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The public distribution system (PDS) is an Indian food security system established to manage the distribution of food grains at affordable prices. As a result of the population explosion, the long-established PDS system finds it challenging to maintain operational efficiency, quality, trust and transparency. This paper explores the possibility of leveraging blockchain technology to overcome these operational hurdles.

Through a literature review and expert interactions, the present research identifies critical success factors in terms of enablers and barriers that influence the adoption of blockchain technology in PDS. Furthermore, we propose two independent interpretive structural models (ISM) and MICMAC to characterize these attributes.

The research identifies 15 distinct enablers and ten barriers that influence the diffusion of the latest technology in the sector at focus. The analyses disclose the interrelationships/dependencies among these enablers and between barriers, along with their individual driving power and dependence power.

The research showcases the importance of automating the system and illustrates how the features of blockchain technology can assist in augmenting stakeholder satisfaction levels. However, poor or nonexistent government regulations and patronage are found to be the major impediments to adoption. The research also delineates the cost implications of this barrier through its interrelationships with other barriers.

Interesting inferences are drawn from the models that offer actionable insights for the industry, government and technologists for improving PDS performance. Such interventions will ensure national food security through enhanced trust and transparency, which can further improve efficiency and effectiveness.

The implementation of BIM in the construction industry requires the coevolution of the various aspects of the BIM ecosystem. The human dimension is a very important dimension of the ecosystem necessary for BIM implementation. It is imperative to study this aspect of the BIM ecosystem both from the employer perspective and employee availability to provide insights for stakeholders (job seekers, employers, students, researchers, policymakers, higher education institutions, career advisors and curriculum developers) interested in the labour market dynamics.

To understand the BIM actor roles through the employer lens and the actual BIM actors in the construction industry, this study employed data mining of job adverts from LinkedIn and Mncjobs website. Content analysis was employed to gain insights into the data collected. Also, through a quantitative approach, the existing BIM actor roles were identified.

The study identified the employers' expectations of BIM actors; however, it is noted that the BIM actor recruitment space is still a loose one as recruiters put out open advertisements to get a large pool of applicants. From the data analysed, it is concluded that the BIM actor role is not an entirely new profession. However, it simply exists as construction industry professionals with BIM tool skills. Also, the professional development route is not well defined yet.

This study presents a realistic angle to BIM actor roles hence enhancing BIM implementation from the human perspective. The findings present an insight into the preferred against the actual.

The integration of artificial intelligence (AI) technologies like conversational AI and HR chatbots in international human resource development (HRD) presents both productivity benefits and ethical challenges. This study aims to examine the ethical dimensions of AI-driven HR chatbots, emphasizing the need for fairness, autonomy and nondiscrimination. It discusses inherent biases in AI systems and addresses linguistic, cultural and accessibility issues. The paper advocates for a comprehensive risk assessment approach to guide ethical integration, proposing a “risk management by design” framework. By embracing ethical principles and robust risk management strategies, organizations can navigate AI-driven HR technologies while upholding fairness and equity in global workforce management.

Systematic literature review.

The paper advocates for a comprehensive risk assessment approach to guide ethical integration, proposing a “risk management by design” framework.

By embracing ethical principles and robust risk management strategies, organizations can navigate AI-driven HR technologies while upholding fairness and equity in global workforce management.

This study explores the intricate ethical landscape surrounding AI-driven HR chatbots, spotlighting the imperatives of fairness, autonomy, and nondiscrimination. Uncovering biases inherent in AI systems, it addresses linguistic, cultural, and accessibility concerns. Proposing a pioneering “risk management by design” framework, the study advocates for a holistic approach to ethical integration, ensuring organizations navigate the complexities of AI-driven HR technologies while prioritizing fairness and equity in global workforce management.

Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which physicians cooperate with AI in their work to achieve productive and innovative performance, which is a key issue in operations management (OM). We conducted empirical research to answer this question.

