Search results

This study aims to investigate limited partners’ (LPs) influence on venture capital (VC) fund returns.

We merge data from Preqin and SDC’s VentureXpert spanning from 1993 to 2014 and conduct multiple regression analysis to examine the influence of LPs on VC fund performance. Additionally, we conduct three distinct robustness tests to verify the credibility of our findings.

Our empirical analysis demonstrates that newbie LPs consistently exert a significant positive influence on VC fund returns.

VC and LP data is self-reported, and there is no comprehensive dataset as some LPs prefer to maintain anonymity.

Extant literature on LPs’ contribution to VC fund performance is limited. The general assumption is that the role of LPs in VC fund performance is confined to funding. We introduce a new variable, LP track record, as a proxy for LP experience to examine if this variable influences VC performance.

With the recent proliferation of AI, organisations are transforming not only their organisational design but also the input and output operational processes of the hiring process. The purpose of this paper is to explore the organisational and operational dimensions resulting from the deployment of AI during talent acquisition process.

The authors conducted semi-structured interviews and meetings with human resources (HRs) professionals, recruiters and AI hiring platform providers in Sweden. Using an inductive data analysis rooted in the principles of grounded theory, the study uncovered four aggregate dimensions critical to understanding the role of AI in talent acquisition.

With insights from algorithmic management and ambidexterity theory, the study presents a comprehensive theoretical framework that highlights four aggregate dimensions describing AI’s transformative role in talent recruitment. The results provide a cautionary perspective, advising against an excessive emphasis on operational performance driven solely by algorithmic management.

The study is limited in scope and subject to several constraints. Firstly, the sample size and diversity are restricted, as the findings are based on a limited number of semi-structured interviews and meetings with HRs professionals, recruiters, and AI hiring platform providers. Secondly, the rapid evolution of AI technologies means that the study’s findings may quickly become outdated as new advancements and applications emerge.

The results provide managers with actionable information that can lead to more precise and strategic management practices, ultimately contributing to improved organizational performance and outcomes. Plus, enhancing their ability to make informed decisions, optimize processes and address challenges effectively.

The results signal both positive and negative impacts on employment opportunities. On the positive side, AI can streamline recruitment processes, making it easier for qualified candidates to be identified and hired quickly. However, AI systems can also perpetuate existing biases present in the data they are trained on, leading to unfair hiring practices where certain groups are systematically disadvantaged.

By examining the balance between transactional efficiency and relational engagement, the research addresses a crucial trade-off that organizations face when implementing AI in recruitment. The originality lies in its critique of the prevailing emphasis on e-recruiting.

This study aims to present systematic analysis of research concerning the intersection of human resource management (HRM) and the integration of artificial intelligence (AI) technologies within a digitalized economy further analyzing the trends in research with specific emphasis on utilization of diverse AI technologies within HRM.

This research is based on bibliometric analyses and content analyses. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses review methodology is implemented, using the Scopus database as the primary source which gathered 1,414 articles between 1978 and 2024. This study investigates publishing trends, the most prolific countries, universities, journals, publications and authors in the field. Further, the research trends based on the use of AI in HRM were accomplished through scientific mapping using VOSviewer.

The outcomes demonstrate a rising inclination toward using various AI techniques in HRM which shows increasing influence and growing appeal of the subject. The research uncovers the deployment of diverse technologies, including emerging ones, within the HRM field. It accomplishes this by scrutinizing the connections among various keywords and unearths both contradictions and focal areas of interest within the domain.

The study contributes to the existing body of literature by ascertaining suggestions for further research in the field of HRM integrated with various AI technologies. The integration of these technologies in HR holds a promising and optimistic outlook for the managers, thereby enhancing employee productivity.

This study aims to explore the influence of creative tourist experiences (CTE) on tourists’ recommendation intentions (RCI) toward creative tourist destinations. This study examines the roles of tourist engagement and satisfaction in this relationship, proposing a sequential mediation model based on the cognitive-affective-conative model.

