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This paper aims to, first, analyze the transformation of the Indian market by extending Sreekumar and Varman’s (2016) work on history of marketing in India into the post-colonial era; second, trace the emergence and adoption of various media technologies in the post-colonial Indian market; third, identify the evolving trends in marketing practices alongside the penetration of these media technologies in the market; and finally, argue the need for mindful adoption of marketing practices in the Indian market, rather than direct replication of Western practices.

The historical perspective on the post-colonial Indian market is done through extant literature review and analysis of marketing practices by iconic brands in the Indian market.

This research reveals that the adoption of Western marketing practices by brands in the Indian market has led to increasing materialistic consumption patterns among consumers. Furthermore, such practices in the social media technology era impose individualistic values in the Indian consumers, contrary to the cultural values of the country. Therefore, this research posits the need for mindful marketing practices to be adopted for the Indian market.

This research shows warning signs of growing materialistic values among Indian consumers and the implications of marketing strategies on the society as a whole.

This study is a first of its kind in highlighting the transformation of the post-colonial Indian market by integrating actual marketing campaigns over this period with literature to present the various issues in the current state of the market.

The authors investigate whether firms in learning-intensive industries are more prone to bankruptcy and how this shapes a firm's financing choices.

Industry learning estimates based on US manufacturing firms are obtained from the study of Balasubramanian and Lieberman (2010; 2011), who collected these estimates from the US Census Bureau. Merging the learning estimates with data from Compustat gives us a final sample of 6,138 publicly-traded US manufacturing firms (56,930 firm-years) between 1973 and 2000. The authors use both OLS and IV estimation approaches to test the hypotheses.

The findings confirm that firms operating in learning-intensive industries have a higher threat of bankruptcy. The authors also find that a debt-intensive capital structure exacerbates the threat of bankruptcy; therefore, firms in such industries have a significantly lower reliance on debt financing.

In the current turbulent business environment, managers operating in learning-intensive industries need to be more careful while making financing choices between debt and equity, and they can explore sources of financing that go beyond the capital markets.

No study so far has examined how industry learning intensity, a key industry characteristic, makes firms more prone to bankruptcy, and how this threat of bankruptcy results in more conservative financing choices. By integrating the theoretical perspectives from the structure–conduct–performance (SCP), transaction cost economics (TCE) and threat rigidity paradigms, this paper contributes to the literature by adding the industry learning environment as a novel determinant of firm financing choices and the threat of bankruptcy.

This paper aims to propose a system to acquire images automatically for digital reconstruction of heritage artifacts using a six-degree of freedom industrial manipulator.

A virtual environment is created using Robot Studio® software to integrate the trajectory and differential motion of the robot manipulator and the motion of camera while acquiring images. A new area similarity matrix method is proposed to reduce the number of images required for digital reconstruction using Autodesk Recap® software. Real-time experiments have been performed using objects such as minion, ultimaker robot and cube. Evaluation of the digital reconstruction is conducted using the contour area matching method.

The number of images required for reconstruction based on area similarity matrix method is reduced to 63 per cent when compared with the random selection method. Quality parameters such as surface area, volume, number of defect holes, vertices and faces are enhanced for the proposed method.

Digital reconstruction of large-sized heritage artifacts cannot be performed in this setup. But this can be overcome by fixing the manipulator on a mobile platform or overhead crane. This paper does not discuss the reconstruction of partially damaged heritage artifacts, which could be accomplished based on deep learning techniques.

Using this approach, off-the-shelf heritage artifacts and large-scale objects can be reconstructed digitally with a minimum number of images and without compromising the quality of original models.

To the best of the authors’ knowledge, area similarity-based approach in 3D digital reconstruction by coupling the kinematics of an industrial manipulator and camera is proposed for the first time. A fully automated digital reconstruction technology to preserve valuable heritage artifacts has been developed. It also highlights the space constraints of the industrial manipulator in digital reconstruction.

The purpose of this paper is to provide a perspective on consumers and technology in a changing world using insights gained from subsistence marketplaces. Consumers in a changing world are on different parts of the economic spectrum and are also reflected in contexts of poverty that is termed subsistence marketplaces. “Data” comes from pioneering the subsistence marketplaces stream of research, education and social enterprise.

The authors study the intersection of poverty and marketplaces, beginning at the micro-level, and take a bottom-up approach to deriving implications.

