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Entrepreneurship in emerging markets; the planning of survival and competition strategies of small businesses run by entrepreneurs against well established larger brands.

The case can be used at the post graduate level in principles of marketing, entrepreneurship or emerging markets courses.

The case looks at the antecedents and process of transformation of a small-scale firm into a marketing-oriented organization, through the lens of holistic marketing. The case focuses on a small-scale Bangalore based Indian company, Vishaal Natural Food Products (I) Pvt. Ltd that had used the concept of marketing orientation and holistic marketing to effectively make use of the advantages of its “smallness” and the characteristics of its entrepreneurial setup.

How can an entrepreneur survive in a dynamic environment? How should the company conceptually finalize its growth avenues? How can holistic marketing have an impact on the entire functioning of the organization when radical changes to handle the environmental changes, are made? How does the concept of holistic marketing which in textbooks fits in with the complexities of large corporations when they plan their strategies, have an impact on the functioning of these small businesses. The case delves into the conceptual linkages posed by these questions.

Teaching notes are available, please consult your librarian for access.

The purpose of this study is for solving many issues in production that includes processing of complex-shaped profile, machining of high-strength materials, good surface finish with high-level precision and minimization of waste. Among the various advanced machining processes, abrasive jet machining (AJM) is one of the non-traditional machining techniques used for various applications such as polishing, deburring and hole making. Hence, an overview of the investigations done on carbon fiber-reinforced polymer (CFRP) and glass fiber-reinforced polymer (GRFP) composites becomes important.

Discussion on various approaches to AJM, the effect of process parameters on the glass fiber and carbon fiber polymeric composites are presented. Kerf characteristics, surface roughness and various nozzle design were also discussed.

It was observed that abrasive jet pressure, stand-off distance, traverse rate, abrasive size, nozzle diameter, angle of attack are the significant process parameters which affect the machining time, material removal rate, top kerf, bottom kerf and kerf angle. When the particle size is maximum, the increased kinetic energy of the particle improves the penetration depth on the CFRP surface. As the abrasive jet pressure is increased, the cutting process is enabled without severe jet deflection which in turn minimizes the waviness pattern, resulting in a decrease of the surface roughness.

The review is limited to glass fiber and carbon fiber polymeric composites.

In many applications, the use of composite has gained wide acceptance. Hence, machining of the composite need for the study also has gained wide acceptance.

The usage of composites reduces the usage of very costly materials of high density. The cost of the material also comes down.

This paper is a comprehensive review of machining composite with abrasive jet. The paper covers in detail about machining of only GFRP and CFRP composites with various nozzle designs, unlike many studies which has focused widely on general AJM of various materials.

The purpose of this study is to bring out the machining characteristics of abrasive jet machining on carbon fibre reinforced thermoplastic composites utilized in aerospace and biomedical applications. Biocompatibility materials such as carbon fibres and polyether thermoplastics, like polyether ether ketone (PEEK) are widely used in trauma and orthopaedic surgery. Due to the heterogeneity, layered construction of reinforcing phase bonds with a resin matrix and abrasiveness of the reinforcing fibre, traditional drilling of carbon fibre-reinforced composites (CFRPs) are always challenging task.

An investigation is carried out using abrasive jet machine for drilling PEEK filled with 30 Wt.% carbon fibre (CF 30) using threaded and unthreaded nozzle to study the effect of abrasive jet process variables on surface roughness (R_a) and delamination factor (D_F). Pressure (P) and stand-off distance (SOD) as important technological abrasive jet factors were evaluated. It is found that higher abrasive jet pressure and minimum SOD maybe selected to achieve minimum delamination.

The study further reported that the threaded nozzle minimized the surface roughness by 43% and delamination factor up to 12%.

This study of experimenting and observing the machining characteristics of CF30 by using a threaded nozzle is being tried for the first time and the results are deliberated.

This study aimed to collect data on the perception of top executive women in the Aruban hotel sector regarding implicit gender bias.

