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The learning outcomes are as follows:

1. enable students to appreciate how a platform company can navigate through diminishing network effects;

2. enable students to foresee the downside of scaling up a platform business;

3. enable students to appreciate the trade-off between an efficiency-centric and a novelty-centric business model for platform businesses; and

4. enable students to create a platform business model canvas for a company.

The teaching case discusses the dilemma of Akshay Chaturvedi, the founder of Leverage Edu, an artificial intelligence-enabled platform for students seeking admission to foreign universities. It had received nearly US$9.6m in funding until December 2021.

Chaturvedi wanted to make the best use of his funds, but was torn between turning Leverage Edu into an “efficient platform” and transforming it into a “novelty-centric platform”. The teaching note attempts to resolve Chaturvedi’s dilemma by analyzing competitors using the platform canvas model and determining how Chaturvedi could create and use network effects to Leverage Edu’s advantage. The case is based on secondary data that is freely available in the public domain.

This case is intended for MBA Entrepreneurship students taking a platform business elective. It can also be used in faculty and management development programs under the banner “Technology and Platform Businesses”.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

In the present study, we examined how effectively online travel agencies (OTAs) handle negative e-word-of-mouth on social media platforms like Facebook, Twitter, and Instagram. We collected data from 497 participants using survey method. To test the hypotheses formulated from the existing literature, structural equation modeling was adopted in this study. The results from structural equation modeling indicate effective handling of the negative e-word of mouth (e-WOM) on social media websites significantly affects customer satisfaction and repurchase intention. The current research work provides insight into social media recovery efforts and service fairness when handling negative e-WOM. The study recommends that customers can distinguish the differences between general efforts and adaptive complaint-handling efforts, and dissimilarities may influence satisfaction, repurchase intentions, etc. Although empathy, apology, responsiveness, and paraphrasing are considered pioneer strategies in complaint handling, customers' negative e-WOM, and firms' recovery management, but the current study is among a few to categorize OTAs' handling of negative e-WOM and complaint handling efforts in the social media environment.

Diabetes is a chronic disease and the major types of diabetes are type 1 and type 2. On aging, people with diabetes tend to have long-term problems in hypertension, coronary artery disease, obesity, and nerves. Given the increasing number of complications in recent years, by 2040, 624 million people will have diabetes worldwide and l in 8 adults will have diabetes in the future. Machine learning (ML) is evolving rapidly, many aspects of medical learning use ML. In this study, tension-type headaches (TTH) were associated with diabetes using SPSS, Pearson correlation, and ANOVA tests. Data were collected from Delhi NCR Hospital. It contains 30 diabetic subjects. The purpose of this study was to correlate diabetes analysis from TTH and other diseases using the latest technologies to analyze the Internet of Things and Big Data and Stress Correlation (TTH) on human health. The authors used Pearson correlation to correlate study variables and see if there was any effect between them. There was an important relationship between the percent variable, the total number of individuals, the number of individuals, and the minimum variable. The age (field) of the number of individuals to one of the total number of individuals showed a strong correlation (1.000) with a significant value of p (1.000). Overall, cases of TTH increased with age in men and do not follow the pattern of change in diabetes with age, but in cases of TTH, patterns of headaches such as diabetes increase to age 60 and then tend to decrease.

During the Coronavirus crisis (COVID-19) that started in 2019 and at the extensive quarantine regulations, educational institutions, companies, and individuals have reacted by shifting their teaching and learning activities to virtual spaces. Yet, although the use of online learning has increased, it has not been able to achieve the long-promised transformative effect. The COVID-19 crisis has the potential to boost online education overall or at least enable better preparation of the system for the next crisis. Ultimately, to make a digital transformation sustainable, appropriate skills are required. In this study, we adapt the dynamic capabilities foundations creating a theoretical approach to explain how educational institutions have responded to the changing environmental conditions during the COVID-19 pandemic.

A finite volume scheme for diffusion equations on non-rectangular meshes is proposed in [Deyuan Li, Hongshou Shui, Minjun Tang, J. Numer. Meth. Comput. Appl., 1(4)(1980)217–224 (in Chinese)], which is the so-called nine point scheme on structured quadrilateral meshes. The scheme has both cell-centered unknowns and vertex unknowns which are usually expressed as a linear weighted interpolation of the cell-centered unknowns. The critical factor to obtain the optimal accuracy for the scheme is the reconstruction of vertex unknowns. However, when the mesh deformation is severe or the diffusion tensor is discontinuous, the accuracy of the scheme is not satisfactory, and the author hope to improve this scheme.

The authors propose an explicit weighted vertex interpolation algorithm which allows arbitrary diffusion tensors and does not depend on the location of discontinuity. Both the derivation of the scheme and that of vertex reconstruction algorithm satisfy the linearity preserving criterion which requires that a discretization scheme should be exact on linear solutions. The vertex interpolation algorithm can be easily extended to 3 D case.

Numerical results show that it maintain optimal convergence rates for the solution and flux on 2 D and 3 D meshes in case that the diffusion tensor is taken to be anisotropic, at times heterogeneous, and/or discontinuous.

This paper proposes a linearity preserving and explicit weighted vertex interpolation algorithm for cell-centered finite volume approximations of diffusion equations on general grids. The proposed finite volume scheme with the new interpolation algorithm allows arbitrary continuous or discontinuous diffusion tensors; the final scheme is applicable to arbitrary polygonal grids, which may have concave cells or degenerate ones with hanging nodes. The final scheme has second-order convergence rate for the approximate solution and higher than first-order accuracy for the flux on 2 D and 3 D meshes. The explicit weighted interpolation algorithm is easy to implement in three dimensions in case that the diffusion tensor is continuous or discontinuous.

