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In assessing the contribution made by telecommunications in India by the state and civil society to public service, this article aims to identify the state's initial reluctance to recognise telecommunications provision as a basic need as against the robust tradition of public service aligned to the postal services and finds hope in the renewal of public service telecommunications via the Right to Information movement.

This article follows a history of telecommunications approach that is conversant with the political economy tradition. It uses archival sources, personal correspondence, and published information as its primary material.

The findings suggest that public service telecommunication is a relatively “new” concept in the annals of Indian telecommunications and that a de‐regulated environment along with the Right to Information movement holds significant hope for making public service telecommunications a real alternative.

This article provides a reflexive, critical account of public service telecommunications in India and suggests that it can be strengthened by learnings gained from the continual renewal of public service ideals and action by the postal services and a people‐based demand model linked to the Right to Information Movement.

Migration is defined as movement of people, especially of whole groups, from one place, region, or country to an other, particularly with the intention of making permanent settlement in a new location (Microsoft Encarta). Migration is as old as the beginnings of human evolution, and in the distant past migrations were localized, slow, and gradual processes taking centuries or even longer to establish significant populations in a given region or country. The populations, therefore, possessed unique and highly homogeneous characteristics of race, religion, culture, traditions, or language. From the oldest periods of civiliza tion, India attracted migrants from different parts of the neighboring regions and continents (notably, Middle east, China, and Africa) owing to its warm weather, wealth of natural resources, spices, and so forth. Like wise, India also be came a prominent country from where people migrated to different parts of the world, first to the neighboring lands (Burma, Indonesia, Malaysia, Thailand, and Bali) and then to distant countries (several African countries, for example, Uganda, South Africa, Mauritius). More recently, migration of Indians has been mostly to the Western Europe and USA.

Timely removal of formwork is one of the crucial aspects of construction management that directly influences the safety and quality of the structure as well as the economy of the project. Code recommendations in this regard are not widely practiced because of the difficulties in their implementations. Also, such code recommendations are not robust for all the possible construction conditions. The present paper proposes an IoT-enabled system that notifies the minimum striking time of vertical formwork based on a specified target compressive strength.

An IoT device is proposed for the timely removal of vertical formwork by monitoring of early age concrete compressive strength in real-time. The maturity method is utilized for this purpose. The implementation of the proposed system is demonstrated on three concrete columns. The proposed system is found to be suitable for any construction condition.

The proposed system is a novel, cost-effective, IoT-enabled real-time monitoring system which includes features like cloud connectivity and remote monitoring. This system can be easily implemented at the site without any human intervention.

The study explores the development of an IoT device for the timely removal of vertical formwork which will ensure quality, safety and productivity in concrete construction.

This paper is the first attempt to determine the minimum striking time of vertical formwork using IoT-based technology.

The best possible way for brick-and-mortar retailers to maximise engagement with personalised shoppers is capitalising on intelligent insights. The retailer operates differently with diversified items and services, but influencing retail atmospheric on personalised shoppers, the perception remains the same across industries. Retail atmospherics stimuli such as design, smell and others create behavioural modifications. The purpose of this study is to explore the atmospheric effects on brick-and-mortar store performance and personalised shopper's behaviour using cognitive computing based in-store analytics in the context of emerging market.

The data are collected from 35 shoppers of a brick-and-mortar retailer through questionnaire survey and analysed using quantitative method.

The result of the analysis reveals month-on-month growth in footfall count (46%), conversation rate (21%), units per transaction (27%), average order value (23%), dwell time (11%), purchase intention (29%), emotional experience (40%) and a month-on-month decline in remorse (20%). The retailers need to focus on three control gates of shopper behaviour: entry, browsing and exit. Attention should be paid to the cognitive computing solution to judge the influence of retail atmospherics on store performance and behaviour of personalised shoppers. Retail atmospherics create the right experience for individual shoppers and forceful use of it has an adverse impact.

The paper focuses on strategic decisions of retailers, the tactical value of personalised shoppers and empirically identifies the retail atmospherics effect on brick-and-mortar store performance and personalised shopper behaviour.

Any business that opts to adopt a recommender engine (RE) for various potential benefits must choose from the candidate solutions, by matching to the task of interest and domain. The purpose of this paper is to choose RE that fits best from a set of candidate solutions using rule-based automated machine learning (ML) approach. The objective is to draw trustworthy conclusion, which results in brand building, and establishing a reliable relation with customers and undeniably to grow the business.

An experimental quantitative research method was conducted in which the ML model was evaluated with diversified performance metrics and five RE algorithms by combining offline evaluation on historical and simulated movie data set, and the online evaluation on business-alike near-real-time data set to uncover the best-fitting RE.

The rule-based automated evaluation of RE has changed the testing landscape, with the removal of longer duration of manual testing and not being comprehensive. It leads to minimal manual effort with high-quality results and can possibly bring a new revolution in the testing practice to start a service line “Machine Learning Testing as a service” (MLTaaS) and the possibility of integrating with DevOps that can specifically help agile team to ship a fail-safe RE evaluation product targeting SaaS (software as a service) or cloud deployment.

