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This paper aims to present a non-linear mathematical model-based routing protocol for wireless body area networks (WBANs). Two non-linear mathematical models for WBANs are used in the proposed protocols Model 1 and Model 2. Model 1 intends to improve the data transmission rate and Model 2 intends to reduce energy consumption in the WBANs. These models are simulated for fixed deployment and priority-based data transmission, and performance of the network is analyzed under four constraints on WBANs.

Advancements in wireless technology play a vital role in several applications such as electronic health care, entertainment and games. Though WBANs are widely used in digital health care, they have restricted battery capacity which affects network stability and data transmission. Therefore, several research studies focused on reducing energy consumption and maximizing the data transmission rate in WBANs.

Simulation results of the proposed protocol exhibit superior performance in terms of four network constraints such as residual energy, the stability of the network, path loss and data transmission rate in contrast with conventional routing protocols. The performance improvement of these parameters confirms that the proposed algorithm is more reliable and consumes less energy than traditional algorithms.

The Model 1 of the proposed work provides maximum data extraction, which ensures reliable data transmission in WBANs. The Model 2 allocates minimal hop count path between the sink and the sensor nodes, which minimizes energy consumption in the WBANs.

The foreign-born skilled immigrant population is growing rapidly in Canada but finding a job that utilizes immigrants’ skills, knowledge and experience is challenging for them. The purpose of this paper is to understand the self-perceived health and social status of skilled immigrants who were working in low-skilled jobs in the service sector in Ottawa, Canada.

In this qualitative study, semi-structured interviews with 19 high-skilled immigrants working as taxi drivers and convenience store workers in the city of Ottawa, Canada were analysed using a grounded theory approach.

Five major themes emerged from the data: high expectations but low achievements; credential devaluation, deskilling and wasted skills; discrimination and loss of identity; lifestyle change and poor health behaviour; and poor mental and physical health status.

The study demonstrates the knowledge between what skilled immigrants expect when they arrive in Canada and the reality of finding meaningful employment in a country where international credentials are less likely to be recognized. The study therefore contributes to immigration policy reform which would reduce barriers to meaningful employment among immigrants reducing the impacts on health resulting from employment in low-skilled jobs.

This study provides unique insights into the experience and perceptions of skilled immigrants working in low-skilled jobs. It also sheds light on the “healthy worker effect” hypothesis which is a highly discussed and debated issue in the occupational health literature.

Consumers are worried about sharing their sensitive information during online shopping due to the e-tailer’s unethical practices and hacking-related concerns. Prior research has established the country of origin (COO) as a trust-building cue; however, it requires empirical testing in the online retailing context. The present study aims to examine the e-tailer COO’s effect on consumer privacy, trust and purchase intention.

An online survey floated a seven-point Likert scale questionnaire and invited the receivers to participate in the investigation over e-mails and text messages. A total of 355 usable responses were analyzed using R programming.

This study empirically validated a proposed conceptual model examining the influence of COO on consumer privacy, trust and purchase intention. The findings suggest that COO influences consumer privacy, trust and purchase intention. This study further found that the privacy practices of online retailers positively impact consumer trust. Trust acts as a mediating factor in influencing purchase intention.

This study offers valuable insights for advancing the research agenda and actionable inputs to e-commerce managers for alleviating consumer privacy concerns in emerging economies. Future researchers can test the proposed model in other demographic and e-commerce settings.

This study contributes to the present knowledge on consumer privacy in online retailing in the Indian context. This paper also examines the relationship of COO with consumer privacy, trust and purchase intention, an underexplored research area in emerging markets.

Online shoppers feel insecure due to the various unethical practices of e-tailers. It is, therefore, crucial for online retailers to alleviate customer concerns. Extant literature indicates that country-of-origin (COO) cues influence consumer perception. A relatively underexplored phenomenon in an emerging market context, the COO image of the online retailer, i.e. a foreign-origin online retailer (FOOR) or an Indian-origin online retailer (IOOR), needs validation. The current study investigates customer expectations of online retailers' ethical behaviour against the backdrop of online retailer-based signals in emerging markets.

The researchers floated an online questionnaire using a seven-point Likert scale. The authors sought recipient responses in Google Forms shared via e-mails and social media connections. The authors analysed 1,018 useable responses using partial least square structural equation modelling (PLS-SEM) in Smart PLS 3.

The empirical study examined the influence of the consumer perception of ethics of online retailers (CPEOR) and COO on consumer purchase intention. It validated the proposed research model. The research findings inform that the CPEOR and the COO influence purchase intention through the mediation effects of trust and satisfaction. Results indicate that privacy, security, non-deception, fulfilment, customer service, FOOR and IOOR strongly predict consumer trust. In contrast, privacy, non-deception, fulfilment, customer service and FOOR strongly predict consumer satisfaction. However, security and IOOR did not influence consumer satisfaction.

