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Earned value management systems (EVMS), also called integrated project and program management systems, have been greatly examined in the literature, which has typically focused on their technical aspects rather than social. This study aims to hypothesize that improving both the technical maturity of EVMS and the social environment elements of EVMS applications together will significantly impact project performance outcomes. For the first time, empirical evidence supports a strong relationship between EVMS maturity and environment.

Data was collected from 35 projects through four workshops, attended by 31 industry practitioners with an average of 19 years of EVMS experience. These experts, representing 23 organizations, provided over 2,800 data points on sociotechnical integration and performance outcomes, covering projects totaling $21.8 billion. Statistical analyses were performed to derive findings on the impact of technical maturity and social environment on project success.

The results show statistically significant differences in cost growth, compliance, meeting project objectives and business drivers and customer satisfaction, between projects with high EVMS maturity and environment and projects with poor EVMS maturity and environment. Moreover, the technical and social dimensions were found to be significantly correlated.

Key contributions include a novel and tested performance-driven framework to support integrated project management using EVMS. The adoption of this detailed assessment framework by government and industry is driving a paradigm shift in project management of some of the largest and most complex projects in the U.S.; specifically transitioning from a project assessment based upon a binary approach for EVMS technical maturity (i.e. compliant/noncompliant to standards) to a wide-ranging scale (i.e. 0–1,000) across two dimensions.

This study aims to explore the managerial conception of the determinants and barriers of sustainability integration into management control systems (MCS) of manufacturing companies in Sri Lanka. Although existing literature has explored the factors that influence the adoption of specific management controls to handle environmental and social issues, the role of management conception has been underrepresented. Specifically, literature is scarce in identifying contextual and organisational factors that influence corporates beyond mere adoption of controls but to integrate with regular controls, especially in developing countries such as Sri Lanka.

A multiple case study approach has been used to identify the management conception of barriers and enablers for sustainability control integration. The analysis is conducted based on a theoretical framework extending the work of Gond et al. (2012) and George et al. (2016). To obtain an in-depth and multifaceted view, semi-structured interviews were conducted with managers in charge of different functional departments of five manufacturing companies.

The findings identified managers’ perceived factors, such as environmental impact, stakeholder pressure (customer, competitor and regulatory authorities) and top management commitment, showing a clear difference between strongly and weakly integrated companies. Contrary to the literature, domestic regulatory pressure and multinational ownership do not sufficiently drive MCS sustainability integration.

The findings have implications for managers and practitioners to anticipate the potential barriers and determinants of sustainability integration and provide guidance to take proper measures to deal with them when designing and implementing their MCS.

The study adds value to the literature by presenting a theoretical framework based on the triangulation of different theories to recognise the significance of management idea in sustainable integration. Furthermore, because sustainable integration of MCS is a novel idea, this research is one of the earlier attempts to highlight problems from the perspective of developing countries.

The aim of this paper is to explore the implementation of an integrated lean and ISO 14001 approach in meat industry for environmental performance and examine a proposed conceptual framework by capturing insights from lean and ISO 14001 experts in New Zealand (NZ).

Semi-structured interviews have been conducted with a group of consultants (lean and ISO 14001) to evaluate the suitability of an integrated lean and ISO 14001 approach in the meat industry for environmental performance. A conceptual framework from literature has guided this study leading to its further development based on the empirical evidence collected.

Findings have illustrated a synergistic positive impact of lean and ISO 14001 implementation as an integrated approach for sustaining environmental performance in the meat industry. A joint implementation program provides more clarity in aligning ISO 14001 operational procedures with lean tools and techniques for an enhanced environmental performance outcome.

The application of an integrated lean and ISO 14001 framework is proposed in this paper, which can help industry practitioners and academia in developing a joint implementation strategy and conducting future research.

To the best of the author’s knowledge, this study is the first to assess the effective implementation of lean and ISO 14001 as an integrated approach in the NZ meat industry.

Generative AI and more specifically ChatGPT has brought a revolution in the lives  of people by providing them with required knowledge that it has learnt from an exponentially large knowledge base. In this viewpoint, we are initiating the debate and offer the first step towards Generative AI based knowledge management systems in organizations.

This study is a viewpoint and develops a conceptual foundation using existing literature on how ChatGPT can enhance the KM capability based on Nonaka’s SECI model. It further supports the concept by collecting data from a public sector univesity in Hong Kong to strenghten our argument of ChatGPT mediated knowledge management system.

