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The paper maps the site of a funded research project to understand how three knowledge articulations—harassment-knowledge, LGBTQ-knowledge, and intersectionality-knowledge—intersect in and around a research project and are produced, circulated, interrogated, and codified to note how intersectionality-knowledge effaces other possible articulations. The paper begins with an auto-ethnographic account of a Ford Foundation funded research project in India, led by key power-brokers of the LGBTQ+ movement, focusing on concerns of discrimination of non-normative genders and sexualities in India. The paper juxtaposes a Ford Foundation funded research project, a narrative from the fieldwork conducted for the project, and a draft of the Equality Bill, 2020 drafted by an organization invested in legal advocacy. The paper highlights the depoliticization of intersectionality, arguing that necessary work must go into mapping the social and the political before intersectionality is deployed as a straight-jacketed methodology in research work, mobilization or advocacy. In doing so, the paper argues that intersectionality's overt focus on state-reform risks depoliticizing queer/feminist politics.

Purpose
This paper aims to find out the impact of seven important factors towards behavior intention on various health-care applications in India. The spectacular rise of uses of smart phones in India has introduced various mobile applications in the market. The mobile applications have become very useful and popular amongst the urban consumers due to several reasons such as reducing time, effort, money, etc. Health-care applications which are used in various smart phones are still in an infancy stage in India. Health-care applications have several advantages and facilities and consumers receive few alerts or suggestions for free. Though the health-care applications have various benefits for everyone, still people are less aware of the services they provide. Fewer studies have been done on this particular subject, and people may find the apps interesting if they understand the benefits of these applications.


Design/methodology/approach
This study aims to find out the impact of seven factors towards behavior intention on various health-care applications in India. The 331 samples have been chosen with the help of a structured questionnaire. The researcher has used stratified random sampling to collect the data for conducting the study, and the samples have been collected from four metro cities of India, namely, Kolkata, Mumbai, Delhi and Chennai. Exploratory factor analysis and multiple regression analysis have been conducted to find out the most influencing factor towards intention with SPSS v 21.


Findings
The result reveals that out of seven factors, perceived usefulness, enjoyment and time are the most influencing and significant factors towards utilization expectation. The other four variables, namely, cost, increased dependability, perceived ease of use and increased protection do not have a significant impact on the dependent variable. The paper has also revealed that marketers need to penetrate the market with some innovative marketing strategies. The findings of the study is providing the hint for implementing the strategies.


Originality/value
The study is unique in the context of a country like India where no such studies on this subject have been conducted before.

Parents and best friends provide social support to adolescents that can protect them from risky sexual behaviors. Although past research has examined various factors related to parents, the benefits of parental involvement in an adolescent's life as it relates to risky sexual activities have not been examined. Past studies have also examined peer influence on adolescent behaviors, but have largely ignored the effect of best friends. The National Longitudinal Study of Adolescent Health (1995) reports that higher levels of family involvement and best friend interaction were related to lowering the odds of engaging in risky sexual activities. Higher levels of family involvement and best friend interaction increased the likelihood of using contraception during intercourse and early sexual activity among adolescents. The effects varied by gender. Programs that are intended to reduce the chances of sexual risk can potentially encourage activities with parents and close friends. Also, programs might focus on best friends, not necessarily peers, as a possible deterrent to behavior among adolescents.

The paper rekindles a three-decade-old debate in the annals of Indian anthropology / sociology which became dormant after no significant headway was made. The debate which goes by the name of "crisis in sociology" in India provides the backdrop against which the paper makes sense of current regimes of knowledge production that a doctoral candidate in India must navigate. By doing so, the paper reflects on the limitations of epistemological critiques wherein an epistemic critique stops at the corridors of an academic workplace. The paper argues that doctoral candidates in India today are cognitive workers engaged in exploitative relations of knowledge production. However, these exploitative relations are obfuscated by the postcolonial epistemological critiques that indulge in foregrounding the hegemony of the North / West. The paper proposes an infrastructural critique of knowledge that does not respond with despair to perceived transformations and crises.

This research article considers tech hype as a mnemonic process that makes us remember or forget the world, technology, and the myriad ways we can relate to it. The argument is based on an auto-ethnographic vignette and a close reading of two key texts in the discourse on using technology for land management in India. The article shows how technology, the social, and the practice of knowledge-production can be rethought in this mock battle between hype and criticism of hype.

In stopping problems, the decision maker receives a sequence of candidates and decides whether to select the current candidate and thereby stop the search or whether to continue surveying. Some examples include searching for an apartment, selecting an employee for a job, or choosing a new product or service from a sequence of vendors. Most of the literature on stopping problems assumes that the decision maker can perfectly evaluate the candidate when surveyed. We consider practical variations where surveying a candidate may provide no further information or imperfect information about its value. We show how the stopping problem can be considered an extension of the two-action (go/no-go) problem and present threshold optimal policies for the general problem. For the case where surveying candidates provides no further information and the uncertain values of candidates are normally distributed, we present analytical results that highlight how the value of information is affected by the parameters. With the help of an illustrative example, we demonstrate how a model that ignores sequential decisions could potentially severely underestimate the value of information. We also present a data-driven application of our results by studying the value of reports to a potential used car buyer.

