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A “state-driven” approach suggests that colonists use census categories to rule. However, a “society-driven” approach suggests that this state-driven perspective confers too much power upon states. A third approach views census-taking and official categorization as a product of state–society interaction that depends upon: (a) the population's lay categories, (b) information intellectuals' ability to take up and transform these lay categories, and (c) the balance of power between social and state actors. We evaluate the above positions by analyzing official records, key texts, travelogues, and statistical memoirs from three key periods in India: Indus Valley civilization through classical Gupta rule (ca. 3300 BCE–700 CE), the “medieval” period (ca. 700–1700 CE), and East India Company (EIC) rule (1757–1857 CE), using historical narrative. We show that information gathering early in the first period was society driven; however, over time, a strong interactive pattern emerged. Scribes (information intellectuals) increased their social status and power (thus, shifting the balance of power) by drawing on caste categories (lay categories) and incorporating them into official information gathering. This intensification of interactive information gathering allowed the Mughals, the EIC, and finally British direct rule officials to collect large quantities of information. Our evidence thus suggests that the intensification of state–society interactions over time laid the groundwork for the success of the direct rule British censuses. It also suggests that any transformative effect of these censuses lay in this interactive pattern, not in the strength of the British colonial state.

As a result of COVID-19 outbreak, the rapid digital transformation has drastically changed the way we work as individuals as well as the organisations. Our constant engagement online has become a natural phenomenon. Whenever we go online, we leave a trail of digital data behind us either actively or passively. For a common customer, employee or even an employer, issues regarding data protection and data security are challenging. For instance, who owns the Digital Footprint Data? Do the employees have the skills to protect customers' data online? How are small and medium enterprises (SMEs) handling the ethical issues around digital footprints? These are some primary questions SMEs are currently facing in the transition of digital transformation. These questions have profound ethical implications for SMEs' digital footprints during the COVID-19 outbreak and beyond, which have been explored further in this study.

The advancement of artificial intelligence (AI) has brought intelligent online shopping experiences to customers. AI-powered retail platforms deliver personalized shopping experiences through tailored recommendations, promotions and assistance. Given the increasing preference for online shopping, it is crucial to explore methods to optimize the adoption of AI-powered retail platforms. To address this, this study aims to examine the impact of technology readiness motivators (optimism and innovativeness) and inhibitors (discomfort and insecurity) on perceived trust, perceived usefulness and purchase intention toward AI-powered retail platforms.

Data were collected from 276 customers in Egypt, primarily from the millennial and Gen Z demographic segments. The collected data were then analyzed using the statistical package for social sciences (SPSS) and partial least squares structural equation modeling (PLS-SEM).

The findings revealed that optimism, innovativeness and discomfort significantly influence perceived trust, while optimism, insecurity and perceived trust significantly influence perceived usefulness. Both perceived trust and usefulness are significant predictors of purchase intention. Perceived trust mediates the effects of technology readiness motivators on perceived usefulness and purchase intention. Moreover, perceived usefulness mediates the effects of technology readiness motivators, insecurity and perceived trust on purchase intention.

To date, there are few investigations regarding the acceptance and adoption of AI-powered retail platforms in developing countries. Thus, this study offers valuable theoretical and practical implications in the context of smart retail technology adoption.

The purpose of this paper is to investigate (1) whether the public health expenditure rises as the gross state domestic product (GSDP) increases and (2) whether the infant mortality rate (IMR) reduces as public health expenditure increases.

For this investigation, the author collected a time series of data on public health spending and IMRs for an Indian state and applied regression, stationarity, cointegration and causality tests. The author also compared the relative performance of selected Indian states.

The author found that none of the Indian states did equally well in reducing the infant mortality rate (IMR). As GSDP rises, the public expenditure on health rises, however, this increase in public health expenditures does not cause a reduction in the IMR. The cointegration and causality test results validated it.

The author recommends that policymakers must shift their focus from merely increasing government health expenditure to efficiently utilising allocated funds and removing the administrative bottlenecks. Also, an equitable health financing system that addresses existing disparities in the healthcare delivery system should be ensured.

Researchers and policymakers have debated the role of public health spending in achieving Sustainable Development Goal (SDG) 3 targets. The paper proves that there exists no long-term relationship between public health spending and IMR.

The purpose of this paper is to examine patient engagement in remote consultation services, an increasingly important issue facing Healthcare Operations Management (HOM) given the significant expansion in this and other forms of telehealth worldwide over the last decade. We use our analysis of the literature to develop a comprehensive framework that incorporates the patient journey, multidimensionality, antecedents and consequences, interventions and improvement options, as well as the cyclic nature of patient engagement. We also propose measures suitable for empirical assessment of different aspects of our framework.

We undertook a comprehensive review of the extant literature using a systematic review approach. We identified and analysed 63 articles published in peer-reviewed scientific journals between 2003 and 2022.

We conceptualise patient engagement with remote consultation across three key aspects: dimensions, process, and the antecedents and consequences of engagement. We identify nine contextual categories that influence such engagement. We propose several possible metrics for measuring patient engagement during three stages (before service, at/during service and after service) of remote consultation, as well as interventions and possible options for improving patient engagement therein.

