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The lack of conceptual approaches for organizing and expressing capabilities, usage and impact of intelligent machines (IMs) in work settings is an obstacle to moving beyond isolated case examples, domain-specific studies, 2 × 2 frameworks and expert opinion in discussions of IMs and work. This paper's purpose is to illuminate many issues that often are not addressed directly in research, practice or punditry related to IMs. It pursues that purpose by presenting an integrated approach for identifying and organizing important aspects of analysis and evaluation related to IMs in work settings. 

This paper integrates previously published ideas related to work systems (WSs), smart devices and systems, facets of work, roles and responsibilities of information systems, interactions between people and machines and a range of criteria for evaluating system performance.

Eight principles outline a straightforward and flexible approach for analyzing and evaluating IMs and the WSs that use them. Those principles are based on the above ideas.

This paper provides a novel approach for identifying design choices for situated use of IMs. The breadth, depth and integration of this approach address a gap in existing literature, which rarely aspires to this paper’s thoroughness in combining ideas that support the description, analysis, design and evaluation of situated uses of IMs.

The purpose of this paper is to review literature on home-country institutional factors influencing the internationalization of small and medium-sized enterprises (SMEs) from emerging markets. Based on the analysis, the authors propose a research agenda to guide future studies in this field.

This paper follows a systematic procedure to review 58 selected articles on how institutional contexts in emerging economies impact SME internationalization, covering studies from 1999 to 2023. This period was chosen to capture recent research following the post-1990 market liberalization in most emerging economies, which has shaped new opportunities and challenges for SMEs expanding abroad.

This literature review shows that SMEs’ internationalization knowledge in emerging markets is strongly shaped by home-country institutional conditions. Key mechanisms include imprinting by home institutions and learning from domestic institutional sources, both critical yet underexplored areas in SME development. These processes offer substantial opportunities for future research into how institutional contexts influence SMEs’ global growth.

This research builds on previous studies that have emphasized firm-level and external factors such as host market appeal, consumer needs and resource availability driving SMEs’ internationalization. Focusing on home institutional factors, the authors provide a comprehensive review of academic studies and propose a future research agenda on the external institutional influences shaping emerging market SMEs’ global expansion.

In their study of reciprocity in investigative interviews, Matsumoto and Hwang (2018) found that offering interviewees water prior to the interview enhanced observer-rated rapport and positively affected information provision. This paper aims to examine whether tailoring the item towards an interviewee’s needs would further enhance information provision. This paper hypothesised that interviewees given a relevant item prior to the interview would disclose more information than interviewees given an irrelevant item or no item.

Participants (n = 85) ate pretzels to induce thirst, engaged in a cheating task with a confederate and were interviewed about their actions after receiving either no item, an irrelevant item to their induced thirst (pen and paper) or a relevant item (water).

This paper found that receiving a relevant item had a significant impact on information provision, with participants who received water providing the most details, and significantly more than participants that received no item.

The findings have implications for obtaining information during investigative interviews and demonstrate a need for research on the nuances of social reciprocity in investigative interviewing.

The findings have implications for obtaining information during investigative interviews and demonstrate a need for research on the nuances of social reciprocity in investigative interviewing.

To the best of the authors’ knowledge, this study is the first to experimentally test the effect of different item types upon information provision in investigative interviews.

This study explores a hegemonic alliance and the role of relational forms of accounting and accountablity in the making of contemporary capitalism.

We use the WikiLeaks “Cablegate” documents to provide an account of the detailed machinations between interest groups (corporations and the state) that are constitutive of hegemonic activity.

Our analysis of the “Cablegate” documents shows that the US and Chevron were crafting a central role for Turkmenistan and its president on the global political stage as early as 2007, despite offical reporting beginning only in 2009. The documents exemplify how “accountability gaps” occlude the understanding of interdependence between capital and the state.

The study contributes to a growing idea that official accounts offer a fictionalized narrative of corporations as existing independently, and thus expands the boundaries associated with studying multinational corporate activities to include their interdependencies with the modern state.

The study traces how global capitalism extends into new territories through diplomatic channels, as a strategic initiative between powerful state and capital interests, arguing that the outcome is the empowerment of authoritarian states at the cost of democracy.

The study argues that previous accounting and accountability research has overlooked the larger picture of how capital and the state work together to secure a mutual hegemonic interest. We advocate for a more complete account of these activities that circumvents official, often restricted, views of global capitalism.

Although organizations are investing heavily in digital transformation (DT) of the sales function, implementation and exploitation at the sales force level are ongoing challenges. As sales managers serve as conduits of influence between top management and the sales force, the success of strategic initiatives, such as DT, hinges heavily on leveraging their influence to promote change adoption at the sales force level. Accordingly, this research is guided by the research question: how can sales organizations secure the buy-in of sales managers and induce their championing behaviors directed toward the sales force?. The purpose of this paper is to investigate how organizational and psychological resources influence sales managers' DT change champion through their change readiness.