Reliability block diagrams (RBDs) depict the functional relationships between components comprising a system, whereas Bayesian networks (BNs) represent probabilistic relationships between uncertain variables. Previous research has described how one can transform an RBD into a BN. In parallel, developments in the artificial intelligence literature have shown how a BN can be transformed into another graphical representation, an arithmetic circuit, which can subsequently be used for efficient inference. In this paper, we introduce a new graphical representation that we call a fault tree circuit, which is a special kind of arithmetic circuit constructed specifically for an RBD. A fault tree circuit can be constructed directly from an RBD and is more efficient than an arithmetic circuit that is compiled from the BN corresponding to that RBD. We develop several methods for fault tree circuits, highlighting how they can aid the analyst in efficient diagnosis, sensitivity analysis, and decision support for many typical reliability problems. The circuit framework can complement tools that are popular in the reliability analysis community. We use a simple pump system example to illustrate the concepts.

Mobile payment services are the most growing business in recent days and it is the most cost‐effective tool as well. This study aimed to explore the factors affecting the adoption of m‐payment services in emerging economies, which was attained by implementing the descriptive research design. Accordingly, the collection of 440 responses was carried out via the e‐mail method, wherein the respondents were selected by using the convenience sampling method. To this end, the research adapted the dimensions of UTAUT, ISS model, trust, and perceived security to examine one's adoption behavior toward mobile banking services. It was thus found that system quality yielded the strongest and significant influence on the intention to adopt, whereby the latter element served as a mediator and fully mediated the relationships between effort expectancy, facilitating conditions, and intention to recommend. Henceforth, the findings obtained in this study would aid industry practitioners in exploring pertinent strategies toward encouraging the adoption of mobile banking services not only among individuals but also for microentrepreneurs and SMEs. This is further achieved via the combination of the dimensions included in the UTAUT and ISS models along with the elements of trust and perceived security, thereby offering tremendous value addition to the existing literature. This particular study will further make several contribution toward mobile banking and mobile payment services related literature.

Decision analysis problems have traditionally been solved using either decision trees or influence diagrams. Although decision trees are better at handling asymmetry, prevalent in many reliability and risk analysis problems, influence diagrams can solve larger real-world problems by exploiting conditional independence. Decision circuits are graphical representations that combine the computational benefits of both graphical models. They are syntactic representations, i.e., they depict the summation, multiplication, and maximization operations required to solve a decision analysis problem. Previous work on decision circuits has focused on compiling them automatically from influence diagrams and describing the ways in which they can be used for efficient solution and sensitivity analysis. In this paper, we show how a decision circuit can be formulated directly, with or without the preprocessing of numbers that are assessed from the decision maker. By constructing two decision circuits for a nuclear reactor example, one using probabilities in inferred form and the other using probabilities in assessed form, we show how decision circuits generalize decision trees. The notion of coalescence is also made more explicit because computations for decision analysis can be saved and then reused in several ways. Because of their generality, decision circuits provide the analyst with a great deal of flexibility in problem formulation.

Purpose
This study aims to apply the theory of consumption value to analyze the utilization of Metaverse technologies within hospitality and tourism while examining the factors that impact consumer intentions to use the Metaverse.

Design/methodology/approach
This paper aims to consider an extensive study spanning the period October 2021 to March 2023 was conducted to understand the shifts in an individual's intention to use Metaverse technologies in hospitality.

Findings
The findings of this study confirm that individual attitudes to the Metaverse and trust in Metaverse technologies significantly impact their intention to use the Metaverse.

Practical implications
The study aims to provide fresh insights into how individuals perceive Metaverse technologies in the context of choosing hotels and resorts, which enriches the understanding of consumer behaviors around Metaverse technology in hospitality.

Originality/value
This study aims to consider not only tourist intentions to use the Metaverse but also how diverse consumption values impact user attitudes, an area currently underresearched.

This study explores the factors that prevent citizens from using contact tracing apps (CTA). It uses the innovation resistance theory to construct a parsimonious data analysis model. Data are collected from 440 users of CTA, and an analysis using structural equation modeling is done. Moderation analysis is performed to measure the influence of trust on the relationship between independent and dependent variables. The results reveal that privacy concerns, functional complexity, and benefit ambiguity are the main factors causing hindrance in the adoption of CTAs. The study carries implications for public authorities and technology professionals for promoting and increasing the uptake of public‐oriented mass‐consumption technology.