The authors cover both aspects – what micro-level insights about thinking, feeling and coping mean for technology perceptions and usage in general and what specific insights are derived for designing and implementing solutions that have bearing on the use of technology. In the course of all endeavors in research, education and social enterprise, technology, particularly information and communications technology, has been central.

The authors discuss implications for research at the confluence of a variety of uncertainties inherent in the context of subsistence marketplaces, in environmental issues and climate change and in the nature and speed of technological change and progress.

In this paper, the authors discuss what subsistence marketplaces mean for consumers and technology in a changing world, lessons learned for the design and development of technological solutions, technological innovation from subsistence marketplaces and a broader discussion of the importance of bottom-up approaches to the intersection of subsistence marketplaces and technological solutions.

The authors use insights developed from pioneering the arena of subsistence marketplaces and creating synergies between research, education and social enterprise.

Subsistence marketplace can be characterized as a marketplace with widespread cognitive and social vulnerabilities, due to low income and low literacy levels. This may result in retailers exploiting the consumers. The purpose of this research paper is to develop a holistic learning program to impart marketplace intelligence to overcome these vulnerabilities of subsistence consumers.

Using vicious cycle approach, the authors illustrate the self-perpetuating nature of consumer vulnerabilities. The authors argue that retailers behave in an opportunistic manner and exploit the consumers. This further reinforces the vulnerabilities of subsistence consumers resulting in a vicious cycle. The authors draw insights from Sen’s capability approach and propose marketplace intelligence as a potential solution to eradicate consumers’ vulnerabilities. The authors apply Biggs’s 3Ps model to design a learning program to impart two types of marketplace intelligence – marketplace metacognition and marketplace social intelligence.

Based on a review of literature on subsistence marketplace initiatives, persuasive knowledge management and education research, the authors have devised a holistic learning program comprising an integrated learning environment (presage), problem-based approach (process) and assessment strategies for learning outcomes (product).

This study marks a pioneering effort toward liberating subsistence consumers from the vicious cycle of retailers’ exploitation by empowering them with marketplace intelligence. This study’s novelty lies in conceptualizing consumer vulnerabilities in the subsistence marketplace as a self-perpetuating phenomenon and subsequently designing a holistic learning program to impart intelligence toward alleviating these vulnerabilities.

This article attempts to highlight the defining role that community media engagements play during times of the pandemic. It is argued that the outbreak of COVID-19 pandemic forced community news media houses to reinvent their news reporting practices to cover issues pertaining to the marginalized and underprivileged sections of the society. It explores the role of community media in engaging and empowering the citizens during the COVID-19 pandemic.

Central to our study is the analysis of the news model of “Video Volunteers” (henceforth VV), an independent community-based online news platform based in India. To understand the level of citizen participation and engagement in the making and dissemination of news during the pandemic, the authors conducted 13 interviews with different stakeholders of VV, including founders and news audiences.

It seeks to reveal that when the mainstream media have failed to represent the issues of a local community, it is the independent media platforms like VV which function as a veritable source of information and sharing of knowledge. Most importantly, this paper emphasizes that the communicative model of independent community-based online platforms has been most successful in the coverage of the pandemic and the level of engagement with the citizenry.

The study contributes to the aspects of reciprocity and collaborative journalism in community news media and its potential impacts on news creation and dissemination.

The purpose of this paper is to provide an advertising history of Tata Steel from its inception in 1907 to 2007 when it completed 100 years of operation. The authors use postcolonial theory to highlight the intertwining of advertising with the broader project of anticolonial resistance and postcolonial nation-building.

The authors used a visual analysis of a compilation of advertisements published by Tata Steel to commemorate 100 years of its existence, spanning the years from 1907 to 2007. They also used ads and posters available on the website of the Tata Steel Archives. Published work on Tata Steel such as books and papers provided contextualization.

Advertising creatives, through selective deployment of anticolonial discourses, manage the contradictory pulls of emergent nationalism on the one hand and the pragmatic need to work with the colonial administration on the other. However, such a negotiation leads to moments of slippage, where advertising reinforces colonial tropes. At a broader level, the authors suggest that despite attempts to draw on subversive discourses of resistance used by nationalists, Tata Steel’s advertising is inescapably intertwined with the larger matrix of colonial and capitalist power.

This study contributes to a non-Western perspective on advertising history. Further, it provides understanding of the marketing activities of a large corporation, which straddles the colonial and postcolonial era of India, an important economy.

The purpose of this paper is to examine the extent to which self-reported resilience was associated with mental health outcomes four years after the Deepwater Horizon oil spill (DWHOS).