The primary contribution of our research is the development of a comprehensive framework for patient engagement in remote consultation that draws on insights from literature in several disciplines. In addition, we have linked the three dimensions of engagement with the clinical process to create a structure for future engagement assessment. Furthermore, we have identified impact factors and outcomes of engagement in remote consultation by understanding which can help to improve levels of adoption, application and satisfaction, and reduce healthcare inequality. Finally, we have adopted a “cyclic” perspective and identified potential interventions that can be combined to further improve patient engagement in remote consultation.

This study aims to evaluate the influence of institutions on the probability of becoming a social entrepreneur and the effect of this choice on individual economic well-being. The authors also analyze the effects of gender (male versus female entrepreneurism) and type (traditional versus social entrepreneurism).

Institutional economics framed the analysis, and hypotheses were tested using two-stage probit least squares models in a sample of 69,236 individuals from 57 countries during the 2010–2014 wave from the World Values Survey.

The results showed that, for most variables, institutions significantly explained the probability of becoming a social entrepreneur. The analyses also indicated that social entrepreneurship is highly associated with individual economic well-being.

This research brings insights into the discussion of the social and economic benefits of socially oriented entrepreneurs. Likewise, the modeling approach overcomes the interplay between entrepreneurship and economic outcomes, in which institutions become key factors.

Este estudio evalúa la influencia de las instituciones en la probabilidad de convertirse en un emprendedor social y el efecto de esta elección en el bienestar económico individual. También se analizan los efectos del género (emprendimiento masculino versus femenino) y del tipo (emprendimiento tradicional versus social).

La economía institucional es el marco para el análisis e hipótesis, las cuales se evaluaron utilizando modelos probit de mínimos cuadrados de dos etapas (2SPLS) en una muestra de 69.236 personas de 57 países durante la ola 2010–2014 de la Encuesta Mundial de Valores.

Los resultados mostraron que, para la mayoría de las variables, las instituciones explicaron significativamente la probabilidad de convertirse en un emprendedor social. El análisis también indicaró que el emprendimiento social está altamente asociado con el bienestar económico individual.

Esta investigación aporta información sobre el debate alrededor de los beneficios sociales y económicos de los emprendedores con orientación social. Asimismo, el enfoque de modelización resuelve la interdependencia entre el emprendimiento y variables económicas, en la que las instituciones son factores claves.

Este estudo avalia a influência das instituições na probabilidade de se tornar um empreendedor social e o efeito desta escolha no bem-estar económico individual. Os efeitos do género (empreendedorismo masculino versus feminino) e do tipo (empreendedorismo tradicional versus social) também são analisados.

A economia institucional é a estrutura para a análise e hipóteses, que foram avaliadas usando modelos probit de mínimos quadrados em dois estágios (2SPLS) em uma amostra de 69.236 pessoas de 57 países durante a onda 2010–2014 dos Valores Mundiais Pesquisa.

Os resultados mostraram que, para a maioria das variáveis, as instituições explicaram significativamente a probabilidade de se tornar um empreendedor social. A análise também indicou que o empreendedorismo social está altamente associado ao bem-estar económico individual.

Esta investigação fornece informações sobre o debate em torno dos benefícios sociais e económicos dos empreendedores de orientação social. Da mesma forma, a abordagem de modelização resolve a interdependência entre o empreendedorismo e as variáveis económicas, nas quais as instituições são fatores-chave.

The integration of big data with artificial intelligence in the field of digital health has brought a new dimension to healthcare service delivery. AI technologies that provide value by using big data obtained in the provision of health services are being added to each passing day. There are also some problems related to the use of AI technologies in health service delivery. In this respect, it is aimed to understand the use of digital health, AI and big data technologies in healthcare services and to analyze the developments and trends in the sector.

In this research, 191 studies published between 2016 and 2023 on digital health, AI and its sub-branches and big data were analyzed using VOSviewer and Rstudio Bibliometrix programs for bibliometric analysis. We summarized the type, year, countries, journals and categories of publications; matched the most cited publications and authors; explored scientific collaborative relationships between authors and determined the evolution of research over the years through keyword analysis and factor analysis of publications. The content of the publications is briefly summarized.

The data obtained showed that significant progress has been made in studies on the use of AI technologies and big data in the field of health, but research in the field is still ongoing and has not yet reached saturation.

Although the bibliometric analysis study conducted has comprehensively covered the literature, a single database has been utilized and limited to some keywords in order to reach the most appropriate publications on the subject.

The analysis has addressed important issues regarding the use of developing digital technologies in health services and is thought to form a basis for future researchers.

In today’s world, where significant developments are taking place in the field of health, it is necessary to closely follow the development of digital technologies in the health sector and analyze the current situation in order to guide both stakeholders and those who will work in this field.

This study aims to examine the interaction effects of chatbots’ language style and customers’ decision-making journey stage on customer’s service encounter satisfaction and the mediating role of customer perception of emotional support and informational support using the construal level theory and social support theory as conceptual frameworks.

This study used a scenario-based experiment with a 2 (chatbot’s language style: abstract language vs concrete language) × 2 (decision-making journey stage: informational stage vs transactional stage) between-subjects design.

Findings show that during the informational stage, chatbots that use abstract language style exert a strong influence on service encounter satisfaction through emotional support. During the transactional stage, chatbots that use concrete language style exert a strong impact on service encounter satisfaction through informational support.

Findings provide some suggestions for improving customer–chatbot interaction quality during online service encounters.

This study offers a novel perspective on customer interaction experience with chatbots by investigating the chatbot’s language styles at different decision-making journey stages.