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The paper follows Jason Cope's (2011) vision of a holistic perspective on the failure-based learning process. By analyzing the research since Cope's first attempt, which is often fragmentary in nature, and providing novel empirical insights, the paper aims to draw a new comprehensive picture of all five phases of entrepreneurial learning and their interplay.

The study features an interpretative phenomenological analysis of in-depth interviews with 18 failed entrepreneurs. Findings are presented and discussed in line with experiential learning theory and Cope's conceptual framework of five interrelated learning timeframes spanning from the descent into failure until re-emergence.

The study reveals different patterns of how entrepreneurs experience failure, ranging from abrupt to gradual descent paths, different management and coping behaviors, and varying learning effects depending on the new professional setting (entrepreneurial vs non-entrepreneurial). Analyzing the entrepreneurs' experiences throughout the process shows different paths and connections between individual phases. Findings indicate that the learning timeframes may overlap, appear in different orders, loop, or (partly) stay absent, indicating that the individual learning process is even more dynamic and heterogeneous than hitherto known.

The paper contributes to the field of entrepreneurial learning from failure, advancing Cope's seminal work on the learning process and -contents by providing novel empirical insights and discussing them in the light of recent scientific findings. Since entrepreneurial learning from failure is a complex and dynamic process, using a holistic lens in the analysis contributes to a better understanding of this phenomenon as an integrated whole.

Total productive maintenance consists of strategies and procedures that aim to guarantee the entire functioning of machines in a production process so that production is not interrupted and no loss of quality in the final product occurs. Planned maintenance is one of the eight pillars of total productive maintenance, a set of tools considered essential to ensure equipment reliability and availability, reduce unplanned stoppage and increase productivity. This study aims to analyze the influence of statistical reliability on the performance of such a pillar.

In this study, we utilized a multi-method approach to rigorously examine the impact of statistical reliability on the planned maintenance pillar within total productive maintenance. Our methodology combined a detailed statistical analysis of maintenance data with advanced reliability modeling, specifically employing Weibull distribution to analyze failure patterns. Additionally, we integrated qualitative insights gathered through semi-structured interviews with the maintenance team, enhancing the depth of our analysis. The case study, conducted in a fertilizer granulation plant, focused on a critical failure in the granulator pillow block bearing, providing a comprehensive perspective on the practical application of statistical reliability within total productive maintenance; and not presupposing statistical reliability is the solution over more effective methods for the case.

Our findings reveal that the integration of statistical reliability within the planned maintenance pillar significantly enhances predictive maintenance capabilities, leading to more accurate forecasts of equipment failure modes. The Weibull analysis of the granulator pillow block bearing indicated a mean time between failures of 191.3 days, providing support for optimizing maintenance schedules. Moreover, the qualitative insights from the maintenance team highlighted the operational benefits of our approach, such as improved resource allocation and the need for specialized training. These results demonstrate the practical impact of statistical reliability in preventing unplanned downtimes and informing strategic decisions in maintenance planning, thereby emphasizing the importance of your work in the field.

In terms of the originality and practicality of this study, we emphasize the significant findings that underscore the positive influence of using statistical reliability in conjunction with the planned maintenance pillar. This approach can be instrumental in designing and enhancing component preventive maintenance plans. Furthermore, it can effectively manage equipment failure modes and monitor their useful life, providing valuable insights for professionals in total productive maintenance.

This study aims to endeavor to shed light on the underlying causal mechanisms behind the failure of startups by examining the failure process in such organizations. To achieve this goal, the study conducted a comprehensive review of the literature on the definition of failure and its various dimensions, resulting in the compilation of a comprehensive list of causes of startup failure. Subsequently, the failure process was analyzed using a behavioral strategy approach that encompasses rationality, plasticity and shaping, as well as the growth approach of startups based on dialectic, teleology and evolution theories.

The proposed research methodology was a case study using process tracing, with the sample being a failed platform in the ride-hailing technology sector. The causal mechanism was further explicated through the combined application of the behavioral strategy approach and interpretive structural modeling analysis.

