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The purpose of this paper is to help better understand the translation process of the management control system (MCS) of privatised solid waste management (SWM) towards creating a stable network.

Drawing on the actor network theory (ANT), the case of a privatised SWM was studied. Data were collected from all entities involved in the privatisation process of SWM, which include Department A, Corporation X and the private sector concessionaire. Six documents were reviewed, 20 interviews were conducted and two observations were carried out.

The findings reveal that the control mechanism of SWM is complex, involving the interaction between human and non-human actors. Non-human actors include the key performance indicators (KPIs) and the concessionaire agreement (CA), which are the main control mechanisms towards creating a stable SWM network. Essentially, stability is achieved when the KPIs and CA can influence the activities of both intra- and inter-organisational relationships.

This paper provides a better understanding of the translation process of the MCS that adds to the stability of the network of a privatised SWM from the lens of the ANT.

This paper aims to map the research on management accounting (MA), clarifying its current role and identifying gaps and opportunities for future research.

In this paper, 784 papers were reviewed for the 1958–2019 period, published in 220 scientific journals indexed on Clarivate Analytics’ Web of Science (Science Citation Index Expanded [SCI-EXPANDED] and Social Sciences Citation Index [SSCI]). In the process, content analysis, regression analysis and bibliometric analysis were used.

The most relevant journals, authors and topics in MA, along with trends and patterns in the literature, were identified. Seven clusters that represent the overall thematic research structure of the MA field were also identified. This study shows that MA is becoming a multidimensional management decision-support instrument covering all organizational dimensions. As such, the research on MA is following the recent concerns with the sustainable development and digitalization of business processes.

Based on the findings of this research study, theoretical and practical implications for MA researchers were provided. These findings could also be useful to industry practitioners to improve their knowledge of emerging trends in MA practices, strategies and concepts.

Based on bibliometric and content analysis, a framework that shows an organizational, market and social context for the evolution of MA over the past 60 years was provided. It highlights the dynamics of MA alignment with organizational and external environment changes. Future research opportunities and implications for researchers and practitioners were also identified.

People donate to charities with the aim of improving society. Yet, many charities fail to use donations efficiently or have ineffective interventions. The authors explore the strategic operational priorities and processes that enable charities to efficiently implement their interventions and have a positive impact on society.

The authors first review the literature on charities to gain a deeper understanding of the current state of knowledge on charity operations. The authors then employ the lens of paradox theory and perform a qualitative investigation of six case studies to explore various aspects of the operations of charities that are known for being cost-effective.

The authors reveal how the strategic operational decisions of charities, as well as the processes they implement, help them resolve the tensions arising from the cost-effectiveness paradox. The authors show that cost-effective charities make strategic operational decisions that help maintain two diverging priorities: prioritizing the status quo and prioritizing change in how they deliver value. Another set of strategic decisions helps balance these two diverging priorities. The authors then show how these charities create and then maintain cost-effective operations.

The authors address recent calls for research on non-profit organizations in the field of operations management. To authors’ knowledge, it is the first in-depth study of exemplary charity operations. The results can be used by charity executives as a benchmarking tool when they develop and implement their charitable interventions and by government agencies and potential donors when they select charities for their donations. Finally, the results should have implications for other organizations trying to have a positive societal impact.

Despite the well-recognized importance of recycled water, the study of industry-peer pressure on recycled water is relatively new. This study investigates how organizations experience and react to industry-peer pressure to set recycled water targets. Additionally, this study investigates the role of board chairs involved in sustainability committees in contributing to responses to industry-peer pressure.

Using Eviews 12, this study employed a pooled logistic regression model to analyze data from 1,346 firms on Taiwan and Taipei exchanges (2017–2020).

The findings revealed that frequency-based imitation drives recycled water target-setting diffusion. However, there is no direct relationship between outcome-based imitation and recycled water target-setting. Notably, outcome-based imitation drives the adoption of recycled water target-setting of firms with board-chair membership in sustainability committees.

This study faces certain data limitations. First, this study primarily focuses on water recycling. Future research could explore other ways to reduce water usage, such as using water-efficient equipment. Second, this study gathered information solely on the presence or absence of a board chairperson on the sustainability committee. Future researchers could explore the impact of the composition of sustainability committee on recycled water target-setting. Lastly, the sample used in this study is restricted to Taiwan's corporations that existed during 2017–2020. Future researchers may consider adopting a longitudinal design in other economies to address this limitation.

The findings of this study offer several guidelines and implications for recycled water target-setting and the composition of sustainability committees. It responds to an urgent call for solutions to water shortages when pressure from governments and nongovernmental organizations is relatively absent. The number of industry peers that have already set recycled water targets is indispensable for motivating firms to set their own recycled water targets. In terms of insufficient water-related regulatory pressure and normative pressure, this study found evidence suggesting that the direct motivation for setting recycled water targets stems from mimetic pressures via frequency-based imitation. The evidence in this study suggests that policymakers should require companies to disclose their peers’ recycled water target information, as doing so serves as an alternative means to achieving SDG 6.3.

