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The relationship between the various existing smell taxonomies and the smell impacting factors has been established. The ideology is to identify the most critical smell influencing factors in the vicinity of various software development environments.

To fulfill the said task, the utilization of the amalgamation of two multicriteria decision-making techniques, namely, Entropy method and CODAS method, is presented.

Through this article, the most critical smell impacting criteria with respect to the smell taxonomies is identified. Furthermore, the behaviour of 4 software development principles was then analysed, and their working state has been successfully assessed.

The ideology to study design-related smells in the software system has been studied by a lot of researchers. Some of them have worked upon their detection and the corresponding refactoration process with the help of several algorithms like machine learning and artificial intelligence. But how and to what extent these design-related smells impact the software development environment has remained out of the limelight till now. Through this article, this research gap has been identified, and an attempt to fill it has been made.

The ideology of this article is to study the performance concerns of SDN Controllers, with the help of developed SRGM and thereby obtain its optimal testing duration. The effect of undetected uncertainty in the parameter values have also been catered in the proposal.

These uncertainties in the parameter values are studied as the risk of not meeting desired set of requirements, whose removal causes additional cost. Considering these two constructs as attributes of MAUT, the controller's optimal testing duration is obtained.

The article focuses towards obtaining the optimal duration for which the SDN Controllers must be tested. It was observed that the inculcation of risk-attribute has provided the higher utility value as compared to any other existing scenarios.

Plenty of SRGM have been proposed in the literature which talks about the testing stop time determination problems. But, none of them have considered the impact of risk of not meeting the requirements (reliability) along with cost to obtain its testing stop time. Further, validation of the proposed model in presented with the help of two releases versions of SDN controller platform, ONOS, entitled as “Kingfisher” and “Loon” and has acquired promising results.

This paper aims to assess the relationships amongst the tearing strength of fabrics after each chemical processing stage and after finishing of plain-woven cotton fabric. An effort has been made to study the effect of different finishing chemicals (tear improver) and their different concentrations on the high-density fabric tear strength and its sub-component with respect to the co-efficient of friction value of yarns for all the fabric samples. It also aims to establish a statistical model for prediction of tear strength with identified parameters as yarn–yarn friction co-efficient, yarn pullout force and single yarn strength.

In case of woven fabrics, it cannot be assumed that only yarn friction plays the role in deciding fabric-tearing strength. Whether the static or kinetic frictions need to be considered or the linear or capstan frictions have to be analyzed, to incorporate the results of friction analysis in the tearing behavior, need to be assessed. In the present work through a fabrication of yarn–yarn friction measurement, under a synchronized slow speed as that of actual fabric tearing (50 mm/min), has been carried out. After each wet processing stage, surface characteristics of yarns have been changed. Surface of yarns becomes smoother after finishing and rough after dyeing, which affects the co-efficient of friction of yarns, accordingly.

After each wet processing stage, the surface characteristics of yarns are changed. Surface structure of yarns becomes smooth after finishing and rough after dyeing, which affects the co-efficient of friction of yarns. For all the fabrics, the weft-way tearing strength is always higher than warp-way tearing strength. It is also observed that yarn pullout force is not the only responsible factor for tearing strength of such fabric. It is because of the combined action of yarn–yarn friction, yarn pullout force and single yarn strength for a given structure.

A more extensive investigation with respect to concentration as well as further variety of chemicals requires to be identified for the optimum concentration level for each chemical. A mathematical model based on the three parameters as yarn–yarn co-efficient of friction, yarn pullout force and yarn strength for all woven fabric structure to achieve optimum strength level has been established which could be further extended for each fabric structures.

The problem has been identified from the day-to-day exercise of the commercial textile industry. The whole of the sample preparations have been done in the industry by using commercial machines under standard industrial conditions. The findings have been discussed and suitably introduced in the industry.

The whole of this paper has been unique in idea origination, sample preparation and execution of tests. The findings are very important for the researchers as well as for textile industry.

After completion of the case study, students will be able to critically appraise the strategic growth opportunities of an “eating out” industry brand; evaluate the role of customer relationship and retention management in sustaining a brand; and analyse the importance of developing core competencies for long-term business viability.

Since its inception in 2017, Urban Chowk was one of the pioneer places that successfully managed to create a hospitality format called “food and lifestyle park” which combined multiple food brands with good ambience and entertainment, all under the same roof. Although Urban Chowk was one of the popular brands in the given format, its USP was not difficult to challenge or copy. The owner, Mr Kartikey Rajput, anticipated a deluge of similar establishments in the near future. Urban Chowk led the pack in terms of footfalls compared to similar establishments, with Rajput looking to expand his brand beyond Ahmedabad. The case took 2022 as the timeline and brought forth the challenge that Urban Chowk faced. The primary challenge was retaining the existing customer base along with adding newer ones. Second, with the industry being extremely dynamic, it was important to determine how marketing analytics could be used to collect customer data and convert them into repeat customers, thus building a loyal customer base.