We developed a conceptual model based on the ambidextrous perspective. To test our model, we collected data from 200 Chinese hospitals. One senior and one junior physician from each hospital participated in this research so that we could get a more comprehensive view. Based on the sample of 400 participants and the conceptual model, we examined whether different types of AI use have distinct impacts on physicians’ productivity and innovation by conducting hierarchical regression and post hoc tests. We also introduced team psychological safety climate (TPSC) and AI technology uncertainty (AITU) as moderators to investigate this topic in further detail.

We found that augmentation AI use is positively related to overall productivity and innovative job performance, while automation AI use is negatively related to these two outcomes. Furthermore, we focused on the impacts of the ambidextrous use of AI on these two outcomes. The results highlight the positive impacts of complementary use on both outcomes and the negative impact of balance on innovative job performance. TPSC enhances the positive impacts of complementary use on productivity, whereas AITU inhibits the negative impacts of automation and balanced use on innovative job performance.

In the age of AI, organizations face greater trade-offs between performance and technology management. This study contributes to the OM literature from the perspectives of operational performance and technology management in three ways. First, it distinguishes among different AI implementations and their diverse impacts on productivity and innovative performance. Second, it identifies the different conditions under which automation AI use and augmentation are superior. Third, it extends the ambidextrous perspective by becoming an early adopter of this approach to explore the implications of different types of AI use in light of contingency factors.

This empirical paper investigates how entrepreneurial firms change their business models in the context of internationalization by identifying different forms of business model innovation (BMI) and exploring the interrelationship between BMI and internationalization.

Based on the dynamic states approach of entrepreneurship (Levie and Lichtenstein, 2010), this paper analyses primary and secondary data from nine European firms following a multiple case study approach.

This paper presents four patterns of radical change and eight types of incremental adaption with-in business models in the context of internationalization. We describe these BMI patterns and types, and we also show how they contribute to increasing involvement in international business activities and the internationalization-related triggers that might cause them.

This paper contributes to a better understanding of the BMI process in the course of internationalization. It also highlights the complex interrelationship between BMI and internationalization by building on a progressive theoretical approach.

The purpose of this study is to investigate the adoption of waqf technology (Waqftech) using blockchain smart contracts for corporate waqf crowdfunding. Despite the growing interest in Waqftech, Malaysian enterprises have not fully embraced this emerging technology because of uncertainty regarding the benefits it offers to contributors. The research incorporates two theoretical frameworks: the electronic data interchange (EDI) model for firms’ technology adoption, and the triple bottom line theory (TBL) for corporate social responsibility.

A quantitative method using a cross-sectional survey design with a five-point Likert scale questionnaire was used. Data was collected from 210 decision-makers representing small and medium-sized enterprises and analyzed using partial least squares-structural equation modeling.

The findings from this research suggest that Malaysian enterprises are influenced by both corporate and social predictive benefits when using blockchain crowdfunding, but not by environmental benefits. The adoption of blockchain smart contracts does not correlate with predictive environmental benefits because of misconceptions about the disruptive technology’s impact on biological and digital environmental preservation.

This research focuses on organizational behavior rather than individual users of waqf crowdfunding, and it is limited, primarily focusing within Malaysia and regions with similar waqf structures.

The Waqftech framework allows innovative mechanisms for executing corporate waqf investment returns to the intended beneficiaries through the smart contracts’ platform. In addition, this study supports relevant corporate social responsibility and creating shared value technology adoption theories, including EDI and TBL. Aside from this, the study provides empirical implications for waqf management using fintech platforms.

This groundbreaking study focuses on creating a Waqftech model for corporate waqf crowdfunding. The results of this study are important for the development of government policies that support the use of Waqftech in charitable fundraising. More research on biological and digital environmental perspectives is proposed to foster investors’ confidence in the visibility of digital tracking and lead to swift investments in future metaverse fundraising platforms.

Cotton fibre lots are graded and selected for yarn spinning based on their quality value which is a function of certain fibre properties. Cotton grading and selection has created a domain of emerging interest among the researchers. Several researchers have addressed the said issue using a few exponents of multi-criteria decision-making (MCDM) technique. The purpose of this study is to demonstrate a cotton selection problem using a recently developed measurement of alternatives and ranking according to compromise solution (MARCOS) method which can handle almost any decision problem involving a finite number of alternatives and multiple conflicting decision criteria.

