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There are two main objectives in this study. First, we aim to develop a set of constructs for health task management support (HTMS) features to evaluate which health-related tasks are supported by mobile health application (mHealth app) functions. Second, drawing on innovation resistance theory (IRT), we examine the impacts of the newly developed HTMS dimensions on perceived usefulness, alongside other barrier factors contributing to technology anxiety.

Using a mixed-method research design, this research seeks to develop new measurement scales that reflect how mHealth apps support older adults’ health-related needs based on interviews. Subsequently, data were collected from older adults and exploratory factor analysis was used to confirm the validity of the new scales. Partial least squares structural equation modeling (PLS-SEM) was used to analyze survey data from 602 older adults.

The PLS-SEM results indicated that medical management task support, dietary task support, and exercise task support were positively associated with perceived usefulness, while perceived complexity and dispositional resistance to change were identified as antecedents of technology anxiety. Perceived usefulness and technology anxiety were found to positively and negatively influence adoption intention, respectively.

This study enriches the information systems literature by developing a multidimensional construct that delineates how older adults’ health-related needs can be supported by features of mHealth apps. Drawing on IRT, we complement the existing literature on resistance to innovation by systematically examining the impact of five types of barriers on technology anxiety.

This research introduces an innovation strategy aimed at bolstering the reliability of a renewable energy resource, which is hybrid energy systems, through the application of a metaheuristic algorithm. The growing need for sustainable energy solutions underscores the importance of integrating various energy sources effectively. Concentrating on the intermittent characteristics of renewable sources, this study seeks to create a highly reliable hybrid energy system by combining photovoltaic (PV) and wind power.

To obtain efficient renewable energy resources, system designers aim to enhance the system’s reliability. Generally, for this purpose, the reliability redundancy allocation problem (RRAP) method is utilized. The authors have also introduced a new methodology, named Reliability Redundancy Allocation Problem with Component Mixing (RRAP-CM), for optimizing systems’ reliability. This method incorporates heterogeneous components to create a nonlinear mixed-integer mathematical model, classified as NP-hard problems. We employ specially crafted metaheuristic algorithms as optimization strategies to address these challenges and boost the overall system performance.

The study introduces six newly designed metaheuristic algorithms. Solve the optimization problem. When comparing results between the traditional RRAP method and the innovative RRAP-CM method, enhanced reliability is achieved through the blending of diverse components. The use of metaheuristic algorithms proves advantageous in identifying optimal configurations, ensuring resource efficiency and maximizing energy output in a hybrid energy system.

The study’s findings have significant social implications because they contribute to the renewable energy field. The proposed methodologies offer a flexible and reliable mechanism for enhancing the efficiency of hybrid energy systems. By addressing the intermittent nature of renewable sources, this research promotes the design of highly reliable sustainable energy solutions, potentially influencing global efforts towards a more environmentally friendly and reliable energy landscape.

The research provides practical insights by delivering a comprehensive analysis of a hybrid energy system incorporating both PV and wind components. Also, the use of metaheuristic algorithms aids in identifying optimal configurations, promoting resource efficiency and maximizing reliability. These practical insights contribute to advancing sustainable energy solutions and designing efficient, reliable hybrid energy systems.

This work is original as it combines the RRAP-CM methodology with six new robust metaheuristics, involving the integration of diverse components to enhance system reliability. The formulation of a nonlinear mixed-integer mathematical model adds complexity, categorizing it as an NP-hard problem. We have developed six new metaheuristic algorithms. Designed specifically for optimization in hybrid energy systems, this further highlights the uniqueness of this approach to research.

The word “sustainability” is discussed in several ways since MDGs and SDGs have gained business attention. Sustainability is not just about something’s durability; it also looks at how to advance development projects without endangering the development of others nearby, both now and in the future (Fink, 2000). It is a drive that weaves together the different facets, including the social, economic, and environmental. World Economic Forum’s has emphasised the need for responsive and responsible leadership. It is in this context, the paper focuses on studying the transformational shift in the role and responsibility of leaders in demonstrating responsible leadership and discusses the ‘Locust and Honeybee Leadership styles’.

Literature portrays that responsible leaders are recognized by their qualities, competency and skills. One such model is “Locust and Honeybee Leadership,” where the two leadership styles are contrasted. The paper attempts to discuss the varied contexts of these leadership styles and attempts to draw a matrix on the commonalities of both set in an Indian context. A leader should always have openness of thought and integrity.

Value systems are important for a leader. The major challenge is developing globally responsible leaders and managers who can perform effectively under these conditions of enormous challenge, as they are chronically pushed beyond their capabilities into unexpected roles and unfamiliar domains. Situations compel leaders to make decisions, yet the styles determine the way the decisions are taken. The paper is unique as it discusses the commonalities and contrasting perspectives of the “Locust and Honeybee Leadership.”

The paper is limited to a small number of respondents and is set in Indian context.

To the best of the authors’ knowledge, the paper is an original piece of work and expresses thoughts of the authors on establishing a sustainable leadership model.