A small data set was considered for A/B phase study and was captured for ten movies from three theaters operating in a single location in India, and simulation phase study was captured for two movies from three theaters operating from the same location in India. The research was limited to Bollywood and Ollywood movies for A/B phase, and Ollywood movies for simulation phase.

The best-fitting RE facilitates the business to make personalized recommendations, long-term customer loyalty forecasting, predicting the company's future performance, introducing customers to new products/services and shaping customer's future preferences and behaviors.

The proposed rule-based ML approach named “2-stage locking evaluation” is self-learned, automated by design and largely produces time-bound conclusive result and improved decision-making process. It is the first of a kind to examine the business domain and task of interest. In each stage of the evaluation, low-performer REs are excluded which leads to time-optimized and cost-optimized solution. Additionally, the combination of offline and online evaluation methods offer benefits, such as improved quality with self-learning algorithm, faster time to decision-making by significantly reducing manual efforts with end-to-end test coverage, cognitive aiding for early feedback and unattended evaluation and traceability by identifying the missing test metrics coverage.

The new ways to complete financial transactions have been developed by setting up mobile payment (m-payment) platforms and such platforms to access banking in the financial mainstream can transact as never before. But, does m-payment have veiled consequences? To seek an answer, the research was undertaken to explore the dark sides of m-payment for consumers by extending the theory of innovation resistance (IR) and by measuring non-adoption intention (NAI).

Three hundred individuals using popular online m-payment apps such as Paytm, PhonePe, Amazon Pay and Google Pay were surveyed for the primary data. IBM AMOS based structural equation modelling (SEM) was used to analyse the data.

Each m-payment transaction leaves a digital record, making some vulnerable consumers concerned about privacy threats. Lack of global standards prevents consumers from participating in the m-payment system properly until common interfaces are established based on up-to-date standards. Self-compassion (SC) characteristics such as anxiety, efficacy, fatigue, wait-and-see tendencies and the excessive choice of technology effect contribute to the non-adoption of m-payment.

This study proposes a threat model and empirically explores the dark sides of m-payment. In addition, it also unveils the moderator's role of SC in building the structural relationship between IR and NAI.

The predominant narrative is that contemporary organisations, motivated by economic-rationalist aspirations, adopt cloud applications on the premise of achieving cost-savings and efficiency gains. However, how they actually adopt and rollover such new or emerging technologies may be influenced by acts, patterns and processes of institutional legitimacy. Therefore, the purpose of this paper is to explore the dynamics surrounding decisions on how specific cloud applications are adopted from the context of institutional theory, with a particular focus on the concepts of coupling and decoupling.

To examine this phenomenon, two qualitative case studies, using a reflexive research approach, of an Australian and a Swedish university have been undertaken, both of which adopted commercial cloud applications for e.g. e-mail, collaboration and storage (as examples of software as a service) at different points in time. One of the universities was known for its early adoption of cloud applications, but had decelerated further deployment of such services, while the other, despite its conservative reputation, has made rapid strides in this regard.

The findings of the dual case studies reveal that organisations, contrary to economic-rationalist claims, may or may not decide to adopt particular commercial cloud-based offerings for the support of core operations, on the basis of how they perceive their institutional legitimacy being affected by a complex network of influential actors, both internally and in the external spaces. Therefore, this paper offers an institutional theory-based discourse and rich illustrations on how the role of technology is played out in enhancing relationships between an organisation and such actors in terms of legitimacy focusing acts of coupling and decoupling.

In the analysis and findings the authors, in a novel way, illustrate how organisations strive for: institutional legitimacy through acts of coupling, and the revelations of consequential decoupling. The value is based on a rich case description, analysis and application of institutional theory.

The purpose of this paper is to investigate the role of the “Big Five” personality traits (extraversion, openness, agreeableness, conscientiousness and neuroticism) on the adoption of augmented reality (AR), with a particular focus on the role AR may play in interactive marketing.

A quantitative-based approach was followed by a questionnaire survey, which was completed by 230 respondents comprising graduate and postgraduate students, using structural equation modelling.

While the trait of openness was positively associated with the perceived ease of use of AR, the usefulness of AR and subjective norms, the trait of neuroticism was negatively associated with the perceived ease of use of AR. Extraversion was positively associated with subjective norms. Perceived ease of use of AR, the usefulness of AR and subjective norms were positively associated with attitudes toward AR.

The data gathered will add a valuable contribution to the currently limited data available on empirical consumer behaviour research, particularly in relation to the adoption of AR for interactive marketing.

The findings of this study will benefit academics working on the adoption of technology in rapidly developing fields such as automation and artificial intelligence; the study also contributes to the emerging interdisciplinary domain of psychology, information systems, marketing and human behaviour.