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The purpose of this paper is to study consumer engagement as a dynamic, iterative process in the context of TV shows. A theoretical framework involving the central constructs of brand actions, customer engagement behaviors (CEBs), and consumption is proposed. Brand actions of TV shows include advertising and firm-generated content (FGC) on social media. CEBs include volume, sentiment, and richness of user-generated content (UGC) on social media. Consumption comprises live and time-shifted TV viewing.

The authors study 31 new TV shows introduced in 2015. Consistent with the ecosystem framework, a simultaneous system of equations approach is adopted to analyze data from a US Cable TV provider, Kantar Media, and Twitter.

The findings show that advertising efforts initiated by the TV show have a positive effect on time-shifted viewing, but a negative effect on live viewing; tweets posted by the TV show (FGC) have a negative effect on time-shifted viewing, but no effect on live viewing; and negative sentiment from tweets posted by viewers (UGC) reduces time-shifted viewing, but increases live viewing.

Content creators and TV networks are faced with the daunting challenge of retaining their audiences in a media-fragmented world. Whereas most studies on engagement have focused on static firm-customer relationships, this study examines engagement from a dynamic, multi-agent perspective by studying interrelationships among brand actions, CEBs, and consumption over time. Accordingly, this study can help brands to quantify the effectiveness of their engagement efforts in terms of encouraging CEBs and eliciting specific TV consumption behaviors.

The purpose of this paper is to explore the interrelationship between television (TV) consumption (viewing ratings), engagement behaviors of different actors on Twitter (TV programs, media, celebrities and viewers) and the content of engagement behaviors (affective, program-related and social content).

TV ratings and Twitter data were obtained. The content of tweets was analyzed by means of a sentiment analysis. A vector auto regression model was used to understand the interrelationship between tweets of different actors and TV consumption.

First, the results showed a negative interrelationship between TV viewing and viewers’ tweeting behavior. Second, tweets by celebrities and media exhibited similar patterns and were both affected mostly by the number of tweets by viewers. Finally, the content of tweets matters. Affective tweets positively relate to TV viewing, and program-related and social content positively relates to the number of tweets by viewers.

The findings help us understand the online engagement ecosystem and provide insights into drivers of TV consumption and online engagement of different actors.

The results indicate that content producers may want to focus on stimulating affective conversations on Twitter to trigger more online and offline engagement. The results also call for rethinking the meaning of TV metrics.

While some studies have explored viewer interactions on Twitter, only a few studies have looked at the effects of such interactions on variables outside of social media, such as TV consumption. Moreover, the authors study the interrelations between Twitter interactions with TV consumption, which allows us to examine the effect of online engagement on offline behaviors and vice versa. Finally, the authors take different actors into account when studying real-life online engagement.

We do not yet have a good understanding of how generation Y makes decisions. Since this segment will soon wield greater influence in the market place, the purpose of this paper is to carry out an exploratory analysis and develop a framework on generation Y decision making.

The dual-system approach states that individuals use a heuristic-based process (system 1) and/or an analytic-based process (system 2) to make decisions. Evidence from six focus group discussions with generation Y is integrated with this approach.

Generation Y has an active heuristic-based system 1. However, they tend not to evaluate options on their own, i.e. system 2 is “lazy”. Instead, friends, family and digital media play the role of a “proxy” system 2.

A limitation is that the study uses data from a small sample of individuals in one country and uses only one methodological approach.

Digital media is a vital component of the analytical “proxy” system 2. Therefore, reallocating advertising efforts from traditional media to digital media is perhaps one reason for declining differentiation between brands. Brands that compete on tangible attributes should target individuals designated as “product experts” by their friends.

The study identifies different factors and the role they play in influencing generation Y's decisions. The paper has important implications for academics and marketers interested in understanding how generation Y makes decisions.

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.

The following are the learning objectives of the case study: to address the problem of urban food insecurity. To facilitate the generation of more employment opportunities and women empowerment through self-help groups (SHGs). To understand the transition from the founder to new leadership provided by Ms J Jayalalithaa. To understand consumer perception and preferences for “Amma canteens”. To appreciate how the case study has added to the historical role of soup kitchens. To address the challenges faced by the government on the sustainability and viability of “Amma canteens” post the death of its founder Ms Jayalalithaa.