The study results have theoretical and practical implications for academic researchers and online retailing managers. Future studies can validate the model in different geo-demographic scenarios and e-commerce settings.

The study enriches the extant literature on CPEOR in the Indian context. This study is pioneering work examining consumer purchase intention by adding the COO construct to the CPEOR model.

The paper aims to introduce an intelligent recognition system for viewpoint variations of gait and speech. It proposes a convolutional neural network-based capsule network (CNN-CapsNet) model and outlining the performance of the system in recognition of gait and speech variations. The proposed intelligent system mainly focuses on relative spatial hierarchies between gait features in the entities of the image due to translational invariances in sub-sampling and speech variations.

This proposed work CNN-CapsNet is mainly used for automatic learning of feature representations based on CNN and used capsule vectors as neurons to encode all the spatial information of an image by adapting equal variances to change in viewpoint. The proposed study will resolve the discrepancies caused by cofactors and gait recognition between opinions based on a model of CNN-CapsNet.

This research work provides recognition of signal, biometric-based gait recognition and sound/speech analysis. Empirical evaluations are conducted on three aspects of scenarios, namely fixed-view, cross-view and multi-view conditions. The main parameters for recognition of gait are speed, change in clothes, subjects walking with carrying object and intensity of light.

The proposed CNN-CapsNet has some limitations when considering for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.

This research work includes for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.

This proposed research work proves to be performing better for the recognition of gait and speech when compared with other techniques.

As evident from the literature review, the research on cyber security performance is centered on security metrics, maturity models, etc. Essentially, all these are helpful for evaluating the efficiency of cyber security organization but what matters is how the factors of internal efficiency affect the business performance, i.e. the external effectiveness. The purpose of this research paper is to derive the factors of internal efficiency and external effectiveness of cyber security and develop impact model to identify the most and least preferred parameters of internal efficiency with respect to all the parameters of external effectiveness.

There are two objectives for this research: Deriving the factors of internal efficiency and external effectiveness of cyber security; Developing a model to identify the impact of internal efficiency factors on the external effectiveness of cyber security since there is not much evidence of research in defining the factors of internal efficiency and external effectiveness of cyber security, the authors have chosen grounded theory methodology (GTM) to derive the parameters. In this study emic approach of GTM is followed and an algorithm is developed for administering the grounded theory research process. For the second research objective survey methodology and rank order was used to formulate the impact model. Two different samples and questionnaires were designed for each of the objectives.

For the objective 1, 11 factors of efficiency and 10 factors of effectiveness were derived. These are used as independent and dependent variable respectively in the later part of the research for the second objective. For the objective 2 the impact models among independent and dependent variables were formulated to find out the following. Most and least preferred parameters lead to internal efficiency of cyber security organization to identify the most and least preferred parameters of internal efficiency with respect to all the parameters external effectiveness.

The factors of internal efficiency and external effectiveness constructed by using grounded theory cannot remain constant in the long run, because of dynamism of the domain itself. Over and above this, there are inherent limitations of the tools like grounded theory, used in the research. Few important limitations of GTM are as below in grounded theory, it is comparatively difficult to maintain and demonstrate the rigors of research discipline. The sheer volume of data makes the analysis and interpretation complex, and lengthy time consuming. The researchers’ presence during data gathering, which is often unavoidable and desirable too in qualitative research, may affect the subjects’ responses. The subjectivity of the data leads to difficulties in establishing reliability and validity of approaches and information. It is difficult to detect or to prevent researcher-induced bias.

The internal efficiency and external effectiveness factors of cyber security can be further correlated by the future researchers to understand the correlations among all the factors and predict cyber security performance. The grounded theory algorithm developed by us can be further used for qualitative research for deriving theory through abstractions in the areas where there is no sufficient availability of data. Practitioners of cyber security can use this research to focus on relevant areas depending on their respective business objective/requirements. The models developed by us can be used by the future researchers to for various sectoral validations and correlations.

Though the financial costs of a cyber-attack are steep, the social impact of cyber security failures is less readily apparent but can cause lasting damage to customers, employees and the company. Therefore, it is always important to be mindful of how the impact of cyber security affects society as well as the bottom line when they are calculating the potential impact of a breach. Underestimating either impact can destroy a brand. The factor of internal efficiency and external effectiveness derived by us will help stakeholder in focusing on relevant area depending on their business. The impact model developed in this research is very useful for focusing a particular business requirement and accordingly tune the efficiency factor.

During literature study the authors did not find any evidence of application of grounded theory approach in cyber security research. While the authors were exploring research literature to find out some insight into the factor of internal efficiency and external effectiveness of cyber security, the authors did not find concrete and objective research on this. This motivated us to use grounded theory to derive these factors. This, in the authors’ opinion is one of the pioneering and unique contribution to the research as to the authors’ knowledge no researchers have ever tried to use this methodology for the stated purpose and cyber security domain in general. In this process the authors have also developed an algorithm for administering GTM. Further developing impact models using factors of internal efficiency and external effectiveness has lots of managerial and practical implication.

