Ann-Marie Kennedy, Sommer Kapitan, Neha Bajaj, Angelina Bakonyi and Sean Sands
This paper aims to use systems thinking, systems theory and Camillus’ framework for responding to wicked problems to provide social marketers with a theoretically based framework…
Abstract
Purpose
This paper aims to use systems thinking, systems theory and Camillus’ framework for responding to wicked problems to provide social marketers with a theoretically based framework for approaching strategy formation for wicked problems. The paper treats fast fashion as an illustrative case and takes a step back from implementation to provide a framework for analysing and gaining understanding of wicked problem system structure for social marketers to then plan more effective interventions. The proposed approach is intended as a theory-based tool for social marketing practitioners to uncover system structure and analyse the wicked problems they face.
Design/methodology/approach
Following Layton, this work provides theoretically based guidelines for analysing the black box of how to develop and refine strategy as first proposed in Camillus’ (2008) framework for responding to wicked issues.
Findings
The prescription thus developed for approaching wicked problems’ system structure revolves around identifying the individuals, groups or entities that make up the system involved in the wicked problem, and then determining which social mechanisms most clearly drive each entity and which outcomes motivate these social mechanisms, before determining which role the entities play as either incumbent, challenger or governance and which social narratives drive each role’s participation in the wicked problem.
Originality/value
This paper shows that using systems thinking can help social marketers to gain big picture thinking and develop strategy for responding to complex issues, while considering the consequences of interventions.
Details
Keywords
Neha Kalra, Pankaj Deshwal, Samir Gokarn and Shiksha Kushwah
The proliferation of technological advancements has facilitated unrestricted access to and customizable consumption of content for viewers. Over-the-top (OTT) services are…
Abstract
Purpose
The proliferation of technological advancements has facilitated unrestricted access to and customizable consumption of content for viewers. Over-the-top (OTT) services are becoming more and more popular as the number of people using video streaming services grows around the world. In this context, this study aims to identify the antecedents and outcomes of Customer over-the-top Experience (COTTE) by synthesizing the existing research.
Design/methodology/approach
This research used the systematic literature review approach to identify the antecedents and outcomes of COTTE, along with the publication schedule, theories, analytical techniques, research methodology, and geographic scope of the 47 studies identified from the Scopus and Web of Science database.
Findings
The findings elucidate various antecedents of COTTE, including user-related, social, content-related, and website/platform-related factors. Additionally, diverse outcomes, encompassing behavioural/attitudinal and company-related factors have been discussed. Furthermore, an integrated framework is presented herein, synthesizing extant research and guiding future researchers in this domain.
Originality/value
The study’s findings offer a novel perspective for service providers aiming to enhance the OTT experience for their customers. This study stands out as one of the first to comprehensively present the antecedents and consequences of COTTE.
Details
Keywords
Rashbir Singh, Prateek Singh and Latika Kharb
Internet of Things (IoT) and artificial intelligence are two leading technologies that bought revolution to each and every field of humans using in daily life by making everything…
Abstract
Internet of Things (IoT) and artificial intelligence are two leading technologies that bought revolution to each and every field of humans using in daily life by making everything smarter than ever. IoT leads to a network of things which creates a self-configuring network. Improving farm productivity is essential to meet the rapidly growing demand for food. In this chapter, the authors have introduced a smart greenhouse by integration of two leading technologies in the market (i.e., Machine Learning and IoT). In proposed model, several sensors are used for data collection and managing the environment of greenhouse. The idea is to propose an IoT and Machine Learning based smart nursery that helps in healthy growing and monitoring of the seed. The structure will be a dome-like structure for observation and isolation of an egg with various sensors like pressure, humidity, temperature, light, moisture, conductivity, air quality, etc. to monitor the nursery internal environment and maintain the control and flow of water and other minerals inside the nursery. The nursery will have a solar panel from which it stores the electricity generated from the sun, a small fan to control the flow of air and pressure. A camera will also be equipped inside the nursery that will use computer vision technology to monitor the health of the plant and will be trained on the past data to notify the user if the plant is diseased or need attention.