Artificial neural networks (ANNs), which represent computational models simulating the biological neural systems, have become a dominant paradigm for solving complex analytical problems. ANN applications have been employed in various disciplines such as psychology, computer science, mathematics, engineering, medicine, manufacturing, and business studies. Academic research on ANNs is witnessing considerable publication activity, and there exists a need to track the intellectual structure of the existing research for a better comprehension of the domain. The current study uses a bibliometric approach to ANN business literature extracted from the Web of Science database. The study also performs a chronological review using science mapping and examines the evolution trajectory to determine research areas relevant to future research. The authors suggest that researchers focus on ANN deep learning models as the bibliometric results predict an expeditious growth of the research topic in the upcoming years. The findings reveal that business research on ANNs is flourishing and suggest further work on domains, such as back-propagation neural networks, support vector machines, and predictive modeling. By providing a systematic and dynamic understanding of ANN business research, the current study enhances the readers' understanding of existing reviews and complements the domain knowledge.

Purpose: Entrepreneurial teams are one of the most crystallized forms of collaboration in the generically collective dynamics underpinning social entrepreneurship. Despite their quantitative prevalence, social entrepreneurial teams (SETs) remain quite absent from the scholarly literature. This chapter aims to develop a research agenda addressing this gap. Methodology/Approach: This chapter first reviews the scarce literature dealing with this subject and develops an operationalizable definition of SETs. Next, it confronts current knowledge on entrepreneurial teams with the specific context of social entrepreneurship to introduce and discuss main topics of investigation on SETs. Findings: Six topics are suggested to have a high potential for developing knowledge on SETs: formation, size and extended team, gender, decision-making and leadership, identity, and turnover. Research Implications: This chapter frames these research avenues within a developmental stages perspective with the aim to contribute to help form and maintain effective SETs. Originality/Value of Chapter: This research has implications for scholars as it defines SETs as a distinct object for research, which allows extending knowledge on collaborative dynamics in social entrepreneurship, but also on entrepreneurial teams in general. The suggested research agenda and its orientation toward the development of effective SETs should be a springboard for future research on this subject.

This chapter aims to examine the role of consumer demographics over the chosen parameters of online shopping. Online shopping had emerged as an important platform for the consumers during the phase of pandemic spread in India which even included several phases of lockdowns. The state of pandemic commenced at a severe note leading to restrictive movement, social distancing, observing least contact with objects, and several other limitations. Due to this, many businesses had moved to online selling in order to target greater sales. This study was conducted in order to provide insights to various businesses, experts, and academic researchers in this domain to find out the role of demographical and behavioral differences of different consumer segments. It could serve as a robust study providing information about the current consumer behavior at the time of pandemic spread toward online shopping. This would help marketing experts explore the different opportunities and challenges involved in this new scenario formed due to COVID-19. Apart from adding value to the existing literature, this study leads a way to future research.

While diversity, equity, inclusion, and belonging (DEIB) in the workplace means making space for all employees, it has unique implications for Indigenous employees who live and work in countries built on colonialism. Indigenous peoples represent diverse groups with unique and rich cultures that in general share values that are more holistic, spiritual, traditional, egalitarian, and other-oriented than non-Indigenous populations. Such distinct worldviews help explain why non-Indigenous organizations struggle to understand and accommodate Indigenous employees’ priorities and goal-oriented behavior. Creating equity, inclusivity, and belonging in the workplace for Indigenous employees requires more than implementing existing organizational practices with a new cultural awareness, it requires rethinking, reframing, and recreating organizational to facilitate a culture of trust. Re-examining organizational norms and assumptions with the ideas of relationship and responsibility that allow collaborative approaches to collective well-being and inclusivity is required. Creating inclusive workspaces requires that attention must be paid to both organizational (group-level) factors, such as organizational cultures of trust, and interpersonal (individual-level) factors, such as interpersonal trust. However, to build foundations of high-functioning and supportive organizational cultures and interpersonal trust that are sustainable, time and resources are necessary. Without this, the ability to reach the crucial result of engaging Indigenous employees and creating safe workplaces serves only to be performative and not meaningful in terms of action, longevity, and the overall well-being of Indigenous people in the workplace.

The purpose of this paper is to achieve high-precision sliding mode control without chattering; the control parameters are easy to adjust, and the entire controller is easy to use in engineering practice.

Using double sliding mode surfaces, the gain of the control signal can be adjusted adaptively according to the error signal. A kind of sliding mode controller without chattering is designed and applied to the control of ultrasonic motors.

The results show that for a position signal with a tracking amplitude of 35 mm, the traditional sliding mode control method has a maximum tracking error of 0.3326 mm under the premise of small chattering; the boundary layer sliding mode control method has a maximum tracking error of 0.3927 mm without chattering, and the maximum tracking error of continuous switching adaptive sliding mode control is 0.1589 mm, and there is no chattering. Under the same control parameters, after adding a load of 0.5 kg, the maximum tracking errors of the traditional sliding mode control method, the boundary layer sliding mode control method and the continuous switching adaptive sliding mode control are 0.4292 mm, 0.5111 mm and 0.1848 mm, respectively.

The proposed method not only switches continuously, but also the amplitude of the switching signal is adaptive, while maintaining the robustness of the conventional sliding mode control method, which has strong engineering application value.