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This work examines a repairable machining system’s reliability by considering multiple failure scenarios, including individual component failures, hardware and software malfunctions, failures resulting from shared causes and failures caused by human error. When a system is susceptible to several modes of failure, the primary goal is to forecast availability and other reliability metrics as well as to calculate the expected profit of the repairable machining system.

The process of recovering after a system failure involves inspecting the system and fixing any malfunctions that may have occurred. The repair procedures for all kinds of faults are taken to follow a general distribution to represent real-time circumstances. We develop a non-Markovian stochastic model representing different system states that reveal working, failed, degraded, repair and delayed repair states. Laplace transformation and the supplementary variable technique are used to assess the transient states of the system.

Analytical expressions for system performance indices such as availability, reliability and cost-benefit analysis are derived. The transient probabilities when the system experiences in different states such as failed, degraded and delayed states are computed. The results obtained are validated using Mathematica software by performing a numerical illustration on setting default values of unknown parameters. This ensures the accuracy and reliability indices of the analytical predictions.

By methodically examining the system in its several states, we will be able to spot possible problems and offer efficient fixes for recovery. The system administrators would check to see if a minor or major repair is needed, or if a replacement is occasionally taken into consideration to prevent recurring repairs.

The primary learning objectives/outcome of case discussion is to apply design thinking principles to design innovative and socially responsible strategies that promote financial sustainability for organizations serving unique societal needs. The secondary learning objectives/outcome of case discussion is to gain a deeper appreciation for the potential social impact of their innovative ideas and understand the complexities and ethical considerations in social entrepreneurship, especially when working with individuals with special needs.

The case study describes the challenge facing Anil Kumar Kundra, the founder and trustee of Autism Ashram and Autism Guardian Village in Hyderabad and Gujarat, an organization that provides shelter and care for individuals with autism and residential facilities for their parents. Autistic individuals often lack social skills and may face challenges in reading, writing and communicating. In addition, they may experience behavioral issues, making it difficult for them to obtain employment or run their own ventures, resulting in a lifetime financial dependency on their guardians. In August 2023, Kundra, in pursuit of sustainability, aims to empower autistic individuals in the ashram to attain financial independence. He envisions Autism Ashrama as a self-sustaining entity, no longer dependent on contributions from parents. The dilemma facing Kundra is the need to identify innovative ideas that will enable these autistic individuals to contribute to revenue generation. The challenges faced by autistic individuals in their day-to-day lives make Kundra’s decision-making complex. While he acknowledges the challenge, he firmly believes that a handful of transformative ideas can bring about a revolutionary shift in the ecosystem for autistic individuals, rendering this business model truly sustainable. The case study invites students to help Kundra identify innovative ideas using design idea techniques, such as the Stanford d.school model.

This take-home assignment is suitable for both undergraduate and postgraduate students and is designed to explore the integration of sustainable business practices and design thinking in a real-world context.

Teaching notes are available for educators only.

CSS 7: Management science.

This study aims to provide a more complete picture of blockchain development by combining numerous methodologies with diverse data sources, such as academic papers and news articles. This study displays the developmental status of each subject based on the interrelationships of each topic cluster by analyzing high-frequency keywords extracted from the collected data. Moreover, applying above methodologies will help understanding top research topics, authors, venues, institutes and countries. The differences of blockchain research and new are identified.

To identify and find blockchain development linkages, researchers have used search terms such as co-occurrence, bibliographic coupling, co-citation and co-authorship to help us understand the top research topics, authors, venues, institutes and countries. This study also used text mining analysis to identify blockchain articles' primary concepts and semantic structures.

The findings show the fundamental topics based on each topic cluster's links. While “technology”, “transaction”, “privacy and security”, “environment” and “consensus” were most strongly associated with blockchain in research, “platform”, “big data and cloud”, “network”, “healthcare and business” and “authentication” were closely tied to blockchain news. This article classifies blockchain principles into five patterns: hardware and infrastructure, data, networking, applications and consensus. These statistics helped the authors comprehend the top research topics, authors, venues, publication institutes and countries.

Since Web of Science (WoS) and LexisNexis Academic data are used, the study has few sources. Others advise merging foreign datasets. WoS is one of the world's largest and most-used databases for assessing scientific papers.

This study has several uses and benefits. First, key concept discoveries can help academics understand blockchain research trends so they can prioritize research initiatives. Second, bibliographic coupling links academic papers on blockchain. It helps information seekers search and classify the material. Co-citation analysis results can help researchers identify potential partners and leaders in their field. The network's key organizations or countries should be proactive in discovering, proposing and creating new relationships with other organizations or countries, especially those from the journal network's border, to make the overall network more integrated and linked. Prominent members help recruit new authors to organizations or countries and link them to the co-authorship network. This study also used concept-linking analysis to identify blockchain articles' primary concepts and semantic structures. This may lead to new authors developing research ideas or subjects in primary disciplines of inquiry.

The aim of this study is to offer valuable insights to businesses and facilitate better understanding on transformer-based models (TBMs), which are among the widely employed generative artificial intelligence (GAI) models, garnering substantial attention due to their ability to process and generate complex data.

Existing studies on TBMs tend to be limited in scope, either focusing on specific fields or being highly technical. To bridge this gap, this study conducts robust bibliometric analysis to explore the trends across journals, authors, affiliations, countries and research trajectories using science mapping techniques – co-citation, co-words and strategic diagram analysis.

Identified research gaps encompass the evolution of new closed and open-source TBMs; limited exploration across industries like education and disciplines like marketing; a lack of in-depth exploration on TBMs' adoption in the health sector; scarcity of research on TBMs' ethical considerations and potential TBMs' performance research in diverse applications, like image processing.

The study offers an updated TBMs landscape and proposes a theoretical framework for TBMs' adoption in organizations. Implications for managers and researchers along with suggested research questions to guide future investigations are provided.