Construing DT in sales as an organizational change that creates contextual job demands, the theoretical framework offers several hypotheses linking organizational and personal resources with sales managers’ change readiness and championing behaviors. The perceived impact of change is included as a moderating variable. Using data from a sample of 176 business-to-business sales managers, the hypotheses are tested using partial least squares structural equation modeling.

The authors demonstrate that two change-related organizational resources (change communication and change mobilization) and a personal psychological resource (psychological capital) facilitate sales managers’ emotional and cognitive change readiness, which, in turn, enhances their championing behaviors toward DT initiatives. Further, the authors find that perceived change impact augments the effects of organizational and psychological resources on change readiness, thus highlighting the importance of effective positioning of the outcomes of change.

This study provides practitioners with actionable guidance on securing the buy-in of sales managers for change initiatives such as DT. Specifically, communication and mobilization are critical inducements. Managers who score high on psychological capital can be targeted as change agents. Further, the impact of change needs to be framed positively, as the resultant perceptions magnify the effects of organizational resources.

While prior research has examined salespeople’s response to change, very little is known about the antecedents of change readiness and championing behavior among sales managers. Based on the results, the authors identify theoretical and managerial implications as well as future research directions.

This study aims to investigate the impact of earnings predictability and truthfulness on nonprofessional investors’ investment willingness.

Earnings predictability is captured by quarterly earnings autocorrelation, and earnings truthfulness is indicated by real earnings management (REM). The average of investment attractiveness and willingness measures investment willingness. The authors use experiments to isolate the impact of quarterly earnings autocorrelation and REM on investors’ investment behaviors.

From the 2 × 2 design, the authors observe that investors weight more on earnings predictability than earnings truthfulness.

The generalization of the findings may be constrained for the following reasons. First, the authors use only one proxy, REM, to measure earnings truthfulness. In addition, the authors provide the participants, Amazon Mechanical Turk, with earnings predictability. Results may no longer hold if each participant has different understanding and analysis of earnings predictability.

In periods of unprecedented and severe financial uncertainty (i.e. the COVID-19 pandemic), investors rely more on earnings predictability than on earnings truthfulness. The study assists managers to strategically emphasize the predictability of earnings to attract investors, especially when firms face financial challenges or uncertainty.

This study contributes to understanding investor behavior and the critical role of earnings predictability and truthfulness in shaping investment decisions.

This paper contributes to the literature of earnings properties in financial reporting, particularly by shedding light on the nuanced interplay between earnings predictability and earnings truthfulness. The research also demonstrates that elevated earnings autocorrelation indirectly stimulates investment willingness by enhancing the investors’ perception of earnings persistence of targeted firms.

This study aims to analyze the performance of quality indices to continuously validate a predictive model focused on the control chart classification.

The research method used analytical statistical methods to propose a classification model. The project science research concepts were integrated with the statistical process monitoring (SPM) concepts using the modeling methods applied in the data science (DS) area. For the integration development, SPM Phases I and II were associated, generating models with a structured data analysis process, creating a continuous validation approach.

Validation was performed by simulation and analytical techniques applied to the Cohen’s Kappa index, supported by voluntary comparisons in the Matthews correlation coefficient (MCC) and the Youden index, generating prescriptive criteria for the classification. Kappa-based control charts performed well for m = 5 sample amounts and n = 500 sizes when Pe is less than 0.8. The simulations also showed that Kappa control requires fewer samples than the other indices studied.

The main contributions of this study to both theory and practitioners is summarized as follows: (1) it proposes DS and SPM integration; (2) it develops a tool for continuous predictive classification models validation; (3) it compares different indices for model quality, indicating their advantages and disadvantages; (4) it defines sampling criteria and procedure for SPM application considering the technique’s Phases I and II and (5) the validated approach serves as a basis for various analyses, enabling an objective comparison among all alternative designs.

The purpose of this research is to undertake a bibliometric analysis of financial performance research in of higher education sector. The study examines papers over the last 2 decades and performed performance analysis, co-citation analysis, bibliographic coupling and scientific mapping.

The study examines 616 documents retrieved from the Scopus database using bibliometric analysis, performance analysis and thematic clustering. The study looked at the scientific productivity of papers, prolific authors, most influencing papers, institutions and nations, keyword cooccurrence, thematic mapping, co-citations and authorship and country collaborations. VOS viewer was employed as a tool in the research to conduct the performance analysis and thematic clustering.

