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The study aims to address the cataloguing challenges faced by Taka Museum, a prominent coin museum in Bangladesh. The focus is on improving coin identification, metadata management and accessibility.

This study evaluates the effectiveness of Taka Museum’s current cataloguing methodologies for numismatic collections from the 6th Century BCE to the 6th Century CE.

The study identifies the primary issues hindering cataloguing at Taka Museum as missing ruler, period and coin source information. The proposed recommendations aim to address these challenges and improve the overall cataloguing process.

Firstly, establish a reliable identifier system for each coin to facilitate accurate tracking and identification. Secondly, implementing automated coin recognition systems can enhance the efficiency and accuracy of coin identification, reducing reliance on manual methods. Thirdly, developing comprehensive metadata standards and bibliographic information to ensure that necessary information is captured and preserved. Fourthly, prioritizing training and capacity building to equip staff with the necessary skills to use new technologies and methodologies effectively. Finally, foster collaboration with experts in machine learning and AI to obtain the technical expertise required for implementing and maintaining advanced recognition systems.

The paper contributes to the field by providing practical solutions to cataloguing challenges faced by coin museums. The proposed strategies can be applied to other similar institutions, enhancing the preservation and accessibility of their collections. By improving cataloguing practices, Taka Museum can better serve researchers, educators and the public.

This research aims to uncover how the adoption process of a mobile payment solution unfolds in its local use. We examined micro-enterprises’ adoption of UPI-based payment system in India.

We employed an ethnographic approach to study the micro-entrepreneurs’ daily practice and adopted a relational ontology to conduct an “in-practice” enquiry of the UPI payment adoption process.

Applying the practice perspective of Technology Affordances and Constraints Theory, we found that UPI adoption was shaped through a dynamic interplay of emerging affordances and constraints. New features, such as All-in-one QR, enabled actions like cross-platform money transfer but also introduced challenges like fraud. Advancements in the technology addressed previous challenges but also created new hurdles. This cycle of evolving affordances and constraints within the contextual use of UPI payment technology shaped its adoption process.

The findings contribute to the existing body of mobile payment literature by elucidating the role of localized and ongoing enactment of affordances and constraints. Unlike existing adoption theories, using relational concepts of affordances and constraints revealed how the integration of mobile payment into practice leads to emergent use patterns and widespread adoption.

We emphasize the need for solutions that address localized challenges and contextual needs. The study advises policymakers to consider technology’s benefits and limitations in interventions.

The study offers a unique view on mobile payment adoption, highlighting the role of technological materiality and temporality. It reveals how the changing materiality of technology shapes the adoption process through localized affordances and constraints.

With the changing landscape of the globalised business world, business-to-business supply chains face a turbulent ocean of disruptions. Such is the effect that supply chains are disrupted to the point of failure, supply is halted and its adverse effect is seen on the consumer. While previous literature has extensively studied risk and resilience through mathematical modelling, this study aims to envision a novel supply chain model that integrates blockchain to support visibility and recovery resilience strategies.

The stochastic bi-objective (cost and shortage utility) optimisation-based mixed-integer linear programming model integrates blockchain through a binary variable, which activates at a particular threshold risk-averse level of the decision-maker.

Firstly, visibility is improved, as identified by the average reduction of penalties by 36% over the different scenarios. Secondly, the average sum of shortages over different scenarios is consequently reduced by 36% as the recovery of primary suppliers improves. Thirdly, the feeling of shortage unfairness between distributors is significantly reduced by applying blockchain. Fourthly, unreliable direct suppliers resume their supply due to the availability of timely information through blockchain. Lastly, reliance on backup suppliers is reduced as direct suppliers recover conveniently.

The findings indicate that blockchain can enhance visibility and recovery even under high-impact disruption conditions. Furthermore, the study introduces a unique metric for measuring visibility, i.e. penalty costs (lower penalty costs indicate higher visibility and vice versa). The study also improves upon shortages and recoveries reported in prior literature by 6%. Finally, blockchain application caters to the literature on shortage unfairness by significantly reducing the feeling of shortage unfairness among distributors.

This study establishes blockchain as a pro-resilience technology. It advocates that organisations focus on investing in blockchain to enhance their visibility and recovery, as it effectively reduces absolute shortages and feelings of shortage unfairness while improving recovery and visibility.

To the best of the authors’ knowledge, this is a unique supply chain model study that integrates a technology such as blockchain directly as a binary variable in the model constraint equations while also focusing on resilience strategies, costs, risk aversion and shortage unfairness.

Limited research has espoused a comparative perspective to study social networking sites’ (SNS) use continuance despite most of them being abandoned after initial adoption. Most existing empirical works have been undertaken in western contexts, and they do not consider country-origin influence. Thus, they are of little benefit to global and transnational organizations. Awareness of countries’ similarities and contrasts provides the basis for understanding people’s behaviors in cross-cultural contexts, which can be crucial to ensuring technology acceptance and success, especially in multinational organizations. Our research aims to explain why and how people use SNSs sustainably in the workplace through a model and comparative study.

The theoretical framework was developed to integrate and extend two major behavioral adoption and technology use models in explaining SNS use continuance. This paper collected data through a survey and analyzed it using structural equation modeling through partial least squares (PLS).

One major contribution of this study is to highlight that the users in selected countries are driven strongly by subconscious factors rather than traditional factors based on the system attributes and users’ perceived rationality of continuing to use SNSs.

This paper recommends that the model in this study be tested in other technology environments to evaluate the external validity of the research study. The research was based on an unspecified platform, but each SNS may have its own singularities that should merit further consideration.

This paper will contribute to the literature by integrating and extending two major theoretical frameworks and espousing a cross-national perspective.

According to extant Supply Chain Risk Management (SCRM) literature, manufacturing firms must align their choice of SC bridging or buffering strategies with their operating environment to achieve high plant performance and minimize SC disruption impacts. However, very few empirical studies have examined the relative performance of these strategies in dynamic industry environments. This study aims to address this research gap. This study also seeks to supplement the limited empirical research that has examined the empirical relationships between a firm’s Supply Base Complexity (SBC), the likelihood of SC disruptions, and plant performance.

This study uses data from a cross-sectional survey of 202 manufacturing firms in India. The data is analyzed, and the study hypotheses are tested using PLS path modeling and SPSS PROCESS Macro.

The study shows that increased SBC leads to an increased frequency of SC disruptions with a negative impact on plant performance. The study also finds that the firm’s implementation of SC bridging or buffering strategies effectively moderates this performance impact. However, the study results do not support the hypothesis that industry dynamism moderates the relative effectiveness of SC bridging or buffering strategies in mitigating the negative impact of SC disruptions.

The study adds to the limited empirical research examining the SC disruption risk associated with SBC and the resulting performance impact. It addresses a gap in extant research by evaluating the efficacy of SC bridging and buffering strategies in mitigating this performance impact in dynamic industry environments.