The MARCOS method of the MCDM technique was deployed in this study to rank 17 cotton fibre lots based on their quality values. Six apposite fibre properties, namely, fibre bundle strength, elongation, fineness, upper half mean length, uniformity index and short fibre content are considered as the six decision criteria assigning weights previously determined by an earlier researcher using analytic hierarchy process.

Among the 17 alternatives, C9 secured rank 1 (the best lot) with the highest utility function (0.704) and C7 occupied rank 17 (the worst lot) with the lowest utility function (0.596). Ranking given by MARCOS method showed high degree of congruence with the earlier approaches, as evidenced by high rank correlation coefficients (Rs > 0.814). During sensitivity analyses, no occurrence of rank reversal is observed. The correlations between the quality value-based ranking and the yarn tenacity-based rankings are better than many of the traditional methods. The results can be improved further by adopting other efficient method of weighting the criteria.

The properties of raw cotton have significant impact on the quality of final yarn. Compared to the traditional methods, MCDM is reported as the most viable solution in which fibre parameters are given their due importance while formulating a single index known as quality value. The present study demonstrates the application of a recently developed exponent of MCDM in the name of MARCOS for the first time to address a cotton fibre selection problem for textile spinning mills. The same approach can also be extended to solve other decision problems of the textile industry, in general.

Novelty of the present study lies in the fact that the MARCOS is a very recently developed MCDM method, and this is a maiden application of the MARCOS method in the domain of textile, in general, and cotton industry, in particular. The approach is very simple, highly effective and quite flexible in terms of number of alternatives and decision criteria, although highly robust and stable.

This study aims to evaluate the efficiency of using some polymers at different concentrations in the consolidation of vegetable-tanned leather artifacts.

New vegetable-tanned leather samples were prepared. The consolidants used were polyacrylamide (PAM) and polymethyl methacrylate/hydroxyethyl methacrylate (MMA-HEMA). Accelerated heat aging was applied to the untreated and treated samples. Analytical techniques used were Fourier transform infrared spectroscopy (FTIR), digital microscope, scanning electron microscope (SEM), change of color and mechanical properties.

The characteristic FTIR bands showed the effect of accelerated heat aging on the molecular structure of the studied samples, but treated and aged treated samples used were better than aged untreated samples. Microscopic investigations (digital and SEM), and mechanical properties proved that 2% was the best concentration for polymers used. The change in the total color difference of the treated and aged treated samples was limited.

This study presents the important results obtained from PAM and poly(MMA-HEMA) used for the consolidation of vegetable-tanned leather artifacts. The best results of the studied polymers can be applied directly to protect historical vegetable-tanned leathers.

To increase the understanding of how entrepreneurship education impacts entrepreneurial careers, the purpose of the paper is to investigate the role that a venture creation program (VCP) might have in mitigating or surpassing a lack of other antecedents of entrepreneurial careers. In particular, the authors focus on entrepreneurial pedigree and prior entrepreneurial experience.

Data from graduates of VCPs at three universities in Northern Europe were collected through an online survey. Questions addressed graduate background prior to education, yearly occupational employment subsequent to graduation and graduates' own perceptions of entrepreneurial activity in employment positions. The survey was sent to 1,326 graduates and received 692 responses (52.2% response rate).

The type of VCP, either independent (Ind-VCP) or corporate venture creation (Corp-VCP), influenced the mitigation of prior entrepreneurial experience. Prior entrepreneurial experience, together with Ind-VCP, made a career as self-employed more likely. However, this was not the case for Corp-VCP in subsequently choosing intrapreneurial careers. Entrepreneurial pedigree had no significant effect on career choice other than for hybrid careers.

Entrepreneurial experience gained from VCPs seems to influence graduates toward future entrepreneurial careers. Evidence supports the conclusion that many VCP graduates who lack prior entrepreneurial experience or entrepreneurial pedigree can develop sufficient entrepreneurial competencies through the program.

This study offers novel evidence that entrepreneurship education can compensate for a lack of prior entrepreneurial experience and exposure for students preparing for entrepreneurial careers.