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In developing countries, how risk management technologies influence management accounting and control (MAC) practices is under-researched. By drawing on insights from institutional studies, this study aims to examine the multiple institutional pressures surrounding an entity and influencing its risk-based management control (RBC) system – that is, how RBC appears in an emerging market attributed to institutional multiplicity.

The authors used qualitative case study research methods to collect empirical evidence from a privately owned Egyptian insurance company.

The authors observed that in the transformation to risk-based controls, especially in socio-political settings such as Egypt, changes in MAC systems were consistent with the shifts in the institutional context. Along with changes in the institutional environment, the case company sought to configure its MAC system to be more risk-based to achieve its strategic goals effectively and maintain its sustainability.

This research provides a fuller view of risk-based management controls based on the social, professional and political perspectives central to the examined institutional environment. Moreover, unlike early studies that reported resistance to RBC, this case reveals the institutional dynamics contributing to the successful implementation of RBC in an emerging market.

This study aims to address three research questions pertaining to climate neutrality within the supply chain of metal and mining industry: (1) How can an organization implement practices related to climate neutrality in the supply chain? (2) How do members of the supply chain adopt different measures and essential processes to assist an organization in responding to climate change-related concerns? (3) How can the SAP-LAP framework assist in analyzing and proposing solutions to attain climate neutrality?

To address the proposed research questions concerning climate neutrality, this study employs a case study approach utilizing the SAP-LAP (situation, actor, process–learning, action, performance) framework. Within the SAP-LAP framework, adopting a natural resource-based perspective, the study thoroughly examines the intricacies and interactions among existing situations, pertinent actors and processes that impact climate initiatives within a metal and mining company.

The study's findings suggest that organizations can achieve the objective of climate neutrality by prioritizing resources and capabilities that lead to reduced GHG emissions, lower energy consumption and optimal resource utilization. The study further proposes key elements that significantly influence the pursuit of climate neutrality within enterprises.

This study is one of the earliest contributions to the development of a holistic understanding of climate neutrality in the supply chain of the metal and mining industry.

The study will assist practitioners and policymakers in comprehending the present circumstances, actors and processes involved in enterprises' supply networks in order to attain climate neutrality in supply chains, as well as in taking the right steps to enhance performance.

This study presents a climate neutrality model and provides valuable insights into emission management, contributing to the achievement of the climate neutrality objective.

Mobile location-based service (m-LBS) seems like a new class of personalized service due to location positioning technologies. This work aims to investigate consumer readiness (RED) toward m-LBS based on integrating pull effect- and push effect-related factors into the technology acceptance model (TAM).

An online survey collected data from 423 participants, and the research framework was analyzed using structural equation modeling (SEM).

The results divulge that consumer RED is determined by TAM antecedents, including usefulness (USE) and ease of use (EOU). EOU motivates USE in m-LBS. Regarding pull effect-related factors, absorptive capacity (ABC) is the strongest positive factor influencing consumer RED to use m-LBS, followed by technology willingness (TWI) and innovativeness (INN). Moreover, INN, trust (TRU) and perceived risk (RIS) significantly influence USE and EOU.

This work endeavors to explicate customer RED toward m-LBS by incorporating some meaningful pull effect-related dimensions (i.e. ABC, TWI and INN) and pushing effect-related dimensions (i.e. RIS) into crucial antecedents rooted in TAM. Thus, the findings assist practitioners in developing marketing strategies by boosting pull effects and controlling push effects on customer engagement in m-LBS.

This study aimed to bridge the gap between the financial measurement of process improvement ideas and Lean Six Sigma measurements. It was required to increase employee engagement in process improvement initiatives.

Through both a practical and theoretical application of the Design for Lean Six Sigma methodology, the researcher was able to design a process and a benefit measuring methodology that was acceptable by finance and aligns with the benefits expected from the elimination of the Lean wastes.

The project found that benefit measurement methodology is not understood by most employees, which leads to a lack of engagement in working on improvements. The result of the study was a model for employees to identify and quantify these benefits. This has resulted in a model for cost-benefit analysis aligning financial costs with non-value add waste costs and cost of poor-quality costs resulting in increased process improvement ideas and activity.

While this study was limited to one company, applying this methodology could benefit any company experiencing the same difficulties.

This is one of the first studies to try and cost the benefits of LSS projects both from an organisational and generic viewpoint.

This paper aims to explore how the scientific literature and company reports have addressed inclusive workplace design and strategies to date.

This paper adopts a scoping review to answer the following question: To what extent is inclusion present in workplace design and related strategies? An analysis of 27 scientific papers and 25 corporate social responsibility reports of the highest-ranked companies in the Great Place to Work global ranking disentangles the main aspects related to workplace design and strategies for promoting inclusion.

This paper opens avenues for four macro-categories of diversity (psycho-physical aspects; cultural aspects; socio-economic conditions; and ability, experience and strengths) to support the development of inclusive workplace design and strategy. Besides, multiple spatial scales emerged as material and immaterial elements of the workplace encountering inclusion and diversity.

Nowadays, the workforce is becoming more diverse. Although diversity, equity and inclusion (DE&I) has become key to many organizations, it remains unclear how DE&I principles are applied in workspace design and strategies. This scoping review provides a novel perspective on the topic by integrating scientific knowledge and practice-based approaches which still address this matter independently.

Surface roughness has a serious impact on the fatigue strength, wear resistance and life of mechanical products. Realizing the evolution of surface quality through theoretical modeling takes a lot of effort. To predict the surface roughness of milling processing, this paper aims to construct a neural network based on deep learning and data augmentation.

This study proposes a method consisting of three steps. Firstly, the machine tool multisource data acquisition platform is established, which combines sensor monitoring with machine tool communication to collect processing signals. Secondly, the feature parameters are extracted to reduce the interference and improve the model generalization ability. Thirdly, for different expectations, the parameters of the deep belief network (DBN) model are optimized by the tent-SSA algorithm to achieve more accurate roughness classification and regression prediction.

The adaptive synthetic sampling (ADASYN) algorithm can improve the classification prediction accuracy of DBN from 80.67% to 94.23%. After the DBN parameters were optimized by Tent-SSA, the roughness prediction accuracy was significantly improved. For the classification model, the prediction accuracy is improved by 5.77% based on ADASYN optimization. For regression models, different objective functions can be set according to production requirements, such as root-mean-square error (RMSE) or MaxAE, and the error is reduced by more than 40% compared to the original model.

A roughness prediction model based on multiple monitoring signals is proposed, which reduces the dependence on the acquisition of environmental variables and enhances the model's applicability. Furthermore, with the ADASYN algorithm, the Tent-SSA intelligent optimization algorithm is introduced to optimize the hyperparameters of the DBN model and improve the optimization performance.

School-university partnerships (SUPs) probe a range of P12 challenges and interests, with teacher residencies being chief among them. Because historically black colleges and universities (HBCUs) have impressive track records (Hill-Jackson, 2017) and knowhow (Marchitello & Trinidad, 2019; Petchauer & Mawhinney, 2017) in preparing teacher candidates to work effectively in diverse schools, this paper seeks deeper understandings of the types of SUPs for teacher residency collaborations employed by traditional versus HBCU programs.

This article draws upon the self-study as a methodology to review a SUP for a teacher residency at an HBCU in the southwestern United States to illustrate an equity-centric model.

Leveraging an equity and third space perspective, three separate approaches to the SUPs are unpacked to establish the outline for this proposal: ceremonial, conventional and communal teacher residency approaches.

A novel typology of three distinct approaches to SUPs for teacher residencies is outlined to establish the extent to which equity is foregrounded among teacher residencies.