This article develops an innovative multidisciplinary conceptual framework in the field of refugee entrepreneurship by combining the theory of mixed embeddedness with the concepts of intersectionality and agency. Focusing on the phenomenon of refugee entrepreneurship, this conceptual framework addresses the following questions: how is entrepreneurship informed by the various intersectional positions of refugees? And how do refugees exert their agency based on these intersecting identities?

By revising the mixed embeddedness approach and combining it with an intersectional approach, this study aims to develop a multidimensional conceptual framework.

This research illustrates how the intersectional positions of refugees impact their entrepreneurial motivations, resources and strategies. The authors' findings show that refugee entrepreneurship not only contributes to the economic independence of refugees in new societies but also creates opportunities for refugees to exert their agency.

This conceptual framework can be applied in empirical research and accordingly contributes to refugee entrepreneurship studies and intersectionality theory.

This paper aims to investigate the influence of “BroncoCut-X” (copper core-ZnCu50 coating) electrode on the machining of Ti-3Al-2.5V in view of its extensive use in aerospace and medical applications. The machining parameters are selected as Spark-off Time (ST_off), Spark-on Time (ST_on), Wire-speed (S_w), Wire-Tension (WT) and Servo-Voltage (S_v) to explore the machining outcomes. The response characteristics are measured in terms of material removal rate (MRR), average kerf width (KW) and average-surface roughness (SA).

Taguchi’s approach is used to design the experiment. The “AC Progress V2 high precision CNC-WEDM” is used to conduct the experiments with ϕ 0.25 mm diameter wire electrode. The machining performance characteristics are examined using main effect plots and analysis of variance. The grey-relation analysis and fuzzy interference system techniques have been developed to combine (called grey-fuzzy reasoning grade) the experimental response while Rao-Algorithm is used to calculate the optimal performance.

The hybrid optimization result is obtained as ST_off = 50µs, ST_on = 105µs, S_w = 7 m/min, WT = 12N and S_v=20V. Additionally, the result is compared with the firefly algorithm and improved gray-wolf optimizer to check the efficacy of the intended approach. The confirmatory test has been further conducted to verify optimization results and recorded 8.14% overall machinability enhancement. Moreover, the scanning electron microscopy analysis further demonstrated effectiveness in the WEDMed surface with a maximum 4.32 µm recast layer.

The adopted methodology helped to attain the highest machinability level. To the best of the authors’ knowledge, this work is the first investigation within the considered parametric range and adopted optimization technique for Ti-3Al-2.5V using the wire-electro discharge machining.

After completion of the case study, students will be able to understand the format of for-profit social enterprise working for menstrual hygiene sustainability and its contribution toward U.N. Sustainable Development Goals, to appreciate the company’s alignment with the triple bottom line framework, to analyze the blue ocean mechanism that the company has developed to create an impact and to critique the strategies the Asan Cups company could adopt to increase its market share and growth.

Asan Cups was a for-profit social enterprise founded by Ira Guha in 2021. The company crafted reusable menstrual cups from liquid silicone, sporting a patented design in India, the UK, Europe and the USA. Successfully retailing its products in India, the UK and Europe, Asan Cups operated on a bootstrap model with a compact team of four, led by its visionary founder. From the get-go, the company embraced a compelling 1-for-1 donation initiative. For every cup sold, Asan Cups generously donated another to women who could not afford it. Collaborating with nongovernmental organizations, schools, educational institutions and social workers, the company spearheaded campaigns to heighten menstrual hygiene awareness. This proactive approach aimed to boost the acceptance of menstrual cups among rural women and championed the cause of environmental sustainability. The company did not just stop at providing an eco-friendly alternative. Asan Cups fervently educated the masses on the detrimental environmental impact of traditional disposable period products like sanitary pads and tampons. Fast-forwarding to 2023, Asan Cups had garnered approximately 30,000 users, with the adoption rate steadily climbing. The company strategically used an education-intensive model to foster awareness about period products in collaboration with partners nationwide. However, being a for-profit entity, the founder, Guha, was at a crossroads. Balancing the need for profitability, there was mounting pressure to explore additional revenue streams and expand operations and market reach. The dilemma loomed large: opt for a quicker marketing strategy or stay true to the company’s foundational education-centered approach. This case study delves into the dynamic strategies, impactful operations and growth scenarios Asan Cups navigated since its inception. It examines the pivotal choices faced by the founder and explores potential strategies for sustained growth.

This case study can be used at both undergraduate and master’s levels. The case study will be handy for strategic management and business strategy courses and can also be used for social entrepreneurship, marketing and entrepreneurship courses.

Teaching notes are available for educators only.

CSS 11: Strategy.

Unlike many existing methods that are primarily focused on two-dimensional localization, this research paper extended the scope to three-dimensional localization. This enhancement is particularly significant for unmanned aerial vehicle (UAV) applications that demand precise altitude information, such as infrastructure inspection and aerial surveillance, thereby broadening the applicability of UAV-assisted wireless networks.

