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Avoided emissions refer to greenhouse gas emission reductions that are a result of using a product or are emission removals due to a decision or an action. Although there is no uniform standard for calculating avoided emissions, market actors have started referring to avoided emissions as “Scope 4” emissions. By default, making a claim about Scope 4 emissions gives an appearance that this Scope of emissions is a natural extension of the existing and accepted Scope-based emissions accounting framework. The purpose of this study is to explore the implications of this assumed legitimacy.

Via a desktop review and interviews, we analyse extant Scope 4 company reporting, associated accounting methodologies and the practical implications of Scope 4 claims.

Upon examination of Scope 4 emissions and their relationship with Scopes 1, 2 and 3 emissions, we highlight a dynamic and interdependent relationship between quantification, commensuration and standardization in emissions accounting. We find that extant Scope 4 assessments do not fit the established framework for Scope-based emissions accounting. In line with literature on the territorializing nature of accounting, we call for caution about Scope 4 claims that are a distraction from the critical work of reducing absolute emissions.

We examine the implications of assumed alignment and borrowed legitimacy of Scope 4 with Scope-based accounting because Scope 4 is not an actual Scope, but a claim to a Scope. This is as an act of accounting territorialization.

This study aims to investigate why and how shared service centres (SSCs) are implemented as well as how they affect audit firm practice and audit quality.

In this qualitative study guided by the theoretical framework of institutional theory, the authors conducted 25 semi-structured interviews in seven European countries, including 16 interviews with audit partners from Big 4 firms, 6 with audit team members, 2 with interviewees from second-tier audit firms and 1 with a member of an oversight body.

The authors show that the central rationale for audit firms to implement SSCs is economic rather than external legitimacy. The authors find that SSC implementation has substantial effects on audit practices, particularly those related to standardisation, coordination and monitoring activities. The authors also highlight the potential impacts on audit quality.

By exploring the motivation for and effects of SSC implementation amongst audit firms, the authors offer insights into the best practices related to subsequent change processes and audit quality.

Regarding human resource and labour relations management, academia focuses mainly on cities; however, rural areas are an integral part of China's economic structure. This study focuses on the movie projection industry in China's rural areas and explores how human resource practices (HRPs) are transformed and the labour process is reconstructed in digital transformation.

We adopt a case study of a rural movie projection company. The company's HRPs reconstructed the labour process of movie projection, and they have been promoted as national standards. Data were collected from in-depth interviews, files and observations.

Rural movie projection companies combine high-performance and paternalistic HRPs in the media industry's digital transformation. HRPs and digital technology jointly reconstruct the labour process. First, the HRPs direct labour process practices towards standardisation. Second, the digital supervision platform guides the control style from simple to technical, placing projectionists under pressure while increasing management efficiency. Third, rural movies made using digital technology have disenchanted rural residents. Accordingly, the conventional relationships between the “country and its citizens,” “individuals themselves,” and “models and individuals” have been removed, and a new relationship between “individuals themselves” is formed thanks to the novel HRPs.

This research plays a crucial role in exposing researchers to the labour process of rural movie projection, which is significant in China but often ignored by Western academia and advances the Chinese contextualisation of research on labour relations.

With production systems become more digitized, data-driven maintenance decisions can improve the performance of production systems. While manufacturers are introducing predictive maintenance and maintenance reporting to increase maintenance operation efficiency, operational data may also be used to improve maintenance management. Research on the value of data-driven decision support to foster increased internal integration of maintenance with related functions is less explored. This paper explores the potential for further development of solutions for cross-functional responsibilities that maintenance shares with production and logistics through data-driven approaches.

Fifteen maintenance experts were interviewed in semi-structured interviews. The interview questions were derived based on topics identified through a structured literature analysis of 126 papers.

The main findings show that data-driven decision-making can support maintenance, asset, production and material planning to coordinate and collaborate on cross-functional responsibilities. While solutions for maintenance planning and scheduling have been explored for various operational conditions, collaborative solutions for maintenance, production and logistics offer the potential for further development. Enablers for data-driven collaboration are the internal synchronization and central definition of goals, harmonization of information systems and information visualization for decision-making.

This paper outlines future research directions for data-driven decision-making in maintenance management as well as the practical requirements for implementation.

In the last 3 decades, organization-wide programs and practices based on the Total Quality Management (TQM) philosophy have become central to continuous improvement (CI) strategy in both public and private enterprises. However, there is paradoxical evidence of TQM-firm performance linkage in non-Japanese contexts. This study presents a meta-analysis of empirical research on TQM-firm performance linkage and investigates the moderating influence of national cultural (NC) values on this relationship.

Meta-analytical procedures are adopted to analyse 364 effects accumulated from 135 independent samples across 31 nations, for 30,015 firm observations. Additionally, weighted least square (WLS) meta-regression is used to test the moderation effects of four NC dimensions based on the Global Leadership and Organizational Behavior Effectiveness (GLOBE) model.

The meta-analysis results reveal that the strengths of the association varied across five soft and hard TQM dimensions and three firm performance dimensions Meta-regression indicate that the effectiveness of the TQM program is high in cultures which reward collectivist behaviours, equity of power distribution and avoidance of ambiguity in rules/structures.

The study contributes to international operational management theory on cultural influences on the effectiveness of operations strategies and decisions.

The aim of this study is to undertake a systematic analysis of the supply chain literature to uncover the changes and patterns of international cooperation in the context of the COVID-19 pandemic.