A qualitative study on the metacognitive processes of awareness, evaluation and autocorrection was utilized. Through purposive sampling women in the top two leadership levels in Aruba Hotel and Tourism Association (AHATA) member-hotels were selected.

Results showed that a third of the top female executives experienced implicit gender bias career barriers. Different types of bias were identified such as: judgments regarding pregnancy, unequal pay and obstructions by the male general manager. How the women dealt with this bias depended on the type of bias and their personality. The identification of bias and its effects on the career trajectory were also influenced by characteristics of the work setting such as the size of the hotel and functional area.

The research limitations include the chosen scope, the impediment of the generalizability of the findings due to the nature of the study, self-perceived data and possible researcher and respondent bias.

This study added to the existing body of leadership development literature with a focus on the effects of implicit bias on female leadership advancement. Some specific theoretical concepts that were combined in this study are organizational leadership, metacognition and the unconscious mind. The important role of personality was also confirmed in this study however one element that stood out in the current study was the effect of resilience in overcoming perceived barriers and attaining personal career goals. Suggestions and directions for future research are provided.

Despite the fact that gender bias was not observed in an explicit form, participants advised to be aware of the existence and effects of the implicit form and to seek education and guidance from female mentors and to remain goal oriented when confronted with this bias. Since female under-representation in senior leadership positions in other economic sectors is not observed this advice serves as a significant practical implication for the development of female leadership in this important sector in Aruba.

The purpose of the study is to machine the composites at lower machining time with higher accuracy without causing delamination.

Abrasive jet machining is the technology appropriate for machining composite materials to obtain good dimensional accuracy without causing de-lamination. The central composite design was followed in deciding the number of experiments to be carried out.

The influence of abrasive jet machining process parameters on machining time, material removal rate (MRR) and kerf characteristics were investigated. The experimental results proved the newly designed internal threaded nozzle increased MRR, thereby reducing the machining time.

Machining of glass fibre reinforced polymer (GFRP) is one of the challenging tasks given its non-linear and in-homogeneous properties. In this investigation, newly developed threaded and unthreaded nozzles in machining were used for making holes on the GFRP composites.

Significant effort has been made to support pre-service and novice teacher learning in the K-12 context. Less attention has been paid to promoting pre-service and novice second language teacher learning via collaboration with peers and more expert educators at the university level. In order to facilitate this type of teacher collaboration, a mentoring project was incorporated into the existing practicum of a Master of Arts in Teaching English as a Second Language (ESL) program at a US University. The purpose of this paper is to examine the nature of the mentoring experiences of four ESL mentor-pre-service teacher pairs in the US University context.

For this research project, eight teachers – four mentor-pre-service teacher pairs – participated as pairs in mentoring sessions focussed on activities such as co-planning, co-teaching, and co-reflecting on teaching. Informed by a sociocultural perspective on teacher learning (Vygotsky, 1978), this study presents case studies of all four pairs in order to demonstrate the complex nature of mentoring. The data analysis focussed on the content of the teachers’ interactions and their perceptions of the mentoring experience.

The study traced the developmental trajectories of the participating teachers over one 15-week academic semester. The study uncovered some critical contradictions that the participants encountered during the mentoring experience, thus pointing to its complexity. The study also uncovered the varied nature of mentoring: whereas in one pair the mentor acted as a more expert other (Vygotsky, 1978), in another pair, the mentoring relationship was more reciprocal.

This study showed that pre-service teachers can develop further through mentoring. Such mentoring can help teachers gain confidence and share teaching strategies. At the same time, the study revealed certain challenges associated with introducing a mentoring project in a pre-service teacher practicum. It is recommended that program faculty as a whole read the rich dialogues produced by participating teachers engaged in relationships focussed on collaborative learning, thereby discovering a foundation for revisions that go beyond individual teaching practices to the programmatic level.

This study’s principal contribution to the field is that it showcases the complex nature of mentoring experiences and the ways in which they differ from each other.