“Amma Unavagam” is a food subsidisation programme operated by the State Government of Tamil Nadu in India. Under the scheme, municipal corporations of the state are required to run canteens that serve subsidised food. The canteens were first launched by the then Chief Minister of the state Ms Jayalalithaa, who was widely acknowledged as “Amma”. These low-cost canteens will be announced as part of government schemes aimed to support economically disadvantaged sections of society. The scheme had been able to generate employment for thousands of women. However, the success of the scheme lies in the low prices and the cooperative management of all the outlets by the SHGs. The SHGs have been able to run the canteens based on self-governing norms, mutual reciprocity and shared responsibilities. This case study evaluates the role of state-sponsored mechanisms to ensure food security, alleviate food inflation and empower more women in the workforce. Yet, several concerns continue to remain unaddressed. Considering the huge amount of subsidy provided by the state government, the sustainability and economic viability of the scheme are uncertain.

This case study can be used for management students studying the basics of management such as teamwork, motivation, leadership and good governance. They may also study government policies and community intervention programmes for the benefit of society. The present case study will help the students to analyse the concept of women empowerment and social inclusion. The students, before discussing the case, may study and read the socio-economic theory of “community engagement and participation”, the “self-help model” and the related “theory of reasoned action/planned behaviour”.

Teaching notes are available for educators only.

CSS 6: Human resource management.

In this research, the authors apply artificial neural networks (ANNs) to uncover non-linear relationships among factors that influence the productivity of ragpickers in the Indian context.

A broad long-term action research program provides a means to shape the research question and posit relevant factors, whereas ANNs capture the true underlying non-linear relationships. ANN models the relationships between four independent variables and three forms of waste value chains without assuming any distributional forms. The authors apply bootstrapping in conjunction with ANNs.

The authors identify four elements that influence ragpickers’ productivity: receptiveness to non-governmental organizations, literacy, the deployment of proper equipment/technology and group size.

This study provides a unique way to analyze bottom of the pyramid (BoP) operations via ANNs.

This study provides a road map to help ragpickers in India raise incomes while simultaneously improving recycling rates.

This research is grounded in the stakeholder resource-based view and the network–individual–resource model. It generalizes these theories to the informal waste value chain at BoP communities.

Supply chain strategy is widely recognized as being a crucial component of a broader corporate strategy. However, the relationships between a firm’s strategic supply chain focus, the tactical orientation of its suppliers, and the firm’s performance, are less well understood. Much of what is known is also based on developed country contexts. The purpose of this paper is to empirically examine relationships between a buying firm’s supply chain strategy and operational dimensions of its suppliers in a developing country context.

A structural equation model is developed and tested using empirical data drawn from 296 organizations in India and Pakistan.

The results demonstrate a positive relationship between a firm’s strategic supply chain focus (lean and responsiveness) and key supplier practices (quality, cost effectiveness, delivery, and flexibility), which in turn have a positive impact on firm performance (operational, quality and market, and financial).

The study paper offers supply chain managers in developing markets with insights that can shape effective supplier selection and management and lead to positive performance outcomes.

The results provide insights into supply chain strategy, and empirically validate the importance of the alignment between strategy and the ability of suppliers to execute in a corresponding manner. It also offers evidence of the impact of the buyer-supplier interface in a developing market context.

This paper aims to report on the development of a novel electrochemical amperometric immunosensor to diagnose early hepatocellular carcinoma (HCC) by detecting the Midkine (MDK) biomarker.

Anti-Midkine antibodies were immobilized covalently through carbodiimides chemistry on carbon screen-printed electrodes modified with carboxylated multi-walled carbon nanotubes. The development process was characterized using cyclic voltammetry, electrochemical impedimetric spectroscopy, Fourier transform infrared spectroscopy and atomic force microscopy. Differential pulse voltammetry was used to investigate the immunosensor performance in detecting MDK antigen within the concentration range of 1 pg/ml to 100 ng/ml.

MDK immunosensor exhibited high sensitivity and linearity with a detection limit of 0.8 pg/ml and a correlation coefficient of 0.99. The biosensor also demonstrated high selectivity, stability and reproducibility.

The developed MDK immunosensor could be a promising tool to diagnose HCC and reduce the number of related deaths.