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Digitally oriented firms are faced with new opportunities and risks in today’s ever-changing world. Drawing upon organisational entrainment theory, this study investigates how supply chain (SC) entrainment improves the effects of digital orientation on firm performance through absorbing risks and exploiting opportunities.

Survey data were collected from 307 Chinese manufactures and analysed using structural equation modelling and regression analysis.

The results show digital orientation absorbs risk through evoking three SC entrainment dimensions (i.e. internal entrainment, entrainment with customers and entrainment with suppliers). Entrainment with customers and suppliers mediate the relationship between internal entrainment and firm performance. An opportunity exploitation mechanism is evidenced by the moderating effects of internal and external entrainment on the relationship between digital orientation and firm performance.

The empirical findings provide timely insights for managers to fully harness the benefits of digital orientation by using SC entrainment, i.e. to match the tempo and pace of internal and external cyclical activities to reduce the risks and increase the benefits of adopting advanced digital technologies. The authors show managers how to adjust their organization’s actions to keep tempo and synchronous phase with their SC partners.

The study introduces and conceptualizes a construct (i.e. SC entrainment) to understand how risks and opportunities arising from digital transformation can be addressed to maximize the value of advanced digital technologies.

This study aims to investigate the structural characteristics, spatial evolution paths and internal driving mechanisms of the knowledge transfer (KT) network in China’s patent-intensive industries (PIIs). The authors' goal is to provide valuable insights to inform policy-making that fosters the development of relevant industries. The authors also aim to offer a fresh perspective for future spatiotemporal studies on industrial KT and innovation networks.

In this study, the authors analyze the patent transfer (PT) data of listed companies in China’s information and communication technology (ICT) industry, spanning from 2010 to 2021. The authors use social network analysis and the quadratic assignment procedure (QAP) method to explore the problem of China’s PIIs KT from the perspectives of technical characteristics evolution, network and spatial evolution and internal driving mechanisms.

The results indicate that the knowledge fields involved in the PT of China’s ICT industry primarily focus on digital information transmission technology. From 2010 to 2021, the scale of the ICT industry’s KT network expanded rapidly. However, the polarization of industrial knowledge distribution is becoming more serious. QAP regression analysis shows that economic proximity and geographical proximity do not affect KT activities. The similarity of knowledge application capacity, innovation capacity and technology demand categories in various regions has a certain degree of impact on KT in the ICT industry.

The current research on PIIs mainly focuses on measuring economic contributions and innovation efficiency, but less on KT in PIIs. This study explores KT in PIIs from the perspectives of technological characteristics, network and spatial evolution. The authors propose a theoretical framework to understand the internal driving mechanisms of industrial KT networks.

Devices for step estimation are body-worn devices used to compute steps taken and/or distance covered by the user. Even though textiles or clothing are foremost to come to mind in terms of articles meant to be worn, their prominence among devices and systems meant for cadence is overshadowed by electronic products such as accelerometers, wristbands and smart phones. Athletes and sports enthusiasts using knee sleeves should be able to track their performances and monitor workout progress without the need to carry other devices with no direct sport utility, such as wristbands and wearable accelerometers. The purpose of this study thus is to contribute to the broad area of wearable devices for cadence application by developing a cheap but effective and efficient stride measurement system based on a knee sleeve.

A textile strain sensor is designed by weft knitting silver-plated nylon yarn together with nylon DTY and covered elastic yarn using a 1 × 1 rib structure. The area occupied by the silver-plated yarn within the structure served as the strain sensor. It worked such that, upon being subjected to stress, the electrical resistance of the sensor increases and in turn, is restored when the stress is removed. The strip with the sensor is knitted separately and subsequently sewn to the knee sleeve. The knee sleeve is then connected to a custom-made signal acquisition and processing system. A volunteer was employed for a wearer trial.

Experimental results establish that the number of strides taken by the wearer can easily be correlated to the knee flexion and extension cycles of the wearer. The number of peaks computed by the signal acquisition and processing system is therefore counted to represent stride per minute. Therefore, the sensor is able to effectively count the number of strides taken by the user per minute. The coefficient of variation of over-ground test results yielded 0.03%, and stair climbing also obtained 0.14%, an indication of very high sensor repeatability.

The study was conducted using limited number of volunteers for the wearer trials.

By embedding textile piezoresistive sensors in some specific garments and or accessories, physical activity such as gait and its related data can be effectively measured.

To the best of our knowledge, this is the first application of piezoresistive sensing in the knee sleeve for stride estimation. Also, this study establishes that it is possible to attach (sew) already-knit textile strain sensors to apparel to effectuate smart functionality.

This study aims to investigate the extent and pattern of the influence of one of the most important decision-making tools in the context of social commerce. This study demonstrates how much customer testimonials (including verified purchases and ordinary users) can influence the sales rank of experience and search goods.

The data were collected by text mining and performing a content analysis on the XML documents of Web pages and processing them. For search goods, 22,311 opinions were recorded regarding 95 mobile phones. Additionally, for experience goods, 67,817 opinions were recorded regarding 162 books in the Amazon online store. The data were analyzed by functional regression method in longitudinal data analysis.

