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Given the continuing need to study service marketing adaptations that emerged in the wake of Covid-19, this paper aims to look at the formation and evolution of purchase groups (PGs) that arose in Indian gated communities during the pandemic and have continued functioning in the post-pandemic marketplace. Not only did these groups act as much-needed interstitial markets during a time of significant external disruption, but they also served as sites of value co-creation, with consumers collaborating with each other and with service providers.

Using a phenomenological research approach, the authors conducted 22 in-depth interviews with Indian consumers and small service providers to gather accounts of how PGs started and evolved with time. Subsequent data coding and analyses are conducted with NVivo 12.

Using the service ecosystem perspective, the authors illustrate seven distinct themes that capture the nuances of the formation and evolution of PGs. These consist of entrepreneurality, collectivity, and fluidity at the service ecosystem level, hybridity and transactionality at the servicescape level, and mutuality and permeability at the service encounter level.

This study provides an empirical and theoretically grounded account of a long-term service marketing adaptation that has persisted in the post-pandemic marketplace. This helps us address recent calls for such research while also adding to the work on value co-creation in collective consumption contexts and extant discourse on service ecosystems.

The sharp increase in interest in social networks among marketing scholars and practitioners has coincided with the rapid proliferation of social networks among broader populations. Considering the substantial body of research that has emerged, it is an opportune time to reflect on the state of social network research (SNR) in marketing. Therefore, this chapter reviews recent marketing research, organized according to substantive areas of interest, followed by a discussion of critical dimensions of SNR for researchers, including network actor characteristics, modes, boundaries, impacts, and mechanisms, as well as the relevant level of analysis. By documenting how SNR can inform marketing decisions and influence marketing outcomes, this study also establishes recommendations for research to advance the state of SNR in marketing. A 2 × 2 classification schema reveals four categories that might guide scholars' choices of research designs, theories, constructs, and measures for SNR.

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.

Manufacturers and remanufacturers strive to maximize supply chain effectiveness by eliminating wastes in all their forms. This line of research extends the effectiveness during the products' working lives. Fraud in the warranty service chain (WSC) is one such source of waste that leads to revenue losses in the short term but when left unchecked leads to far worse results in the long term. Warranty frauds in the new product industry have received significant attention in recent literature. Addressing fraud issues in the remanufacturing industry have not been a high priority. Previous studies considered the primary parties in the WSC as possible sources of fraud. However, several unique opportunities exist for the secondary parties when it comes to fraud. This chapter considers fraud originating from one of the secondary parties of the WSC, namely the warranty administrator. The chapter models this fraud scenario using discrete event simulation and explores a possible fraud mitigation scenario.

The purpose of this paper is to propose a structured multilevel system that will distinguish the anomalies present in different online social networks (OSN).

Author first reviewed the related work, and then, the research model designed was explained. Furthermore, the details regarding Levels 1 and 2 were narrated.

By using the proposed technique, F_Score obtained for Twitter and Facebook data set was 96.22 and 94.63, respectively.

Four data sets were used for the experiment and the acquired outcomes demonstrate enhancement over the current existing frameworks.

This paper designed a multilevel framework that can be used to detect the anomalies present in the OSN.

One of the important key components of health care–based system is a reliable intrusion detection system. Traditional techniques are not adequate to handle complex data. Also, the diversified intrusion techniques cannot meet current network requirements. Not only the data is getting increased but also the attacks are increasing very rapidly. Deep learning and machine learning techniques are very trending in the area of research in the area of network security. A lot of work has been done in this area by still evolutionary algorithms along with machine learning is very rarely explored. The purpose of this study is to provide novel deep learning framework for the detection of attacks.

In this paper, novel deep learning is the framework is proposed for the detection of attacks. Also, a comparison of machine learning and deep learning algorithms is provided.

The obtained results are more than 99% for both the data sets.

The diversified intrusion techniques cannot meet current network requirements.

The data is getting increased but also the attacks are increasing very rapidly.

Deep learning and machine learning techniques are very trending in the area of research in the area of network security.

Novel deep learning is the framework is proposed for the detection of attacks.

In recent times, reverse logistics (RL) is gaining significant traction in various automobile industries to recapture returned vehicles’ value. A good RL program can lower manufacturing costs, establish a green supply chain, enhance customer satisfaction and provide a competitive advantage. However, reducing disruptions and increasing operational efficiency in the automobile RL requires implementing innovative technology to improve information flow and security. Thus, this manuscript aims to examine the hurdles in automobile RL activities and how they can be effectively tackled by blockchain technology (BCT). Merging BCT and RL provides the entire automobile industry a chance to generate value for its consumers through effective vehicle return policies, manufacturing cost reduction, maintenance records tracking, administration of vehicle information and a clear payment record of insurance contracts.

This research is presented in three stages to accomplish the task. First, previous literature and experts' opinions are examined to highlight certain factors that are an aggravation to BCT implementation. Next, this study proposed an interval-valued intuitionistic fuzzy set (IVIFS) – decision-making trial and evaluation laboratory (DEMATEL) with Choquet integral framework for computing and analyzing the comparative results of factor interrelationships. Finally, the causal outline diagrams are plotted to determine the influence of factors on one another for BCT implementation in automobile RL.

This study has categorized the barriers to BCT implementation into five major factors – operational and strategical, technical, knowledge and behavioral, financial and infrastructural, and government rules and regulations. The results revealed that disreputable technology, low-bearing capacity of IT systems and operational inefficiency are the most significant factors to be dealt with by automobile industry professionals for finer and enhanced RL processes utilizing BCT. The most noticeable advantage of BCT is its enormous amount of data, permitting automobile RL to develop client experience through real-time data insights.

This study reveals several factors that are hindering the implementation of BCT in RL activities of the automobile industry. The results can assist experts and policymakers improve their existing decision-making systems while making an effort to implement BCT into the automobile industry's RL activities.

Although there are several studies on the benefits of BCT in RL and the adoption of BCT in the automobile industry, individually, none have explicated the use of BCT in automobile RL. This is also the first kind of study that has used IVIFS-DEMATEL with the Choquet integral framework for computing and analyzing the comparative results of factor interrelationships hindering BCT implementation in automobile RL activities.

Drawing from our current original research on cultural trends in Latin America‐based multinational firms, this paper challenges the stereotypical perception of Latin America as a homogeneous region and explores the cultural distances among groups of multinational employees. After collecting surveys from 733 employees across eight multinationals in Argentina, Brazil, Chile, Colombia, and Mexico, we establish that, much like it happens in other lumped‐together regions of the globe, such as “East Asia” and “Africa”, Latin American countries present significant differences in the way firm employees respond to situations where cultural traits are at stake. By researching these countries, we recorded significant variation in aspects such as the treatment and place of women in the workplace, attachment or detachment to formal rules, formal organizational hierarchies, and structured business planning, in addition to varying levels of tolerance to invasion of privacy. Implications of the study include the need to develop methodologies that adequately capture cultural differences within large geographic blocs and business practices that prepare the expatriate, the international manager, and the policy maker for the different realities they are bound to encounter in different countries.