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The essence of management education lies in preparing and enabling the students to evolve cognitively, affectively and behaviorally into capable ones equipped to meet and manage challenges from within and outside their organisations or workplaces. Mentoring, as pedagogy, results in enhancing effectiveness of B‐schools (Institutions offering MBA program) in ensuring the transformation of students into professionals. The purpose of this paper is to analyze and evaluate the formal and teacher‐initiated student mentoring in B‐schools in Kerala in terms of the designated activities, to establish effectiveness of mentoring as outcomes of faculty‐related antecedents and mentoring activities, and to demonstrate the effectiveness in terms of the psycho‐social changes of students.

This research employed a conclusive approach that combined the features of descriptive and explanatory research designs. The respondents of the study comprised 141 permanent teachers, 327 first‐year students and 318 final‐year students enrolled in the management programs of 19 B‐schools in Kerala that had minimum five years of existence and approval of the All India Council of Technical Education (AICTE).

The study revealed that less than half of the B‐schools had implemented a mentoring program as part of their pedagogy. A structural equation model using the partial least square technique validated the conceptual model and the findings revealed that socio‐demographic characteristics, mentoring activities (teach the job, provide challenge, teach politics, career help, sponsor, career counseling and trust) influenced effectiveness of mentoring.

The study was conducted only among B‐schools, hence the research results may lack generalization. Therefore, researchers are encouraged to test the proposed model further.

The paper includes a conceptual framework employed for bringing about effectiveness of mentoring, proven to be valid and may be considered by B‐schools that are institutionalizing mentoring as an element of the pedagogy.

The paper bridges the perceptible lack of theoretical and empirical bases to explain the dynamics of student mentoring in management institutes in the country and will be an eye‐opener to management institutions which have not incorporated mentoring as part of their pedagogy.

The purpose of this paper is to examine the usability of the Cultural Framework Analysis Process, a strategy designed to examine cultural factors in mentoring endeavors and to identify whether there are patterns of cultural elements that served to hinder or facilitate mentoring programs across a variety of organizations and contexts. The process also involves identifying methods for overcoming the barriers and enhancing the facilitating factors.

Graduate students in a class on mentoring were given an assignment to analyze a mentoring program using the Cultural Framework Analysis Process. They were also asked to share their most significant learning outcomes. Data were gathered by two student groups over a two-year period. Researchers determined the usability of the analysis process by evaluating the quality of the student submissions. They aggregated the data and conducted a content analysis on the facilitating and hindering factors to determine commonalities and the lessons learned.

The Cultural Framework Analysis Process appears to be a useful tool in examining and dealing with cultural elements in mentoring programs and relationships. The barriers and facilitating factors were closely related to one another. The five barriers to success were matching processes; mentee attitude toward matching; lack of organizational support; static or closed organizational culture; and organizational or community culture. The five factors that facilitated mentoring endeavors were: comprehensive and flexible matching; mentee/mentor attitudes; training; organizational culture and demonstrated commitment; and a focus on mentees.

The ability to examine the cultural elements in the context of mentoring is vital in assuring mentoring success. Having a description of how the process was conducted should be of value to those wanting to engage in similar analyses. The findings related to the factors identified should help guide those engaged in mentoring endeavors to become more aware of elements to consider and deal with as they create and operationalize their programs.

There is a need to enhance the knowledge about the cultural factors involved in mentoring programs and relationships. This research study expands the understanding and presents findings about barriers and supports to mentoring that have not been previously reported. It also provides a mechanism for others to conduct similar analyses as they develop, implement and research mentoring endeavors.

The purpose of this paper is threefold: first, to investigate the role of big data and predictive analytics (BDPA) and social capital on the performance of humanitarian supply chains (HSCs); second, to explore the different performance measurement frameworks and develop a conceptual model for an HSC context that can be used by humanitarian organizations; and third, to provide insights for future research direction.

After a detailed review of relevant literature, grounded in resource-based view and social capital theory, the paper proposes a conceptual model that depicts the influence of BDPA and social capital on the performance of an HSC.

The study deliberates that BDPA as a capability improves the effectiveness of humanitarian missions to achieve its goals. It uncovers the fact that social capital binds people, organization or a country to form a network and has a critical role in the form of monetary or non-monetary support in disaster management. Further, it argues that social capital combined with BDPA capability can result in a better HSC performance.

The proposed model integrating BDPA and social capital for HSC performance is conceptual and it needs to be empirically validated.