The paper introduced a novel method that employs recurrent neural networks (RNNs) for node localization in three-dimensional space within UAV-assisted wireless networks. It presented an optimization perspective to the node localization problem, aiming to balance localization accuracy with computational efficiency. By formulating the localization task as an optimization challenge, the study proposed strategies to minimize errors while ensuring manageable computational overhead, which are crucial for real-time deployment in dynamic UAV environments.

Simulation results demonstrated significant improvements, including a channel capacity of 99.95%, energy savings of 89.42%, reduced latency by 99.88% and notable data rates for UAV-based communication with an average localization error of 0.8462. Hence, the proposed model can be used to enhance the capacity of UAVs to work effectively in diverse environmental conditions, offering a reliable solution for maintaining connectivity during critical scenarios such as terrestrial environmental crises when traditional infrastructure is unavailable.

Conventional localization methods in wireless sensor networks (WSNs), such as received signal strength (RSS), often entail manual configuration and are beset by limitations in terms of capacity, scalability and efficiency. It is not considered for 3-D localization. In this paper, machine learning such as multi-layer perceptrons (MLP) and RNN are employed to facilitate the capture of intricate spatial relationships and patterns (3-D), resulting in enhanced localization precision and also improved in channel capacity, energy savings and reduced latency of UAVs for wireless communication.

By aligning the “Small is beautiful” and “Bleak house” theories, this study aims to examine how robotic working patterns affect employees’ working life and job satisfaction (JS) in Bangladeshi-owned ethnic minority businesses.

The study uses information from 40 face-to-face interviews of employees from 20 Bangladeshi restaurants in Greater London.

The findings suggest that workers are treated as “robots”, consistent with the “Bleak house” view of small businesses in this segment of the restaurant and hospitality industry. Owners expect employees to perform multiple tasks, to assume many responsibilities, to work long shifts, without any holiday allowances. Consistent with the “Small is beautiful model”, the findings underscore the lack of written employment contracts and the emergence of acute staff shortages.

The findings can inform owner-managers’ decisions to refine their HR strategies and improve the work conditions of employees in ethnic minority-owned restaurants. The “Small is beautiful” model highlights five key interventions for improving ethnic minority business work quality: recruit employees with first preferences for restaurant jobs, introduce flexible work arrangements, formalise work, improve market research and tackle acute staff shortages.

The study contributes novel insights into the small- and medium-sized enterprises (SMEs) and job quality literature by offering new qualitative-based findings on the negative impact of robotic work patterns on work quality and JS in ethnic minority SMEs.

This paper responds to several calls for a cross-national comparative study of immigrant entrepreneurship throughout the longstanding discourse of this phenomenon. This study aims to comparatively analyze the nature of immigrant enclave entrepreneurship among one immigrant community across three different jurisdictional contexts (UK, Denmark and Norway) based on comparative ethnographic methods of inquiry.

The data was collected in person from April 2022 to June 2023 by the researchers to identify the similarities and differences of migrant entrepreneurial activities in three immigrant enclaves (Manchester, Oslo and Copenhagen). Comparative ethnographic narrative analysis methods and template analysis approaches were combined to analyze interviews, observations and secondary published data.

This study examines spatiality, sectoral occupation and market orientation for comparative analysis. Through detailed analysis, it uncovers the spatiality and nuances in market demands and sectoral similarities across diverse regulatory environments. Notably, it identifies traditional migrant sectoral occupations shared across regions and its relevance to immigrant enclaves.

This scholarly contribution explores immigrant entrepreneurship in various national contexts, emphasising their engagement in neglected and low-value sectors within immigrant enclaves. The study addresses the influence of the host economy’s conditions on immigrant entrepreneurs, impacting their strategic orientation and the extent of their “embeddedness”. It responds to the theoretical gap in immigrant entrepreneurship literature by conducting a cross-national investigation across countries, extending the comparative dimension to Norway and Denmark. The research employs a unique design focusing on a specific immigrant group and emphasizes spatial contexts, sectoral proliferation and market orientation within immigrant enclaves, offering insights into the mixed embeddedness perspective and the broader environmental forces shaping migrant entrepreneurial activities in the UK and Scandinavia.

Retirement is a preparation for transitioning from one role to another and transitioning to a new stage of life. The deepening aging of the population encourages the policymakers to start the Bridge Employment plan when the society faces the unprecedented challenges of decreasing labor supply, heavier burdens of retirement and slow economic growth. The purpose of this study, the decision model for Bridge Employment has been developed by systematically reviewing the research literature.

A bibliometric analysis was conducted to cover publications on Bridge Employment for Return to Work published from 1994 to 2023, including a total of 1,936 publications collected from the Web of Science and Scopus. The patterns and trends in terms of sources of publications, intellectual structure and major topics were analyzed.

After carefully examining the results of the selected studies, three categories of individual (micro level), organizational (medium level) and contextual (macro level) factors were identified as effective factors on bridge employment and model development. Each of the mentioned factors, along with the legal, financial, managerial, educational-administrative and consulting requirements, form the basis for the development of the model and decision framework for Paul’s employment.

This model can be a basis as a framework for bridge recruitment planning so that organizations can once again use their skills–knowledge–expertise in different jobs and even training younger people.