The findings of the study suggest that the failure of startups is a result of interlinked causes and effects, and growth in these organizations is driven by dialectic, teleology and evolution theories.

The outcomes of the research can assist startups in formulating an effective strategy to deliver the right value proposition to the market, thereby reducing the chances of failure.

Although it is commonly agreed that prescriptive analytics can benefit organizations by enabling better decision-making, the deployment of prescriptive analytics tools can be challenging. Previous studies have primarily focused on methodological issues rather than the organizational deployment of analytics. However, successful deployment is key to achieving the intended benefits of prescriptive analytics tools. Therefore, this study aims to identify the enablers of successful deployment of prescriptive analytics.

The authors examine the enablers for the successful deployment of prescriptive analytics through five organizational case studies. To provide a comprehensive view of the deployment process, each case includes interviews with users, managers and top management.

The findings suggest the key enablers for successful analytics deployment are strong leadership and management support, sufficient resources, user participation in development and a common dialogue between users, managers and top management. However, contrary to the existing literature, the authors found little evidence of external pressures to develop and deploy analytics. Importantly, the success of deployment in each case was related to the similarity with which different actors within the organization viewed the deployment process. Furthermore, end users tended to highlight user participation, skills and training, whereas managers and top management placed greater emphasis on the importance of organizational changes.

The results will help practitioners ensure that key enablers are in place to increase the likelihood of the successful deployment of prescriptive analytics.

The present study undertakes an extensive review of the causes of service failures in artificial intelligence (AI) technology literature.

A hybrid review has been employed which includes descriptive analysis, and bibliometric analysis with content analysis of the literature approach to synthesizing existing research on a certain topic. The study has followed the SPAR-4-SLR protocol as outlined by Paul et al. (2021). The search period encompasses the progression of service failure in AI from 2001 to 2023.

From identified theories, theoretical implications are derived, and thematic maps direct future research on topics such as data mining, smart factories, and among others. The key themes are being proposed incorporates technological elements, ethical deliberations, and cooperative endeavours.

This research study makes a valuable contribution to understanding and reducing service defects in AI by providing insights that can inform future investigations and practical implementations. Six key future research directions are derived from the thematic and cluster discussions presented in the content analysis.

Capitalism is under siege (Porter & Kramer, 2011), and business schools are under fire (Amann et al., 2013). So, management and leadership education in higher education institutions should be reinvented under the more challenging era of capitalism. How then can business schools cope with these challenges and contribute to global endeavor for making sustainable capitalism? In this context, there is thus reason for the following three core concerns that new understanding of management and leadership education is required. First, shortcomings of contemporary capitalism lead to failures of responsible management. Second, ethical failure of management leadership is a pressing issue. Third, academic responsibility under the new capitalism remains unexamined. Based on these three core concerns, we seek to generate inclusive insights into the educational embeddedness of management and leadership members and the consequences of such embeddedness on managerial processes, structures, and outcomes under contemporary capitalism.

Against the backdrop of management, planning, temporary organizations, Shannon–Weaver theory of communication and evaluation theories, the purpose of this research paper is to examine the relative importance of specific project management tasks in the various phases of system delivery projects in distinguishing successful and unsuccessful projects.

A survey method was used (N = 3,129) to collect data from the customers of a major systems delivery project management company operating in the facilities management industry. Logistic regression was used to analyze the capability and relative importance of the tasks in discriminating successful and unsuccessful projects.

The results of the paper indicate that three out four installation tasks were among the top three in their ability to differentiate the successful and unsuccessful systems delivery project. Especially critical tasks were “Meeting milestones” and “Allocation of appropriate resources” so that the project could be completed on-time. Relatively less important tasks were “Advice and suggestions regarding the development of specifications for the project” and “Proposal to meet the intent of the company’s specifications” in the proposal phase of the project, and “Resolving warranty issues as defined by the warranty process” in the commissioning phase.

Previous research has assessed the importance of the various project management phases. This research examines the capability of the more minutiae tasks to distinguish the successful and unsuccessful projects in the various phases of systems delivery projects, i.e. proposal, installation and commissioning.