This study delves into the recent advancements in financial performance research within higher education, focusing particularly on the year 2023, characterized by a peak of productivity with 46 significant articles. Notable institutions contributing substantially to this discourse include the University of Sussex (UK), and Ratio Institute Stockholm (Sweden), each referenced 227 times. The United Kingdom has emerged as a leader in financial performance research, amassing 3,850 citations from 92 publications. Key journals driving this conversation include “Entrepreneurship: Theory and Practice” and “The British Journal of Political Science.” The most cited study examines the impact of business-university partnerships on innovation and financial outcomes.”

This is the first study that provides a performance analysis and scientific mapping of the financial performance literature in the higher education sector. In addition, this study is the initial one to do a thorough analysis and organized representation of financial performance in the higher education sector, providing an unparalleled understanding of a hitherto uninvestigated area of academic research.

The purpose of this paper is to explore the challenges of implementing accountable artificial intelligence (AI) systems in India, focusing on the need for algorithms to justify their decisions, especially in subjective and complex scenarios. By analyzing various government projects, documented biases and conducting empirical case studies and experiments, the study highlights the limitations of AI in recognizing the nuances of India’s unique social landscape. It aims to underscore the importance of integrating political philosophy to ensure that AI systems are held accountable within India’s sociopolitical context, urging policymakers to develop frameworks for responsible AI decision-making.

The research adopts a mixed-methods approach to address the five research questions. It begins with an extensive literature review, focusing on AI’s transformative potential, algorithmic bias and accountability in the Indian context. Data is collected from 15 AI use cases in health care, education and public safety, 13 government automated decision tools and five bias cases, including facial recognition and caste-based discrimination. Additionally, ten case studies and three experiments on ChatGPT are analyzed. Content analysis is used to interpret and categorize the data, identifying patterns and themes. Specific case studies and experiments on autocompletion in search engines further support the findings.

The study revealed significant limitations in current AI systems when applied to India’s complex socio-cultural landscape. Analyzing 15 AI applications and 13 government projects, the research identified multiple instances of algorithmic bias. Experiments with Google’s autocomplete and ChatGPT showed that these systems often reinforce social stereotypes and struggle with nuanced, subjective situations. The findings emphasize the accountability gap in AI-driven decisions, highlighting the need for rigorous oversight, particularly in welfare projects where errors could lead to severe consequences. The study recommends developing regulatory frameworks, improving AI design and raising public awareness to address these challenges.

In the context of complex societies like India, a pressing concern arises: who should assume responsibility for the repercussions stemming from algorithmic failures to comprehend subjective complexities? To this end, there exist no serious scholarly works toward which present paper tries to shed new insights. It draws upon insights from the corpus of political philosophy literature, encompassing both classical and contemporary notions of responsibility, and seeks to establish connections between these concepts and the unique sociopolitical structure of India. The work is unique in the focus of the paper and is original in the direction projected.

This study aims to validate the hypothesis that a country’s preparedness for epidemics and pandemics, as measured by the GHS Index, significantly influences inward FDI inflows. By examining panel data from 2019 to 2021, the research seeks to elucidate the impact of heightened epidemic and pandemic preparedness on investment behavior, thereby highlighting the importance of health resilience and preparedness in attracting foreign investment and fostering economic growth and development.

The study uses panel data spanning 181 countries from 2019 to 2021 and uses logarithmic regression models to analyze the impact of a country’s preparedness for epidemics and pandemics, as measured by the Global Health Security (GHS) Index, on inward Foreign Direct Investment (FDI) inflows. Auxiliary variables including GDP, labor supply, openness rate, inflation rate and political stability are incorporated. Robust weighted least squares estimation techniques are used to account for potential heterogeneity and panel data characteristics.

The study reveals a consistent and statistically significant positive relationship between a country’s GHS score and inward FDI, indicating that destinations with robust health systems are more attractive to investors. Higher GHS scores correlate with reduced investment risk, improved business continuity during health crises and enhanced health-care infrastructure, leading to a healthier and more productive workforce.

While the study provides valuable insights into the relationship between epidemic and pandemic preparedness and inward FDI inflows, several limitations exist. The analysis relies on cross-sectional data from a relatively short timeframe (2019–2021), limiting the ability to capture long-term effects. Additionally, the study focuses on the GHS Index as a measure of preparedness, overlooking other potential determinants of FDI attractiveness. Future research could explore a broader range of health security indicators and incorporate longer-term data to provide a more comprehensive understanding of the relationship.

This study contributes to the literature by examining the previously underexplored relationship between a country’s epidemic and pandemic preparedness, as measured by the GHS Index and inward FDI inflows. By using panel data analysis and robust econometric techniques, the research provides empirical evidence supporting the positive impact of robust health systems on FDI attractiveness. The findings underscore the importance of prioritizing public health initiatives and epidemic preparedness as integral components of attracting and retaining foreign investment, thereby fostering economic resilience and sustainable development in host countries.