Recycled water target-setting might be challenging. Water recycling practices may face strong resistance and require substantial additional resources (Zhang and Tang, 2019; Gao et al., 2019; Gu et al., 2023). Therefore, this study suggests that firms should ensure the mindfulness of board members in promoting the welfare of the natural environment when making recycled water target-setting decisions. To reap the second-mover advantage, firms must consider the conditions in which board members can more effectively play their role. Corporations may help their chairpersons in setting recycled water targets by recruiting them as members of sustainability committees. Meanwhile, chairpersons tend to activate accurate mental models when the water conservation performance of pioneering industry peers is strong enough to indicate the potential benefits of adopting recycled water target-setting. Investors’ and stakeholders’ understanding of how the composition of sustainability committees is related to recycled water target-setting may help to identify the potential drivers of firms’ water responsibility. Investors and stakeholders should distinguish firms in terms of the board chair’s membership of their sustainability committee and focus on water-use reduction outcomes in the industry. This study provides insights into circumstances whereby chairpersons help to restore the water ecosystem.

This study explains how frequency-based and outcome-based imitation are two prominent mechanisms underlying the industry-peer pressure concerning recycled water target-setting. Moreover, this study fills literature gaps related to the moderating roles of board-chair membership in sustainability committees concerning industry-peer pressure on recycled water target-setting.

This study aims to analyse the influence of digitalisation on the management control function of small and medium-sized enterprises (SMEs). In particular, it aims to illuminate how digitalisation influences management control elements, organisation and roles/competencies and to identify obstacles to digitalisation of management control in SMEs and measures taken to overcome them.

The study is based on guideline-supported expert interviews conducted with 14 financial managers from SMEs in Germany, Austria and Switzerland.

This study reveals the influence of digitalisation on management control elements, organisation, and roles/competencies. The automation and standardisation of management control processes result in new elements for management control, such as strategic support for management. In addition, the increased availability and transparency of data enable the use of instruments within a company that allow for quick analyses of the company's development. Digitalisation leads to the integration of management control into the corporate network and, thus, a change in the organisation of management control. It also triggers the expansion of management control competencies, especially IT competencies. A shortage of internal digitalisation resources, unclear corporate roadmaps, and a lack of managerial experience loom as central challenges for digitalising the management control function. Measures derived from the interviews can help SMEs overcome the obstacles to the digitalisation of management control.

This research is the first interview-based study of the impact of digitalisation on management control in SMEs, potential obstacles to that digitalisation, and measures to overcome those obstacles. Thus, it contributes to the emerging debate on factors that may explain why SMEs lag in terms of the digitalisation of their internal processes.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.

This study aims to explore the moderating effects of strategy on the relationship between working capital management (WCM) and profitability.

A data sample of 72,444 firm-year observations of US-listed firms during 2000–2020 was used. The research hypotheses were tested using a panel regression analysis and an appropriate research instrument that signifies a firm’s strategic positioning.

The prospecting (defending) strategy has a decreasing (increasing) moderating effect on the relationship between WCM and profitability. The empirical findings are not affected by the level of earnings management, the presence of motives to meet earnings targets or the intensity of unreported intangible assets. Additionally, the reported empirical results remain robust within the context of propensity score matching regression analysis, in the presence of nonlinear effects of WCM on profitability, when alternative measures of WCM are used, and between firms with an increase or decrease in future profitability or different levels of efficiency on net WCM investments.

This study may stimulate future research exploring the moderating effects of various variables on the relationship between WCM and operating performance.

The findings highlight the importance of strategy for improving the performance evaluation of WCM policies and the prediction accuracy of the consequences of a strategy on short-term operating performance.

Prior empirical research has documented either a negative or positive relationship between WCM and profitability, which implies the presence of moderating effects of various factors. This study provides empirical evidence of the moderating effects of strategy on the relationship between WCM and profitability.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

This paper explores Lean Six Sigma principles and the DMAIC (define, measure, analyze, improve, control) methodology to propose a new Lean Six Sigma 4.0 (LSS 4.0) framework for employee occupational exams and address the real-world issue of high-variability exams that may arise.

This study uses mixed methods, combining qualitative and quantitative data collection. A detailed case study assesses the impact of LSS interventions on the exam management process and tests the applicability of the proposed LSS 4.0 framework for employee occupational exams.

The results reveal that changing the health service supplier in the explored organization caused a substantial raise in occupational exams, leading to increased costs. By using syntactic interoperability, lean, six sigma and DMAIC approaches, improvements were identified, addressing process deviations and information requirements. Implementing corrective actions improved the exam process, reducing the number of exams and associated expenses.

It is important to acknowledge certain limitations, such as the specific context of the case study and the exclusion of certain exam categories.

The practical implications of this research are substantial, providing organizations with valuable managerial insights into improving efficiency, reducing costs and ensuring regulatory compliance while managing occupational exams.

This study fills a research gap by applying LSS 4.0 to occupational exam management, offering a practical framework for organizations. It contributes to the existing knowledge base by addressing a relatively novel context and providing a detailed roadmap for process optimization.