After reading the case and answering the case assignments, students will be able to understand and explain the challenges and opportunities for engineering, procurement and construction (EPC) contractors and their subcontractors; understand and critically analyse the advantages and disadvantages of insourcing and outsourcing of engineering, procurement and construction in EPC projects; determine which situations merit insourcing or outsourcing within each of engineering, procurement and construction in EPC projects; understand and identify the competencies and qualifications that a subcontractor must possess if any EPC activity is outsourced to them; and develop a decision-making framework to determine which EPC activities must be kept in-house or outsourced in EPC projects.

In mid-March 2021, PetroSahand International Group, a leading EPC contractor specializing in the oil, gas and petrochemicals industries in Iran, encountered significant challenges with its subcontractors in engineering and construction. These issues resulted in widespread repercussions for the company, including project delays and mounting debts. At the peak of these crises, PetroSahand’s senior management embarked on a thorough examination of whether to insource or outsource various aspects of their operations, such as engineering, procurement and construction. Their objective was twofold: to prevent similar setbacks in future projects and to navigate existing projects with minimal disruption to the company’s reputation. To address this critical dilemma, PetroSahand enlisted the expertise of a consulting team from Sharif University of Technology. Comprising esteemed professors, graduates and students from one of Iran’s most respected institutions, this team undertook an exhaustive analysis of the insourcing versus outsourcing debate across EPC domains. Subsequently, they presented their comprehensive findings, thereby confronting PetroSahand’s senior management with a pivotal choice regarding the optimal approach for each activity.

The audience of this work is undergraduate and graduate students who are enrolled in project management courses, both fundamentals and advanced. In addition, this case helps senior managers of EPC contractors gain a deeper and more comprehensive understanding of insourcing or outsourcing different project activities.

Teaching notes are available for educators only.

CSS 7: Management science.

The healthcare sector relies on knowledge management systems to improve knowledge flows and effectively capture, leverage and share knowledge with several organizational stakeholders. However, knowledge as a resource represents a social construct that involves additional managerial complexities and challenges, including undesirable knowledge behaviours. The aim of the current study is to provide insight on how knowledge management systems, knowledge hoarding, knowledge hiding and task conflict shape the quality of care provided by hospitals. We propose and test an original revealing model.

We follow a quantitative approach to address the structural relationship between variables using a combination of factor analysis and multiple regression analysis. The model is tested adopting a structural equation modelling approach and using survey data conducted to 318 healthcare professionals working in Portuguese hospitals.

The main findings suggest that knowledge hiding is positively related to task conflict in hospitals, and task conflict negatively influences quality of care. Knowledge management systems directly and indirectly (via knowledge hoarding) promote quality of care. Moreover, knowledge management systems also mitigate the negative influence of task conflict over quality of care. We propose a final corollary on the relevant role of HRM as the backstage for the model.

Our research offers a novel insight into an overlap of organizational behaviour and healthcare management research. It provides an original framework on knowledge management systems, counterproductive knowledge behaviours and task conflict in hospital settings.

Our research offers a novel insight into an overlap of organizational behaviour and healthcare management research. It provides an original framework on knowledge management systems, counterproductive knowledge behaviours and task conflict in hospital settings.

Healthcare organizations have been facing challenges due to high costs and low efficiency in health services. The growth of costs and losses caused by avoidable mistakes lead to the search for solutions, and Health Lean Management appears as a potential solution to help in solving service quality problems, as well as reducing risks. This study aims to analyse the state of the art in the literature centred on the Lean approach in the context of risk management in healthcare organizations, and to identify new research opportunities, highlighting possible lines of future research.

Following a systematic literature review approach, 51 papers were considered relevant for this research, and reviewed to explore the development of literature in this area.

Based on the results, five main research streams were identified: (1) risk management oriented towards patient safety; (2) risk management oriented towards employee safety; (3) importance of attitudes and behaviours in risk reduction projects; (4) Lean tools used in healthcare risk management and (5) Integration of approaches. Moreover, several shortcomings were identified in literature.

Identified shortcomings represent significant opportunities for further research development.