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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.

By adopting the “hard” and “soft” project management (PM) approaches from the PM-literature, this paper aims to problematize the expected role of client organizations in driving innovation in the transport infrastructure sector.

Addressing a large public client in Sweden, a case study design was initially applied to provide in-depth insights and perspectives of client project managers’ views and experiences of managing projects expected to drive innovation. In this paper, the concepts of “hard” and “soft” are used to discuss empirical findings on challenges associated with adopting a PM-approach for driving innovation in projects. The empirical material consists of interview data, complemented with observations and archival data.

Findings reveal challenges associated with combining hard and soft approaches, frequently demonstrating difficulties in balancing short-term project expectations with the promotion of innovation. In line with the literature, project managers note that there is a need for soft approaches to promote development and drive innovation. Yet, findings reflect a situation in which operational success criteria predominate, whereas soft approaches are not sufficiently used to create the grounds required for fostering innovation.

Insights are provided into how PM-approaches may impact construction innovation in the infrastructure sector, demonstrating a need for further research on the challenges and implications of applying and combining hard and soft PM-approaches.

While existing research has explored the association between supervisor support and turnover intention among construction workers, there is a notable gap in the literature concerning the potential mediating role of work engagement in elucidating this relationship, warranting further investigation. The paper, hence, aims to examine the mediating role of work engagement in the relationship between supervisor support and turnover intention among construction workers.

Based on the quantitative research method, the hypothesis was tested. The data were collected from 144 construction professionals using a structured questionnaire. Observed variables were tested using confirmatory factor analysis, and the mediating role relationship was validated using hierarchical regression.

The outcome of this study shows a significant positive impact of work engagement and supervisor support on employee turnover intention. The study further showed that work engagement plays a mediating role in the connection between supervisory support and the intention to turnover and improve project and business performance. Turnover intention, on the other hand, negatively affects project and organizational performance.

By enhancing employee work engagement and perceptions of supervisor support, the findings of this study may aid construction organizations in making better judgments regarding the likelihood of employee turnover. The effectiveness of the project and the organization will likely be greatly impacted.

The results of this study provide supporting evidence and advance efforts at reducing employee turnover intention through work engagement and supervisor support in improving project and organizational performance.

This paper aims to elucidate responsible leadership as a construct with strong moral and ethical underpinnings, as well as a focus on multiple stakeholders and the triple bottom line. This paper also highlights the interdependence of the economic, social and environmental dimensions of a business to achieve corporate sustainability.

This conceptual paper is the outcome of analysing and synthesizing the findings of the literature review on three main constructs: responsible leadership, triple bottom line and corporate sustainability. This review enabled the development of logical associations among these constructs.

The literature revealed logical associations between responsible leadership, the triple bottom line and corporate sustainability. All three constructs embody the three dimensions of economic, social and environmental sustainability, which form the basis of the associations.

Responsible leadership, grounded in stakeholder theory, goes beyond the traditional dyadic leader–follower relationship to influence multiple stakeholders within and outside the organization and achieve positive outcomes for both the organization and society. Multiple levels of outcomes and higher levels of organizational performance for businesses are the hallmarks of responsible leadership.

This paper highlights the importance of responsible leadership and triple bottom-line performance for corporate sustainability. Responsible leadership has the potential to create significant impact on business and society, to achieve long-term corporate sustainability. A conceptual model of responsible leadership is also proposed to show the association between responsible leadership, the triple bottom line and corporate sustainability.

Specific teaching and learning objectives include to identify factors influencing market expansion decisions and recommend appropriate entry modes, understand factors in the international business environment that contribute to success or failure of international businesses in developing countries, evaluate strategies enabling international businesses to sustain market presence in developing countries and overcome local competition, analyze the concept of local responsiveness in international business operations and suggest strategies for internationalizing domestic companies from developing countries.

The McDonald’s case examines the challenges associated with market expansion by global brands. The case occurs during the early-globalization era in the 1990s. Barbados, a developing country, is the site for potential expansion. Prospective investors, the Winters, are desirous of establishing a McDonald’s in Barbados. They need to thoroughly analyze the previous experience of McDonald’s against the host country’s current international business environment, e.g. political, economic, cultural and competitive environment. This case analysis provides a framework for understanding the multifaceted reasons behind McDonald’s exit from Barbados, considering the complex interplay of political, economic, sociocultural, technological and legal factors in the international business environment. The case equips the instructor and students to explore the risks of international expansion, particularly in developing country markets. The case study on McDonald’s failure in Barbados highlights the need to thoroughly examine one’s market entry strategy and available information on the host market and be more locally responsive regarding tastes and preferences. The case study also presents essential lessons for firms and planners from developing countries. Local firms innovated and enhanced their operations in response to the threat from the entry of the global fast-food giant. Yet, they did not seek to internationalize once McDonald’s exited the Barbadian market. The case study, therefore, considers strategies firms from developing countries could utilize to penetrate markets from developed countries.