The research surveyed travelers to Kinnaur, Himachal Pradesh, India, using a structured questionnaire. Through purposive sampling data were collected from 413 generation Z (Gen Z in short) tourists. The study used exploratory factor analysis, confirmatory factor analysis and sequential mediation analysis. The present research used Model 6 by Andrew Hayes in the SPSS process macro to test the serial mediation.

The findings emphasize the importance of active engagement in creative tourism and its potential to transform cultural heritage into enriching experiences, thereby influencing tourists’ recommendation behaviors. Results of sequential mediation analysis show that there is a significant and positive impact of CTE on tourist’s RCI. Further, results showed the sequential mediation effect of tourist engagement and satisfaction on the relationship between CTE and RCI.

The findings offer valuable insights for destination managers and policymakers in creative tourism. Enhancing tourist engagement and satisfaction through creative experiences can effectively increase RCI, contributing to the sustainable management of cultural resources and preventing the over-commercialization of cultural heritage.

This research contributes to the literature on creative tourism by empirically testing the sequential mediation model and highlighting the pivotal role of tourist engagement and satisfaction in transforming creative experiences into positive behavioral outcomes. This study provides a nuanced understanding of the factors influencing tourists’ RCI in creative tourism contexts.

This study aims to help understand individual donors’ preferences over different designs of humanitarian–business partnerships in managing humanitarian operations and to help understand if donors’ preferences align with their actual donation behavior.

Choice-based conjoint analysis was used to understand donation preferences for partnership designs, and a donation experiment was performed using real money to understand the alignment of donors’ preferences with actual donation behavior.

The results show that partnering with the business sector can be a valuable asset for humanitarian organizations in attracting individual donors if these partnerships are managed well in terms of partnership strategy, partnership history and partnership report and disclosure. In particular, the study finds that the donation of services and products from businesses corporations to humanitarian organizations are preferable to individual donors, rather than cash. Furthermore, donors’ preferences are not necessarily aligned with actual donation behavior.

The results highlight the importance of presenting objective data on projects to individual donors. The results also show that donors value the provision of services and products by business corporations to humanitarian operations.

Partnerships between humanitarian organizations and business corporations are important for the success of humanitarian operations. However, little is known about which partnership designs are most preferable to individual donors and have the biggest chance of being supported financially.

This study attempts to analyse and rank the impact of work-related issues arising within the Indian construction industry in the context of the existing pandemic. Furthermore, this is the first attempt to provide strategies to overcome issues among a workforce that is highly contractual in nature and is currently witnessing the uncertainties of the pandemic's aftermath. To the best of the author's knowledge, few studies have highlighted the combined analysis of job insecurity, psychological stress and emotional exhaustion in the Indian construction industry.

The “Best Worst Methodology” (BWM) has been used in this study to analyse and rank the key factors that eliminate negative characteristics among contractual construction employees. The BWM, outlined by Rezaei (2015, 2016), is a popular “multi-criteria decision analysis technique” due to its advantage of consistent results and lesser pairwise data requirements.

The study identified and ranked the socioeconomic impact of the three waves of the COVID-19 pandemic on construction sector employees in the Indian subcontinent. The results indicate that job insecurity has the most prominent impact, which ultimately produces psychological stress and emotional exhaustion among employees.

To achieve the objective of identifying and prioritising the criteria of adverse socioeconomic impacts during the pandemic and outlining plans of action for the construction industry, ten experts (civil engineers/managers) from ten different construction projects were involved in a mixed-method case study, which has never been explored in the Indian construction sector.

The research objectives were to: (1) examine the relationship among motivations, satisfaction and loyalty with plant-based food dining at destinations; (2) determine if and how the attractiveness of eating plant-based foods moderates satisfaction and loyalty; and (3) investigate potential differences in visitor background information and consumption characteristics.

A survey was conducted at tourist attractions in southern Taiwan and 274 valid questionnaires were obtained. The relationships among motivations, satisfaction and loyalty were investigated when eating plant-based foods during travel. The moderating effects of food attractiveness on motivations and satisfaction/loyalty were measured.