In this article we compare the performance of the traditional CAPM with the multi factor model of Fama and French (1996) for equities listed in the Shanghai Stock Exchange. We also investigate the explanatory power of idiosyncratic volatility and respond to the claim that multi factor model findings can be explained by the turn of the year effect. Our results show that firm size, book to market equity and idiosyncratic volatility are priced risk factors in addition to the theoretically well specified market factor. As far as the turn of the year effect is concerned we reject the claim that the findings are driven by seasonal factors.

This paper aims to identify the role of internet of things (IoT) in water supply chain management and helps to understand its future path from the junction of computer science and resource management.

The current research was studied through bibliometric review and content analysis, and various contributors and linkages were found. Also, the possible directions and implications of the field were analyzed.

The paper’s key findings include the role of modern computer science in water resource management through sensor technology, big data analytics, IoT, machine learning and cloud computing. This, in turn, helps in understanding future implications of IoT resource management.

A more extensive database can add up to more combinations of linkages and ideas about the future direction. The implications and understanding gained by the research can be used by governments and firms dealing with water management of smart cities. It can also help find ways for optimizing water resources using IoT and modern-day computer science.

This study is one of the very few investigations that highlighted IoT’s role in water supply management. Thus, this study helps to assess the scope and the trend of the case area.

The main aim of this paper is to design a technique for improving the quality of EEG signal by removing artefacts which is obtained during acquisition. Initially, pre-processing is done on EEG signal for quality improvement. Then, by using wavelet transform (WT) feature extraction is done. The artefacts present in the EEG are removed using deep convLSTM. This deep convLSTM is trained by proposed fractional calculus based flower pollination optimisation algorithm.

Nowadays' EEG signals play vital role in the field of neurophysiologic research. Brain activities of human can be analysed by using EEG signals. These signals are frequently affected by noise during acquisition and other external disturbances, which lead to degrade the signal quality. Denoising of EEG signals is necessary for the effective usage of signals in any application. This paper proposes a new technique named as flower pollination fractional calculus optimisation (FPFCO) algorithm for the removal of artefacts from EEG signal through deep learning scheme. FPFCO algorithm is the integration of flower pollination optimisation and fractional calculus which takes the advantages of both the flower pollination optimisation and fractional calculus which is used to train the deep convLSTM. The existed FPO algorithm is used for solution update through global and local pollinations. In this case, the fractional calculus (FC) method attempts to include the past solution by including the second order derivative. As a result, the suggested FPFCO algorithm approaches the best solution faster than the existing flower pollination optimization (FPO) method. Initially, 5 EEG signals are contaminated by artefacts such as EMG, EOG, EEG and random noise. These contaminated EEG signals are pre-processed to remove baseline and power line noises. Further, feature extraction is done by using WT and extracted features are applied to deep convLSTM, which is trained by proposed fractional calculus based flower pollination optimisation algorithm. FPFCO is used for the effective removal of artefacts from EEG signal. The proposed technique is compared with existing techniques in terms of SNR and MSE.

The proposed technique is compared with existing techniques in terms of SNR, RMSE and MSE.

100%.

Electric vehicles are well known for a silent and smooth drive; however, their presence on the road is difficult to identify for road users who may be subjected to certain incidences. Although electric vehicles are free from exhaust emission gases, the wear particles coming out from disc brakes are still unresolved issues. Therefore, the purpose of the present paper is to introduce a smart eco-friendly braking system that uses signal processing and integrated technologies to eventually build a comprehensive driver assistance system.

The parameters obstacle identification, driver drowsiness, driver alcohol situation and heart rate were all taken into account. A contactless brake blending system has been designed while upgrading a rapid response. The implemented state flow rule-based decision strategy validated with the outcomes of a novel experimental setup.

The drowsiness state of drivers was successfully identified for the proposed control map and set up vindicated with the improvement in stopping time, atmospheric environment and increase in vehicle active safety regime.

The present study adopted a unique approach and obtained a brake blending system for improved braking performance as well as overall safety enhancement with rapid control of the vehicle.