Recently, blockchain technology (BT) has resolved healthcare data management challenges. It helps healthcare providers automate medical records and mining to aid in data sharing and making more accurate diagnoses. This paper attempts to identify the critical success factors (CSFs) for successfully implementing BT in healthcare.

The paper is methodologically structured in four phases. The first phase leads to identifying success factors by reviewing the extant literature. In the second phase, expert opinions were solicited to authenticate the critical success factors required to implement BT in the healthcare sector. Decision Making Trial and Evaluation Laboratory (DEMATEL) method was employed to find the cause-and-effect relationship among the third phase’s critical success factors. In phase 4, the authors resort to validating the final results and findings.

Based on the analysis, 21 CSFs were identified and grouped under six dimensions. After applying the DEMATEL technique, nine factors belong to the causal group, and the remaining 12 factors fall under the effect group. The top three influencing factors of blockchain technology implementation in the healthcare ecosystem are data transparency, track and traceability and government support, whereas; implementation cost was the least influential.

This study provides a roadmap and may facilitate healthcare professionals to overcome contemporary challenges with the help of BT.

The choice of best machining parameters is an extremely basic factor in handling of any machined parts. The purpose of this paper is to exhibit a multi-objective optimization technique; in view of weighted aggregate sum product assessment (WASPAS) technique toward upgrade the machining parameters in modified air abrasive jet machining (MAAJM) process: injecting pressure, stand-off distance (SOD), and abrasive mesh size measure with 100 rpm rotatable worktable on Nickel 233 alloy material. Three conflicting destinations, material removal rate (MRR), surface roughness (SR) and taper angles (Ta), respectively, are considered at the same time. The proposed procedure uses WASPAS, which is the examination of parametric optimization of the abrasive jet machining (AJM) process. The results was used any scopes of reactions in MAAJM process is the ideal setting of parameters are resolved through investigations represented. There is wide utilization of Nickel 233 in aviation enterprises; machining information on producing a hole utilizing MAAJM for the first time is given in this work, which will be helpful different industries.

This paper exhibits a multi-objective optimization technique; in view of WASPAS technique toward upgrade the machining parameters in MAAJM process: injecting pressure, SOD, and abrasive mesh size measure with 100 rpm rotatable worktable on Nickel 233 alloy material.

As an outcome of using the tool in any ranges of responses in the AJM process, the optimal setting of parameters is determined through experiments illustrated. The machining data of generating a hole using AJM are studied for the first time in this work, which will be useful for aerospace industries, where Nickel 233 is used broadly.

A new material in unconventional machining process and also a multi-objective optimization technique are adopted.

This case study will allow students to learn about effective segmentation and how to choose an appropriate segment, analyse the attractiveness of the target market by using five-forces analysis and explore business growth alternatives by using Ansoff’s growth matrix.

The Left-Out Store was an online shop that sold products exclusively for left-handers. Maitri Wadher, the proprietor of the store, being a left-handed person and driven by her childhood experiences, started the store to help left-handed people find products for their use. She started the online-only store in September 2018, and in October 2022, she found that, despite the COVID-19 pandemic having abated, her store had not grown as expected. How, then, should she push for growth? Was the niche segment substantial enough? Was her target market attractive? Should she penetrate the market or go for market development? What should she do?

PG level (MBA/PGDM).

Teaching Notes are available for educators only.

CSS 8: Marketing.

Acknowledging the significance of perceived organizational support (POS) for employees’ performance, this study aims to examine the underlying mechanism of task performance in a COVID-19 pandemic-induced blended working (TPBW) environment and the role of perceived usefulness of digitalization (PUDBW) in the process.

Survey data collected from 204 managers of Indian public sector undertakings pursuing blended working for the first time were analyzed using structural equation modelling. A qualitative study on 31 such managers was also performed.

Although employees perceived an improvement in POS, PUDBW and TPBW (during the COVID pandemic) in comparison to the pre-COVID time when traditional work design was operational, yet the improvement in task performance was not directly influenced by POS. POS had a positive effect on PUDBW, which in turn positively affected TPBW. PUD acted as a mediator. A negative moderation effect of POS on the relationship between PUDBW and TPBW was found.

Findings of the study may help organizations and policymakers to focus on key enablers, such as organizational support and relevant digital initiatives, for ensuring better task performance by their employees during a blended working environment, even in difficult times as the COVID-19 pandemic.

This study, for the first time, examined the proposed relationships in a new work setting of blended working and explained the underlying mediation and moderation mechanisms in their relationships.