The results indicated a positive relationship between motivations and satisfaction/loyalty in plant-based food dining. Motivations for plant-based food dining were comprised of four domains (physical, cultural, interpersonal and prestige) and satisfaction and loyalty had three (overall satisfaction, intention to revisit and intention to recommend).

The major implications were that motivations had a significant effect on satisfaction and loyalty; food attractiveness did not moderate the effect of motivations on satisfaction/loyalty; and background characteristics influenced satisfaction and loyalty.

Marketers and strategic planners for plant-based restaurants or those with plant-based meal options must make a greater effort to understand the distinctive demographic and dietary characteristics of the people who comprise the core of this market.

This research adds to the very limited literature on plant-based and vegetarian dining in tourism destinations. Furthermore, it tests, partially validates and expands a model by Kim et al. (2009) for consuming local food while traveling. The findings also complement the considerable evidence linking motivations to satisfaction and loyalty when dining.

This study aims to investigate the relationship link between societal and governmental support factors, individuals’ self-efficacy, experience and outcome expectations in framing nascent social entrepreneurs' intentions to establish e-government service centres in rural areas by using the integrated model approach of Hockert’s (2017) social entrepreneurial intentions (SEI) theoretical model and social cognitive career theory (SCCT).

Using a convenient sampling strategy, 615 survey samples were obtained through a questionnaire from e-governance-based social entrepreneurs in Karnataka. The primary data and theorised model are analysed and tested using partial least squares structural equation modelling.

This research findings indicate that appointing agency support, perceived societal support (PSS), government support, social entrepreneurial self-efficacy (SE-SE), public image, prior experience and outcome expectations substantially predicted SEI to establish an e-government service centre. Hence, prior experience and PSS were insignificant regarding direct influence outcome expectations towards establishing e-governance social ventures.

The present research study initially explored the social entrepreneur's intention to provide e-public services to people in rural and distant areas to fulfil social needs. Furthermore, this research revealed that new antecedents of government support, appointing agency support and public image influence the social entrepreneur's intention to establish e-governance service centres. These research findings evaluate the contribution of the government, appointing agencies, social entrepreneurs and citizens to make a framework for the inclination of e-government service centres to create a social impact in rural and remote areas.

Transportation-related pollution is expected to decrease when using battery electric cars. This will not only address energy and environmental issues but also promote reform and transformation in the zero-emission automotive industry. To craft policy interventions and promotional initiatives, manufacturers need to comprehend the techno-psychological perspectives of automotive users on the adoption of electric cars. Therefore, this study aims to test a “perception-attitude-intention” linking framework built upon the “Unified Theory of Technology Acceptance and Use” (UTAUT) and analyze the behavioral intentions of existing automobile users to embrace battery electric cars.

The conceptual model tests the underlying direct paths, the mediation of attitudes and the moderating gender effects in predicting users’ attitudes and behavioral intentions to adopt battery electric cars using a techno-psychological approach from UTAUT. “Structural equation modeling” is used to analyze the model using the 361 valid online responses received from conventional car owners.

The results show that behavioral intentions are directly predicted by UTAUT measures with attitudes and indirectly through its mediation and gender moderation. The results support the “Perceptions-Attitudes-Intentions” linkage model that explains the phenomenon of electric car adoption. However, the mediating and moderating paths between facilitating conditions and intentions do not support the model. In addition, the research corroborates that men have a stronger effect than women on behavioral intentions to prefer battery electric cars.

This work may assist manufacturers and regulators in developing marketing policies to encourage consumers’ adoption of battery electric cars and potentially improve their favorable perception of these vehicles.

This study contributes to the comprehension of how UTAUT constructs shape consumers’ attitudes and behavioral intentions regarding the adoption of battery cars equipped with emission-free technology. This study validates the grounded framework “perception-attitude-intention” linkage model, which also describes gender-wise differences toward electric car adoption in the backdrop of Indian sustainable transportation.