Details
Keywords
Leela Rani and Sanal Kumar Velayudhan
Purpose – This study aims to examine empirically how consumers' attitude towards retail stores gets affected by situational, consumer, store and product characteristic variables…
Abstract
Purpose – This study aims to examine empirically how consumers' attitude towards retail stores gets affected by situational, consumer, store and product characteristic variables when they face out‐of‐stock situations. Design/methodology/approach – Survey method for data collection was used. Data were collected from a sample of 1,207 retail customers in India's unorganized retail sector across five product categories in Varanasi, India. Findings – Results showed that six of the independent variables considered, namely, shopping attitude of respondent, store loyalty (SL), perceived store prices, store distance, shopping frequency, and brand loyalty (in order of importance of impact) significantly influenced consumers' attitude towards retail store in out‐of‐stock. Research limitations/implications – Data were collected only for five product categories and for unorganized retail setting because of which results and findings are not generalizeable to beyond these boundaries. Practical implications – Implications of this for retailers and future research are discussed. Originality/value – Since attitudes towards retail outlets are very important in determining future SL and subsequent profitability, understanding of consumer store attitudes in negative events like stockout is importantly for retailers. The paper provides crucial insights to retailers by identifying independent variables that must be considered while designing their operations.
Details
Keywords
The body has been one of the central tools in analysing connections between sport and postcolonialism in India, given how sport was an essential part of the colonial ‘civilising’…
Abstract
The body has been one of the central tools in analysing connections between sport and postcolonialism in India, given how sport was an essential part of the colonial ‘civilising’ mission, which involved disciplining and controlling Indian bodies. Any discursive understanding of sport and postcolonialism in India must consider how it relates to existing concepts of the body and shapes the experiences of the people involved in it – acknowledging not just the power of colonialism in moulding sporting experiences but also the force of internal hierarchies that exist in Indian society. This chapter explores the experiences of students who studied in higher educational institutions in Kerala under the ‘sports quota’, a system that reserves seats in colleges/universities for high-performing sportspersons in India. Through their interviews, the sustained exclusion of the sporting body in contemporary Indian pedagogy is illustrated here. Specifically, the continuing prevalence of the colonial emphasis on the sporting body, as one whose strength and instrumentality are paramount, as well as its corollary postcolonial position, which treats this sporting body as inferior to the ‘refined mind’ of studious pupils, can be observed. Approaching the sports quota with a decolonising lens would require re-examining the disembodied nature of pedagogy in India’s higher educational institutions, acknowledging sporting students’ lived experiences, and a seamless integration – as opposed to separation/exclusion – of the sportsperson into higher education.
Details
Keywords
Shruti Garg, Rahul Kumar Patro, Soumyajit Behera, Neha Prerna Tigga and Ranjita Pandey
The purpose of this study is to propose an alternative efficient 3D emotion recognition model for variable-length electroencephalogram (EEG) data.
Abstract
Purpose
The purpose of this study is to propose an alternative efficient 3D emotion recognition model for variable-length electroencephalogram (EEG) data.
Design/methodology/approach
Classical AMIGOS data set which comprises of multimodal records of varying lengths on mood, personality and other physiological aspects on emotional response is used for empirical assessment of the proposed overlapping sliding window (OSW) modelling framework. Two features are extracted using Fourier and Wavelet transforms: normalised band power (NBP) and normalised wavelet energy (NWE), respectively. The arousal, valence and dominance (AVD) emotions are predicted using one-dimension (1D) and two-dimensional (2D) convolution neural network (CNN) for both single and combined features.
Findings
The two-dimensional convolution neural network (2D CNN) outcomes on EEG signals of AMIGOS data set are observed to yield the highest accuracy, that is 96.63%, 95.87% and 96.30% for AVD, respectively, which is evidenced to be at least 6% higher as compared to the other available competitive approaches.
Originality/value
The present work is focussed on the less explored, complex AMIGOS (2018) data set which is imbalanced and of variable length. EEG emotion recognition-based work is widely available on simpler data sets. The following are the challenges of the AMIGOS data set addressed in the present work: handling of tensor form data; proposing an efficient method for generating sufficient equal-length samples corresponding to imbalanced and variable-length data.; selecting a suitable machine learning/deep learning model; improving the accuracy of the applied model.