At the undergraduate level, the McDonald’s Barbados case can be used in international business classes to highlight risks in the international business environment and the need for a carefully planned and executed market entry strategy.

Teaching notes are available for educators only.

CSS5: International Business.

This study aims to understand the practices and rules of Sharia crowdfunding policies in Indonesia given the rapid growth of financial technology and the increasing importance of crowdfunding as a funding alternative for micro, small, and medium enterprises (MSMEs).

This study used qualitative methods, exploratory methods and literature studies for data collection. The focus is on understanding the regulatory environment and institutional framework that support Sharia crowdfunding in Indonesia.

Despite a specific law regulating Sharia crowdfunding, several authoritative institutions in Indonesia offer FinTech, crowdfunding and Sharia crowdfunding services. Some regulations have been issued, such as Bank Indonesia Regulation Number 19/12/PBI/2017 and Financial Services Authority (OJK) Regulation Number 37/POJK.04/2018, which was later amended to Number 57/POJK.04/2020. This study emphasizes the crucial role of OJK in providing security guarantees for implementing FinTech, including crowdfunding. At the same time, Sharia crowdfunding also follows fatwas issued by DSN-MUI.

This study describes Sharia crowdfunding policies in Indonesia and indicates that further research could delve deeper into specific cases and examine the impact of these policies on the growth and sustainability of Sharia crowdfunding.

This study underlines the need to enhance Sharia crowdfunding standards and to create rules that explicitly address this issue. This has implications for regulatory authorities, FinTech companies and MSMEs seeking to leverage Sharia crowdfunding.

This study suggests potential social implications, including a more inclusive financial system that complies with Islamic principles and supports MSMEs' growth.

This study is unique in its focus on Sharia crowdfunding policies in Indonesia, providing a comprehensive view of the regulatory landscape and existing institutional framework.

In the context of the journey toward digital transformation and the realization of a fully connected factory, concepts such as data science, artificial intelligence (AI), machine learning (ML) and even predictive models emerge as indispensable pillars. Given the relevance of these topics, the present study focused on the analysis of customer complaint data, employing ML techniques to anticipate complaint accountability. The primary objective was to enhance data accessibility, harnessing the potential of ML models to optimize the complaint handling process and thereby positively contribute to data-driven decision-making. This approach aimed not only to reduce the number of units to be analyzed and customer response time but also to underscore the pressing need for a paradigm shift in quality management. The application of AI techniques sought to enhance not only the efficiency of the complaint handling process and data accessibility but also to demonstrate how the integration of these innovative approaches could profoundly transform the way quality is conceived and managed within organizations.

To conduct this study, real customer complaint data from an automotive company was utilized. Our main objective was to highlight the importance of artificial intelligence (AI) techniques in the context of quality. To achieve this, we adopted a methodology consisting of 10 distinct phases: business analysis and understanding; project plan definition; sample definition; data exploration; data processing and pre-processing; feature selection; acquisition of predictive models; evaluation of the models; presentation of the results; and implementation. This methodology was adapted from data mining methodologies referenced in the literature, taking into account the specific reality of the company under study. This ensured that the obtained results were applicable and replicable across different fields, thereby strengthening the relevance and generalizability of our research findings.

The achieved results not only demonstrated the ability of ML models to predict complaint accountability with an accuracy of 64%, but also underscored the significance of the adopted approach within the context of Quality 4.0 (Q4.0). This study served as a proof of concept in complaint analysis, enabling process automation and the development of a guide applicable across various areas of the company. The successful integration of AI techniques and Q4.0 principles highlighted the pressing need to apply concepts of digitization and artificial intelligence in quality management. Furthermore, it emphasized the critical importance of data, its organization, analysis and availability in driving digital transformation and enhancing operational efficiency across all company domains. In summary, this work not only showcased the advancements achieved through ML application but also emphasized the pivotal role of data and digitization in the ongoing evolution of Quality 4.0.