We posit that all four processes, that is Socialization, Externalization, Combination and Internalization can significantly improve when integrated with ChatGPT. ChatGPT users are, in general, satisfied with the use of ChatGPT being capable of facilitating knowledge generation and flow in organizations.

The study provides a conceptual foundation to further the knowledge on how ChatGPT can be integrated within organizations to enhance the knowledge management capability of organizations. Further, it develops an understanding on how managers and executives can use ChatGPT for effective knowledge management through improving the four processes of Nonaka’s SECI model.

This is one of the earliest studies on the linkage of knowledge management with ChatGPT and lays a foundation for ChatGPT mediated knowledge management system in organizations.

This study aims to propose a longitudinal analysis of motivations for Integrated Reporting (IR) adoption, internal changes, the benefits of IR implementation and compliance challenges.

The authors analyse a longitudinal case study of an Italian-listed company (Eni) participating in the IR-Pilot Programme (PP) and covering 10 years of IR adoption. The analysis was based on a mixed-method approach that included semi-structured interviews, content analysis of annual reports and triangulation with other data sources. Results are discussed regarding institutional theory, legitimacy theory and diffusion of innovation theory.

The study suggests that motivations for adopting IR change over time and participation in the IR-PP helps Eni acquire a comprehensive and substantial integrated view of value creation over time, makes integrated culture a key factor for strategic business sustainability and confirms the readiness of early adopters to comply with the non-financial Directive (NFD).

This study, among the few longitudinal case studies, provides organisations, regulators and academics with insights into the motivations driving the successful adoption and implementation of IR and the NFD. The results may help companies consider one of the tools currently deemed to bring sustainability into action and participation in pilot groups.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

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.

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.

The present study shows that the implementation and development of enterprise resource planning (ERP) systems as a technological innovation provide a competitive advantage that helps to improve the functionality of business intelligence (BI) systems in the digital transformation of manufacturing companies, in addition to improving overall firm performance.

The research uses the structural equation approach based on PLS-SEM technique with a sample of 120 firms in the manufacturing industry in Coahuila, Mexico.

The paper provides empirical insights into how the interaction of ERP systems and innovation significantly affects the functionality of BI Systems and has a substantial effect on overall firm performance.

Empirical evidence of how advanced digital management systems (ERP and BI) impact digitalization processes in organizations by improving performance is still scarce.

This study aims to develop a conceptual framework for the role of chief financial officer (CFO) in an ever-changing environment. As previous research focused on responding to specific crises, there have been theoretical and practical gaps in the role of CFO. The study's goal is to fill a critical gap by developing a comprehensive and integrated set of roles to assist the CFO in a constantly changing environment.

Using a grounded theory approach, semi-structured interviews and observations were conducted with 21 CFOs from various industries in Thailand, including foreign multinational corporations and domestic companies with international operations. CFOs were asked how they frame their roles in the face of an ever-changing environment and how they prepare for the future.

The iCFO model is developed, which identifies the critical “core” roles of the CFO in securing the business foundation, as well as the “future opportunities” roles that function as growth engines for long-term business strength. The research delves into the importance of integrity, ethical mindset and corporate governance in the role of the CFO. The iCFO model is designed to help guide future research and provide practical applications for CFOs in both domestic and international contexts. The term “core” refers to the CFO’s primary responsibilities, which include driving profitability, managing risks and optimizing business performance. The “future opportunities” component focuses on the roles that CFOs can play in strengthening the future of business by optimizing investment efficiency, driving digital transformation and being the CEO’s business partner. The findings also emphasized “integrity,” which must encompass all decisions, actions or recommendations made by the CFO.

The study offers unique perspectives on an emerging economy, providing new insights. Through interviews with 21 CFOs, it contributes empirical evidence on the development of roles in accounting and finance, emphasizing good governance practices. The findings highlight the integrated role of the CFO and their self-reflection on their value within the company. Significantly, the study's implications are relevant and applicable to a global audience, particularly in developing economies that prioritize growth. Future studies could incorporate integrated thinking into the iCFO model to address social, environmental and economic factors, making it more universally relevant. Additionally, exploring the adoption of the chief value officer context in developing markets could enable CFOs to expand their focus beyond financial metrics, embracing a comprehensive approach to value creation. By integrating these concepts into the iCFO model, CFOs can effectively drive sustainable and impactful business outcomes on a global scale.