor to examine the relationships between awareness of consequences, perceived consumer effectiveness and attitudes toward the adoption of energy-efficient systems. A quantitative survey method was used to collect data from households from Faisalabad, Pakistan. A total of 203 valid questionnaires were received and data analyzed through SmartPLS 4 for structural equation modeling.

The results revealed that awareness of consequences positively impacts compliance, social identification and internalization, while perceived consumer effectiveness has a positive relationship with social identification and internalization. Moreover, the positive association of social identification and internalization with attitude were supported but relationship of compliance with attitude was unsupported.

The results may also be used to develop compelling marketing campaigns focusing environmental conservation and social influence for positive attitude development.

The study contributes to theoretical literature by examining the empirical relationships between specific individual characteristics and societal pressure that play a critical role in shaping attitudes toward the acceptance of energy-efficient systems. Additionally, the study's findings offer actionable implications for policymakers and marketers, contributing to the development of targeted interventions for promoting sustainable consumption.