This study presents a significant contribution by exploring complaint data within the organization, an area lacking investigation in real-world contexts, particularly focusing on practical applications. The development of standardized processes for data handling and the application of predictions for classification models not only demonstrated the viability of this approach but also provided a valuable proof of concept for the company. Most importantly, this work was designed to be replicable in other areas of the factory, serving as a fundamental basis for the company’s data scientists. Until then, limited data access and lack of automation in its treatment and analysis represented significant challenges. In the context of Quality 4.0, this study highlights not only the immediate advantages for decision-making and predicting complaint outcomes but also the long-term benefits, including clearer and standardized processes, data-driven decision-making and improved analysis time. Thus, this study not only underscores the importance of data and the application of AI techniques in the era of quality but also fills a knowledge gap by providing an innovative and replicable approach to complaint analysis within the organization. In terms of originality, this article stands out for addressing an underexplored area and providing a tangible and applicable solution for the company, highlighting the intrinsic value of aligning quality with AI and digitization.

Due to the complexity and diversity of megaprojects, the architectural programming process often involves multiple stakeholders, making decision-making difficult and susceptible to subjective factors. This study aims to propose an architectural programming methodology system (APMS) for megaprojects based on group decision-making model to enhance the accuracy and transparency of decision-making, and to facilitate participation and integration among stakeholders. This method allows multiple interest groups to participate in decision-making, gathers various perspectives and opinions, thereby improving the quality and efficiency of architectural programming and promoting the smooth implementation of projects.

This study first clarifies the decision-making subjects, decision objects, and decision methods of APMS based on group decision-making theory and value-based architectural programming methods. Furthermore, the entropy weight method and fuzzy TOPSIS method are employed as calculation methods to comprehensively evaluate decision alternatives and derive optimal decision conclusions. The workflow of APMS consists of four stages: preparation, information, decision, and evaluation, ensuring the scientific and systematic of the decision-making process.

This study conducted field research and empirical analysis on a practical megaproject of a comprehensive transport hub to verify the effectiveness of APMS. The results show that, in terms of both short-distance and long-distance transportation modes, the decision-making results of APMS are largely consistent with the preliminary programming outcomes of the project. However, regarding transfer modes, the APMS decision-making results revealed certain discrepancies between the project's current status and the preliminary programming.

APMS addresses the shortcomings in decision accuracy and stakeholder participation and integration in the current field of architectural programming. It not only enhances stakeholder participation and interaction but also considers various opinions and interests comprehensively. Additionally, APMS has significant potential in optimizing project performance, accelerating project processes, and reducing resource waste.

This paper aims to address the challenge raised in the literature regarding whether and how digitalization supports a servitized new product development (NPD) process, considering the customer’s involvement from the early stage of the process.

Pragmatic constructivism (PC) has been adopted for conceptualizing the NPD process as the construction of a new reality. PC is the method theory used for interpreting the field evidence drawn from a qualitative case study carried out at a multinational company operating in the semiconductor industry.

This study shows how digitalization supports the alignment to the overarching topoi of the company servitization strategy by enabling the integration and merging of different organizational topoi during the NPD process.

This study is confined to a single-case study and context.

The results of this study are relevant for managers involved in the stage-gate product development of manufacturing companies, informing them on how the use of digital tools enables or hinders the progression of product development projects.

This paper contributes to the servitization literature by offering field evidence that demonstrates the importance for manufacturing firms of acquiring customer feedback from an early NPD phase. Another contribution is related to the literature on the role of digitalization in NPD processes, describing how digital tools give support during the different phases of the NPD process.

This paper delves into the transformative impact of artificial intelligence (AI) across diverse sectors, notably project management. It examines the potential of AI to revolutionize project management processes within entrepreneurial ventures, where agility, efficiency and innovation reign supreme.

Through a comprehensive analysis, this study navigates the intersection of AI and entrepreneurial project management. It meticulously dissects the opportunities AI presents, the hurdles it introduces and the optimal strategies for harnessing its capabilities effectively. Drawing insights from complexity theory, a framework is crafted to delineate AI’s capacity to substitute human involvement, elucidating key considerations for transitioning to a digitally-driven paradigm in entrepreneurial project management.

The study underscores AI’s potential to augment project management processes significantly, particularly in fostering agility and innovation. However, challenges persist, necessitating adept navigation to maximize AI’s benefits. The framework delineates the extent to which AI can supplant human roles, offering crucial insights into the digital transformation of entrepreneurial project management.

Practitioners are equipped with valuable guidance on leveraging AI effectively, enhancing organizational agility and performance. Understanding the implications of AI adoption fosters informed decision-making in the realm of project management.

The integration of AI in entrepreneurial project management signifies broader societal shifts toward digitalization and automation. Insights from this study contribute to navigating these transformations, fostering greater resilience and adaptability in entrepreneurial endeavors.

This study offers a novel perspective on the intersection of AI and entrepreneurial project management, shedding light on unexplored terrain. By drawing on complexity theory, it advances a nuanced understanding of AI’s implications, paving the way for future research avenues in this dynamic field.