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The authors aim to contribute to the understanding of the enduring underrepresentation of women in the IT industry by analysing media discourse triggered by a campaign intended to encourage women to join the IT industry.

Internet media coverage of the Little Miss Geek campaign in the UK was analysed as qualitative data to reveal systematic and coherent patterns contributing to the social construction of the role of women with respect to the IT industry and IT employment.

While ostensibly supporting women's empowerment, the discourse framed women's participation in the IT industry as difficult to achieve, focused on women's presumed “feminine” essential features (thus, effectively implying that they are less suitable for IT employment than men), and tasked women with overcoming the barrier via individual efforts (thus, implicitly blaming them for the imbalance). In these ways, the discourse worked against the broader aims of the campaign.

Campaigns and organisations that promote women's participation should work to establish new frames, rather than allowing the discourse to be shaped by the established frames.

The authors interpret the framing in the discourse using Bourdieu's perspective on symbolic power: the symbolic power behind the existing patriarchal order expressed itself via framing, thus contributing to the maintenance of that order. By demonstrating the relevance of Bourdieu's symbolic power, the authors offer a novel understanding of how underrepresentation of women in the IT sector is produced and maintained.

This study aims to conduct the domain mapping of consumer behaviour research in the context of solar energy. The study can help in understanding the intellectual structure, evolution of keywords and key research producers (at the author, institutional and source level) related to the domain of solar energy consumer research.

This study uses R-studios’ bibliometrix package for analysing the bibliographical data collected from the Scopus database. Analysis has been conducted at the descriptive level (summary, author, institution and source) and analytical level (co-citation analysis, co-occurrence analysis, thematic maps and historiography).

This study finds out the most relevant authors, institutions and sources using criteria such as production, citations and H-index. Relevant research clusters have been identified using the clustering of authors, co-citations and keywords. Thematic mapping has identified the basic and motor themes. Historical citation analysis shows the direct linkage of previous studies. Overall, this study reports the most relevant bibliometric indicators in the domain of solar energy consumer research.

Identified patterns can help policymakers, business experts, social marketers and energy conservation organisations to study consumer behaviour.

Thiis bibliometric study can effectively assess sustainable development goals and suggest improved action plans.

This study examined bibliometric analysis in solar energy products (SEPs), recognised varied domains of research work on consumers’ intention to purchase solar household products and mapped them into six groups. This study provides an overview of 40 years of research on consumer behaviour towards SEPs and discusses its findings to identify the research gap.

Financial services industry is increasingly showing interest in automated financial advisors, or robo-advisors, with the aim of democratizing access to financial advice and stimulating investment behavior among populations that were previously less active and less served. However, the extent to which consumers trust this technology influences the adoption of rob-advisors. The resemblance to a human, or anthropomorphism, can provide a sense of social presence and increase trust.

In this paper, we conduct an experiment (N = 223) to test the effect of anthropomorphism (low vs medium vs high) and gender (male vs female) of the robo-advisor on social presence. This perception, in turn, enables consumers to evaluate personality characteristics of the robo-advisor, such as competence, warmth, and persuasiveness, all of which are related to trust in the robo-advisor. We separately conduct an experimental study (N = 206) testing the effect of gender neutrality on consumer responses to robo-advisory anthropomorphism.

Our results show that consumers prefer human-alike robo-advisors over machinelike or humanoid robo-advisors. This preference is only observed for male robo-advisors and is explained by perceived competence and perceived persuasiveness. Furthermore, highlighting gender neutrality undermines the positive effect of robo-advisor anthropomorphism on trust.

We contribute to the body of knowledge on robo-advisor design by showing the effect of robot’s anthropomorphism and gender on consumer perceptions and trust. Consequently, we offer insightful recommendations to promote the adoption of robo-advisory services in the financial sector.

COVID-19 and its accompanying lockdowns were arguably the most traumatic events of our times. This paper investigates the impact of COVID-19 on market efficiency.

I analyze all publicly traded U.S. equities for 2014–September 2021, using intraday data from TAQ, TRACE, I/B/E/S and Capital IQ and daily data from CRSP, Thomson Reuters, Compustat, CRSP-Compustat Merged Database and FRED, using a controlled contrast between absolute abnormal returns for relevant halfhours versus absolute abnormal returns in control halfhours, measured by the negative of the coefficient of the fixed effect of the interaction between the indicator variable, and as the case may be, ticker and/or time period of interest, in the regression of halfhour-level absolute abnormal returns on tickers, months and interactions.

Using two separate objective, systematic, independent and ordinal per se measures of market efficiency based upon market reactions separately to key developments and earnings announcements, I find that U.S. equities markets were statistically and economically significantly less efficient during the first two-three months of the COVID-19 lockdowns.

Efficient capital markets provide substantial social benefits and are a sine qua non for the democratization of markets and the protection of investors, and constitute a critical mission of regulatory bodies such as the U.S. Securities and Exchange Commission (SEC) and the U.S. Financial Industry Regulatory Authority (FINRA).

The impact on market efficiency provides one critical input into the social cost-benefit analysis of public health policy and that of government interventions in general.

There has been no previous work done on the systematic and objective characterization of the impact of COVID-19 and associated lockdowns on market efficiency.

Norway, like other welfare states, seeks to leverage data to transform its pressured public healthcare system. While managers will be central to doing so, we lack knowledge about how specifically they would do so and what constraints and expectations they operate under. Public sources, like the Norwegian policy documents investigated here, provide important backdrops against which such managerial work emerges. This article therefore aims to analyze how key Norwegian policy documents construe data use in health management.