Organizations and practitioners may use this framework by mobilizing social capital, BDPA to enhance their abilities to help victims of calamities.

Findings from study can help improve coordination among different stakeholders in HSC, effectiveness of humanitarian operations, which means lives saved and faster reconstruction process after disaster. Second, by implementing performance measurements framework recommended by study, donors and other stakeholders will get much desired transparency at each stage of HSCs.

The findings contribute to the missing link of social capital and BDPA to the existing performance of HSC literature, finally leading to a better HSC performance.

Business organisations are under serious threat to sustain their business due to globalisation, challenging market and recent economic competitiveness. The aim of this study is to address various pressures to circular supply chain management (CSCM) implementation for sustainability.

The present study is based on two research levels. Initially, extensive literature review has been made to identify 31 pressures to CSCM, and eight categories of pressures have been identified. At the second level, fuzzy analytical hierarchy process (F-AHP) has been applied to rank the identified pressures to CSCM implementation for sustainability.

“Financial Pressures (FP)” has been identified as most significant pressure to CSCM implementation for sustainability. Further, “Lack of support of top management (MP1)”, “Lack of implementation of laws and policies (GP2)” and “Lack of vision for CSCM (GP1)” have been found most critical sub-pressures CSCM implementation for sustainability.

The final results give the prioritised list of all identified 31 sub-pressures and eight main pressure heads, which will be helpful in their removal for achieving the goal of CSCM implementation. It will be helpful for managers to take decisions promoting circular practices in supply chains to achieve truly sustainable supply chains. It will also be help for SC managers to understand the flow of activities and materials in CSC to get good results and remove pressures.

The present study plays an important role in circular activities implementation in supply chain for profit gain, and their pressure ranking may help the mangers to implement the CSCM effectively.

The purpose of this study is to assess the impact of spirituality on subjective stress and psychological well-being (PWB). Additionally, the study also examines the mediating role of stress in the spirituality – well-being relationship.

The study is quantitative in nature. Data were collected from 322 secondary school teachers using a structured questionnaire. Partial least squares based structural equation modelling was used to analyse the data.

Results indicated a positive relationship between spirituality and PWB but an inverse relationship between job stresses. Also, subjective stress was found to be a significant mediator in the relationship between spirituality and well-being.

The inner resource of spirituality among teachers can be tapped to cope with perceived stress levels thereby augmenting a sense of well-being. Psychologically clear and receptive minds are indispensable in the process of teaching.

The present study combines the evolving construct of workplace spirituality with PWB and subjective stress, which are under explored in the social sector.

The purpose of this paper is to propose and develop a live interaction-based video player system named LIV4Smile for the improvement of the social smile in individuals with autism spectrum disorder (ASD).

The proposed LIV4Smile intervention was a video player that operated by detecting smile using a convolutional neural network (CNN)-based algorithm. To maintain a live interaction, a CNN-based smile detector was configured and used in this system. The statistical test was also conducted to validate the performance of the system.

The significant improvement was observed in smile responses of individuals with ASD with the utilization of the proposed LIV4Smile system in a real-time environment.

A small sample size and clinical utilizing for validation and initial training of ASD individuals for LIV4Smile could be considered under implications.

The main aim of this study was to address the inclusive practices for children with autism. The proposed CNN algorithm-based LIV4Smile intervention resulted in high accuracy in facial smile detection.

Introduction: Big data in the insurance industry can be defined as structured or unstructured data that can affect the rating, marketing, pricing, or underwriting. The five Vs of big data provide insurers with a valuable framework for converting their raw data into actionable information. These five Vs are specifically: (1) Volume: The need to look at the type of data and the internal systems; (2) Velocity: The speed at which big data is generated, collected, and refreshed; (3) Variety: Refers to both the structured and unstructured data; (4) Veracity: Refers to trustworthiness and confidence in data; and (5) Value: Refers to whether the data collected are good or bad.

Purpose: Insurance companies face many data challenges. However, the administration of big data has allowed insurers to acknowledge the demand of their customers and develop more personalised products. In addition, it can be used to make correct decisions about insurance operations such as risk selection and pricing.

Methodology: We do this by conducting a systematic literature review on big data. Our emphasis is on gathering information on the five Vs of the big data and the insurance market. Specifically, how big data can help in data-driven decisions.

Findings: Big data technology has created an endless series of opportunities, which have ensured a surge in its usage. It has helped businesses make the process more systematic, cost-effective, and helped in the reduction in fraud and risk prediction.