This case is applicable for teaching at undergraduate and graduate levels for understanding the concepts of brand development and strategic growth as well as creating and maintaining customer relationships, also helping the students in assimilating these concepts as a part of brand building.

Teaching notes are available for educators only.

CSS 11: Strategy.

Mohan Dixit, Head, Sales and Marketing, India Operations, EuroMotoCorp Pvt. Ltd., an automobile manufacturing multinational company headquartered in Munich, Germany. This case outlines the harried nature of his life: professional problems (decrease in the market share, not being able to say ‘no’, unable to delegate, pressed for time, member of too many committees) and personal issues (weight gain, not able to spend time for his personal interests) and family problems (work-life balance issue). The case can be taught through different angles, including individual behaviour, transaction analysis, time and stress management, career management and general management. Apart from this, the case discusses the emotional instability of Dixit and the automatic cycle of behavior of Dixit in various situations and events. The case also discusses the ‘ego-self’ and the ‘natural—self’ of a person and how the two should be balanced for a good quality of life. The case thus delves deep into the psychology of a person and discusses how his/her thoughts or inner talk should be managed for a content and successful personal and professional life.

This study aims to examine the effect of perceived supervisor support (PSS) and workplace dignity (WPD) on employees' affective commitment to change (ACC). It also investigates PSS as an antecedent of WPD and WPD as a mediator between PSS and ACC.

To examine the proposed relationships, data was collected from employees of an Indian public sector company undergoing many change initiatives at the time of the study. The hypotheses were tested using the structural equation model.

The findings indicate the direct effect of PSS and WPD on employees' ACC, and WPD does mediate between PSS and ACC. The results also suggest PSS works as an antecedent of WPD.

The findings suggest how organizations can enhance employees’ ACC by creating a positive context involving supervisor support and experience of WPD.

The findings contribute to ACC literature by highlighting the role of WPD and PSS. This is one of the few quantitative studies which examines the antecedent and consequences of WPD.

The case describes the predicament of Aditya Kumar, Vice President of Marketing at Green Living India Technologies Private Limited (GLIT), an organisation working in arena of sustainable products and technology. Aditya Kumar, who has had an excellent academic background and a fast track promotion after seven months of joining the company, is harshly criticized by his boss Rajiv Nanda, Chief Marketing Officer. Aditya Kumar and Rajiv Nanda have different personalities and work styles. Aditya has a different opinion for some of Rajiv's initiatives and he does not agree to Rajiv's revenue projections which he finds to be over-estimated. Aditya has succeeded in his previous role but he has failed to adapt his work style and establish an effective relationship with his new boss that may lead to his position being removed from the organisation.

The case describes the dilemma faced by Meera Nair, chief manager at PhoenixWay – a consultancy firm that has successfully grown over the years. There is a silent conflict in the personalities, work styles and attitude of Meera Nair and Mohit Dubey, her contemporary looking after client relationships. Nair finds inconsistencies in the words and actions of Dubey that have started to impact the work and motivation of her team. Her unsuccessful attempts to draw the attention of their boss Shekhar Sinha to these variances have left her unsure and demotivated. Sinha overlooks Dubey's fallacies and shows no signs of paying attention to the discrepancies and contradictions.

The ‘CSIR-Tech: Facilitating lab to market journeys’ case is designed to teach students the strategic intricacies of an organizational network. The case also throws light on the formation and design of a collaborative inter-organizational network. CSIR, a premier R&D organization in India, was plagued with challenges in the commercialization of technologies developed in its constituent laboratories. CSIR-Tech was established as a private-limited company to catalyse the technology development and commercialization process. The case analyses formation of CSIR-CSIR-Tech alliance and discusses how the alliance can help in overcoming challenges associated with commercialization of technologies being developed at CSIR.

This paper aims to propose a statistical and context-aware feature reduction algorithm that improves sentiment classification accuracy. Classification of reviews with different granularities in two classes of reviews with negative and positive polarities is among the objectives of sentiment analysis. One of the major issues in sentiment analysis is feature engineering while it severely affects time complexity and accuracy of sentiment classification.

In this paper, a feature reduction method is proposed that uses context-based knowledge as well as synset statistical knowledge. To do so, one-dimensional presentation proposed for SentiWordNet calculates statistical knowledge that involves polarity concentration and variation tendency for each synset. Feature reduction involves two phases. In the first phase, features that combine semantic and statistical similarity conditions are put in the same cluster. In the second phase, features are ranked and then the features which are given lower ranks are eliminated. The experiments are conducted by support vector machine (SVM), naive Bayes (NB), decision tree (DT) and k-nearest neighbors (KNN) algorithms to classify the vectors of the unigram and bigram features in two classes of positive or negative sentiments.

The results showed that the applied clustering algorithm reduces SentiWordNet synset to less than half which reduced the size of the feature vector by less than half. In addition, the accuracy of sentiment classification is improved by at least 1.5 per cent.

The presented feature reduction method is the first use of the synset clustering for feature reduction. In this paper features reduction algorithm, first aggregates the similar features into clusters then eliminates unsatisfactory cluster.