Participants included 179 men and women randomly selected from two Northeast Gulf Coast communities as part of a larger, prospective study of behavioral health post oil spill. The majority of the participants were Caucasian (70.8 percent), female (61.5 percent), had a high school education or lower (75.3 percent), and ranged in age from 18 to greater than 60 years old. Participants completed a measure of resilience (Connor-Davidson Resilience Scale, CD-RISC) 2.5 years post oil spill and measures of overall mood disturbance (Profile of Mood States), depression (Beck Depression Inventory), quality of life (World Health Organization Quality of Life-BREF Scale) 4.5 years post oil spill.

Based upon linear regression analyses, elevated self-reported resilience significantly predicted lower scores on mood disturbance (b=−0.63, p<0.01) and depressive symptoms (b=−0.14, p<0.05) and higher scores on psychological (b=0.08, p<0.01) and overall health quality of life (b=0.08, p<0.01). Factor analysis of the CD-RISC identified three factors (hardiness, adaptability, optimism). Each factor predicted some, but not all, of the outcomes with optimism being the least predictive of mental health.

Self-reported resilience two years after the DWHOS was a useful predictor of mental health outcome four years post-spill. Early assessment may facilitate the identification of individuals at risk of longer-term mental health problems for public health prevention or mental health intervention efforts.

The purpose of this paper is to review the key literature pertaining to consumption during the colonial period in India, broadly covering the time period from the early nineteenth century to the middle of the twentieth century. The review shows the prominent themes and patterns that help us understand colonial Indian consumers’ encounter with Western products and institutions.

The paper is a review of historical research papers and papers pertaining to the colonial period in India.

British colonialism introduced new products, institutions and ways of living into India, which were negotiated with and contested by Indian consumers and intellectuals. These new products and practices were not seamlessly adopted into the Indian context. Rather, they were appropriated into existing social structures determined by caste, gender and religion. The tensions produced by such negotiations and contestations fed Indian resistance to colonialism, culminating in British withdrawal from India.

Historical research pertaining to marketing in the Indian context is scarce. Moreover, there are few reviews which outline the important consumption practices and changes pertaining to the colonial period. The findings of this review will be of use to researchers and students of history, marketing and cultural studies.

The main purpose of the present study is to develop an integrated approach combining data envelopment analysis (DEA) and neural network (NN) for assessment and prediction of performance of Indian B‐schools for effective decision making as error and biasness due to human intervention in decision making is appreciably reduced.

DEA, being a robust mathematical tool, has been employed to evaluate the efficiency of B‐schools. DEA, basically, takes into account the input and output components of a decision‐making unit (DMU) to calculate technical efficiency (TE). TE is treated as an indicator for performance of DMUs and comparison has been made among them. A sensitivity analysis has been carried out to study robustness of the ranking of schools obtained through DEA. Finally, NN is used to predict the efficiency when changes in inputs are caused due to market dynamism so that effective strategies can be evolved by the managers with limited available data.

A total of 49 Indian B‐schools are chosen for benchmarking purpose. The average score of efficiency is 0.625 with a standard deviation of 0.175 when Charnes, Cooper and Rhodes (CCR) model is used. Similarly, when the Banker, Charnes and Cooper (BCC) model is used the average score is 0.888 with a standard deviation of 0.063. The rank order correlation coefficient between the efficiency ranking obtained through CCR and BCC model is 0.736 (p=0.000) which is significant. The peer group and peer weights for the inefficient B‐schools have been identified. This is useful for benchmarking for the inefficient DMUs. They can identify the parameters in which they lack and take necessary steps for improvement. The peer group for the inefficient B‐schools indicates the efficient B‐schools to which the inefficient B‐schools are closer in its combination of inputs and outputs. The TE obtained through DEA is used as output variable along with input variables considered in DEA as input and output parameters in a generalized regression NN during training phase. It can be observed that root mean square error is 0.009344 and 0.02323 for CCR‐ and BCC‐efficiency prediction, respectively, during training. Similarly, root mean square error is 0.08585 and 0.03279 for CCR‐ and BCC‐efficiency prediction, respectively, during testing. Now, individual schools can generate scenario with the data within their control and test their own performance through NN model.

This work proposes integration of DEA and NN to assist the managers to predict the performance of an individual DMU based on input consumed and generate various “what‐if” scenarios. The study provides a simple but comprehensive methodology for improving performance of B‐schools in India.