We analyzed five notable policy documents using a “practice-oriented” framework, considering these as arenas for “organizing visions” (OVs) about managerial use of data in healthcare organizations. This framework considers documents as not just texts that comment on a topic but as discursive tools that formulate, negotiate and shape issues of national importance, such as expectations about data use in health management.

The OVs we identify anticipate a bold future for health management, where data use is supported through interconnected information systems that provide relevant information on demand. These OVs are similar to discourse on “evidence-based management,” but differ in important ways. Managers are consistently framed as key stakeholders that can benefit from using secondary data, but this requires better data integration across the health system. Despite forward-looking OVs, we find considerable ambiguity regarding the practical, social and epistemic dimensions of data use in health management. Our analysis calls for a reframing, by moving away from the hype of “data-driven” health management toward an empirically-oriented, “data-centric” approach that recognizes the situated and relational nature of managerial work on secondary data.

By exploring OVs in the Norwegian health policy landscape, this study adds to our growing understanding of expectations towards healthcare managers' use of data. Given Norway's highly digitized health system, our analysis has relevance for health services in other countries.

This study aims to conceptualise a customer-centric model based on an online customer experience (OCE) construct, mediated by e-loyalty (EL) and e-trust (ET), to improve the continuous usage intention (CUI) of Indian digital banks from Generation Y and Z perspectives.

This study used an online survey method to gather data from a sample of 466 digital banking users, from which usable questionnaires were obtained. The obtained data were subjected to thorough analysis using PLS-SEM to further study the research hypotheses.

The main factors that determine digital banks’ OCE are perceived enjoyment, e-service quality, information quality and e-convenience. Additionally, relevant constructs were evaluated using an importance-performance map analysis.

This study used convenience sampling for the urban population using digital banking; therefore, the outcome may be generalised to a limited extent. It would be valuable to imitate studies in other countries to strengthen digital banking further.

There is a lack of research on digital banking and OCE in India; thus, this study helps rectify this issue while providing valuable insights. This study differs from others in that it examines the connections between OCE, EL, ET and the bottom line of financial institutions, using these factors as dependent variables instead of traditional measures.

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.

In spite of wide civic and academic interest in obesity, there are no bibliometric records of this issue in the marketing corpus. Thus, this inquiry is conceived to address this shortcoming with a bibliometric analysis of Scopus indexed articles published on the subject.

The analysis followed a five-step science mapping approach of study design, data collection, data analysis, data visualisation and data interpretation. R programming software was used to review 88 peer reviewed journals published between 1987 and 2021.

A sizable stream of literature exploring obesity has accrued in the marketing area as authors have drawn parallels between the influence of persuasive communication and advertising on human wellbeing and child health. The United States of America is found to be by far the country with the highest number of publications on obesity, followed by Australia and the United Kingdom. The topic dendrogram indicates two strands of obesity discourse: (1) social and policy intervention opportunities and (2) the effects on social groups in the population.

This review will shape future enquiries investigating obesity. Beyond the focus on children, males and females, an emerging focus on cola, ethics, food waste, milk, policy-making and students is highlighted.

This is the first bibliometric review of obesity in the marketing literature. This is especially timely for weighing up the utility of research aimed at understanding and reporting the trends, influences and role of stakeholders in addressing obesity.

The purpose of this paper is to present an integrated data-driven framework for processing and analyzing large-scale vehicle maintenance records to get more comprehensive understanding on vehicle quality.

We propose a framework for vehicle quality analysis based on maintenance record mining and Bayesian Network. It includes the development of a comprehensive dictionary for efficient classification of maintenance items, and the establishment of a Bayesian Network model for vehicle quality evaluation. The vehicle design parameters, price and performance of functional systems are modeled as node variables in the Bayesian Network. Bayesian Network reasoning is then used to analyze the influence of these nodes on vehicle quality and their respective importance.

A case study using the maintenance records of 74 sport utility vehicle (SUV) models is presented to demonstrate the validity of the proposed framework. Our results reveal that factors such as vehicle size, chassis issues and engine displacement, can affect the chance of vehicle failures and accidents. The influence of factors such as price and performance of engine and chassis show explicit regional differences.

Previous research usually focuses on limited maintenance records from a single vehicle producer, while our proposed framework enables efficient and systematic processing of larger-scale maintenance records for vehicle quality analysis, which can support auto companies, consumers and regulators to make better decisions in purchase choice-making, vehicle design and market regulation.

Drawing on the work of Niklas Luhmann, the paper argues that technology can be viewed as a self-referential system which is autonomous from both human beings and other function systems of society. The paper aims to develop a philosophy of technology from the work of Niklas Luhmann. To achieve this aim, it draws upon the systems-theory work of Jacques Ellul, a philosopher of technology who focuses on the autonomous potential of technological evolution.

The paper draws on the work of Niklas Luhmann and Jacques Ellul to explore the theme of autonomous technology and what this means for our thinking about technological issues in the twenty-first century. Insights from these two thinkers and researchers working in the Luhmannian sociological tradition are applied to remote work.

The sociological approach of Luhmann, coupled with Ellul's insights into the autonomous nature of technology, can help us develop a systems theory of technology which takes seriously its irreducibility to human functions.

The paper contributes to the growing sociological literature that thematizes the Luhmannian approach to technology, helping us better understand this phenomenon and think in new ways about what technological autonomy means.

The paper brings together the work of Luhmann, Ellul and contemporary researchers to advance a new understanding of technology and technological communication.