In this study, the information on supply chain-related publications in the Web of Science (WOS) database is analyzed using statistical techniques and visual approaches. The focus is on the five countries with the highest number of supply chain publications, accounting for approximately 70% of global publications. This in-depth analysis aims to provide a clearer understanding of the cooperation patterns and their impact on the supply chain during the COVID-19 pandemic.

The results of the study reveal that the growth rate of international cooperation in supply chain research during the COVID-19 pandemic is higher compared to the 5-year and 10-year periods before the pandemic. This suggests that the pandemic has not hindered international cooperation in the field, but instead has increased collaboration. In terms of international cooperation patterns, the findings indicate that China and the USA have a strong partnership, with China being the largest partner for the USA and vice versa. The UK's largest partner is China, India's largest partner is the UK and Italy's largest partner is also the UK. This implies that trade, rather than the pandemic, is a determining factor in supply chain research.

This study examines the patterns of international cooperation in supply chain research during the COVID-19 pandemic, providing insights into the changes and mechanisms of international cooperation in this field. Moreover, the results of this study may offer practical benefits for supply chain operators and managers. By providing a deeper understanding of the international cooperation patterns in the field, this research could contribute to the recovery and growth of the global supply chain.

This study's analysis of the impact of crisis events, such as the COVID-19 pandemic, on international cooperation in supply chain research contributes to the theoretical development of the field. Additionally, by examining how academia responds to emergencies, it provides valuable insights for operations and supply chain managers in their pursuit of more effective supply chain management.

This study provides a preliminary examination of the international cooperation patterns of supply chain research in the context of the COVID-19 pandemic, representing a novel and early contribution to the existing literature, helping to expand upon current understanding in the field and provide a more comprehensive perspective. Furthermore, this study offers a practical analysis strategy for future supply chain research, fostering progress and growth in the field.

Small- and medium-sized enterprises (SMEs) within the construction sector are highly vulnerable to disruptions caused by political and economic decisions or even pandemics. This study evaluated the current operations of selected SMEs providing engineering design and consultancy services against Toyota Production System (TPS) lean tool. The purpose is to juxtapose SME operations and processes with TPS to ascertain the level of their operations conformity to the established TPS lean thinking tool.

This study used a qualitative data collection and analysis approach to evaluate the current processes of participating SMEs against Liker's 14 management principles of TPS. The data collected were analysed using thematic analysis to identify patterns and themes that emerged from the qualitative data.

The analysis revealed that focus on short-term goals, immediate profit and duplication of effort resulting from insufficient collaboration is currently creating waste in participating SMEs' operations. Hence, the implementation of TPS was recommended as a lean tool and a framework based on TPS lean tool was developed for improving the operations of SMEs.

The study is limited to SMEs operating only as consultants providing project planning design within the construction industry. Data collection is limited to qualitative even though observations would improve the outcome of the study.

The study advances contemporary issues in promoting lean implementation in construction sector and developed an improved framework based on the TPS to enhance the performance of SME construction businesses.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

Process orientation is important for improving organizational performance. The process view is considered a key enabler of digital transformation, and thus management control systems (MCS) are expected to incorporate this view. However, the existing body of knowledge is fragmented, as different process approaches are often considered independently following a reductionist view of control practices. This paper aims to provide recommendations for further research as well as guidance for practice by a systematic review of the state of research of MC for process orientation. It is based on both a comprehensive view to MC using an MCS package approach and a comprehensive view of process orientation.

A systematic literature review addressing major types of process orientation approaches was performed by applying the comprehensive MC framework of Malmi and Brown. The results were synthesized and propositions were developed.

All components of the MC framework, as well as MCS packages, are highly relevant for process orientation. Propositions regarding configurations of MC for process orientation show directions for future research. However, comprehensive considerations of packages and of individual components, especially cultural controls, remain scarce in the literature.

To the best of the authors‘ knowledge, this paper is the first of its kind to provide a comprehensive, structured overview of MC for process orientation, applying a nonreductionist view, based on an MCS Package approach, and consolidating the so far fragmented view of different process approaches.

Platform-based enterprises, as micro-entities in the platform economy, have the potential to effectively promote the low-carbon development of both supply and demand sides in the supply chain. Therefore, this paper aims to provide a multi-criteria decision-making method in a probabilistic hesitant fuzzy environment to assist platform-type companies in selecting cooperative suppliers for carbon reduction in green supply chains.

This paper combines the advantages of probabilistic hesitant fuzzy sets (PHFS) to address uncertainty issues and proposes an improved multi-criteria decision-making method called PHFS-DNMEREC-MABAC for aiding platform-based enterprises in selecting carbon emission reduction collaboration suppliers in green supply chains. Within this decision-making method, we enhance the standardization process of both the DNMEREC and MABAC methods by directly standardizing probabilistic hesitant fuzzy elements. Additionally, a probability splitting algorithm is introduced to handle probabilistic hesitant fuzzy elements of varying lengths, mitigating information bias that traditional approaches tend to introduce when adding values based on risk preferences.

In this paper, we apply the proposed method to a case study involving the selection of carbon emission reduction collaboration suppliers for Tmall Mart and compare it with the latest existing decision-making methods. The results demonstrate the applicability of the proposed method and the effectiveness of the introduced probability splitting algorithm in avoiding information bias.

Firstly, this paper proposes a new multi-criteria decision making method for aiding platform-based enterprises in selecting carbon emission reduction collaboration suppliers in green supply chains. Secondly, in this method, we provided a new standard method to process probability hesitant fuzzy decision making information. Finally, the probability splitting algorithm was introduced to avoid information bias in the process of dealing with inconsistent lengths of probabilistic hesitant fuzzy elements.