In terms of importance, the opinions and recommendations of verified purchases had a 60% greater impact on the sales rank of experience goods than the opinions and recommendations of ordinary users. In search goods, the opinions of ordinary users had a greater impact than the opinions of verified purchases. The historical effect of the opinions of ordinary users at the end of the review period on sales rank was evident, while the historical effect of the verified purchase viewpoints during the review period had a nonlinear curve. The results showed that it was necessary to increase the volume of comments to increase their reliability in experience goods.

Measuring the effect of customer testimonials helps the managers of retail websites design algorithms and online suggestion systems, thereby improving the sales of their products by providing information desired by customers.

Individuals can be a source of information and influence the buying decision process of others by sharing their experiences. This issue helps reduce the purchase risk and explains the importance of interaction and sharing the customer’s experience.

Analyzing the impact of customer testimonials by separating verified purchases and ordinary users is one of the advantages of this study. The quantitative estimation of the impact of recommendations and the provision of a model of their historical effect is one of the approaches not addressed in similar studies.

The purpose of this study is to analyse cyberfraud in the South African banking industry using a multiple regression approach and develop a predictive model for the estimation and prediction of financial losses due to cyberfraud.

To mitigate the occurrence of cyberfraud, this study uses the multiple regression approach to correlate the relationship between financial loss and cyberfraud activities. The cyberfraud activities in South Africa are classified into three, namely, digital banking application, online and mobile banking fraud. Secondary data that captures the rate of cyberfraud occurrences within these three major categories with their resulting financial losses were used for the multiple regression analysis that was carried out in the Statistical Package for Social Science (SPSS, 2022 environment).

The results obtained indicate that the South African financial institutions still incur significant financial losses due to cyberfraud perpetration. The two main independent variables used to estimate the magnitude of financial loss in the South Africa’s banking industry are online (internet) banking fraud (X2) and mobile banking fraud (X3). Furthermore, a multiple regression model equation was developed for the prediction of financial loss as a function of the two independent variables (X2 and X3).

This study adds to the literature on cyberfraud mitigation. The findings may promote the combat against cyberfraud in the South Africa’s financial institutions. It may also assist South Africa’s financial institutions to predict the financial loss that financial institutions can incur over time. It is recommended that South Africa’s financial institutions pay attention to these two key variables and mitigate any associated risks as they are crucial in determining their profitability.

Existing literature indicated significant financial losses to cyberfraud perpetration without establishing any relationship between the magnitude of losses incurred and the prevalent forms of cyberfraud. Thus, the novelty of this study lies in the analysis of cyberfraud in the South African banking industry using a multiple regression approach to link financial losses to the perpetration of the prevalent forms of cyberfraud. It also develops a predictive model for the estimation and projection of financial losses.

In the evolving landscape of global remittances, this study systematically explores cryptocurrency's transformative impact on remittance services through a comprehensive literature review and bibliometric analysis.

Through meticulous PRISMA-guided analysis, the research identifies cryptocurrency technology as a pivotal force in enhancing remittance efficiency, reducing costs and broadening access contributing significantly to financial inclusion.

Findings revealed that cryptocurrency technology could significantly enhance remittance services, offering improved efficiency, reduced costs and increased accessibility. This suggests a transformative potential for financial inclusion, presenting a compelling case for broader adoption and regulatory support to leverage these benefits effectively.

By integrating recent research, this work underlines the urgent need for broader adoption and regulatory support to leverage these benefits effectively. It offers novel insights for institutions and policymakers, highlighting the potential for technology adoption in remittances to enhance financial inclusivity.

More cryptocurrency studies are needed to concentrate on remittance markets. Thus, this investigation constitutes a unique addition to the field. Additional investigation in this domain presents significant possibilities for future exploration and progress.

The “experience is the best teacher” model assumes that acquiring expertise in a given domain reduces biases. Research in expert knowledge in investment decisions has shown better ability to produce improved results in asset selection or portfolio returns. Universities created student-managed investment funds (SMIFs) to train students in portfolio management as fiduciaries. However, analyses of the effectiveness of the SMIF as a medium for expert knowledge transfer have not been done.

The authors’ analyze an SMIF's structure against established models of expert knowledge transfer, using the voting patterns of the trustees of the fund from the recorded minutes of the fund's meetings to show the fund's structure and outcomes demonstrate effective knowledge transfer. Voter consensus between faculty and student trustees is one proxy the authors use for knowledge transfer.

Consensus between faculty and students was uniformly high across all recommendations. Chi-square tests were employed to test for independence between approval of recommendation and level of consensus, showing dependence in most cases. Analysis of sale returns over the 12-year sample period showed significantly better performance of asset sales over relevant benchmarks for both equity and fixed income portfolios.

Most analyses of SMIF structure concentrate on well-known issues with things like student turnover, summers or other structural issues. Performance is evaluated based on returns. This study looks at the SMIF as an expert knowledge transfer medium and examines expert/novice decision approval in terms of knowledge transfer.

The purpose of this paper was to investigate how recordkeepers in Canada, Finland, the Netherlands, New Zealand, Iceland and Italy experienced accomplishing their tasks from home over varying lengths of time during the COVID-19 pandemic.

A multilingual survey including 44 questions was designed and administered to the six countries identified above in 2022. This research was preceded by an environmental scan looking at existing studies considering archival and records management responses to the pandemic.

The impact of working from home on recordkeeping and, more generally, work performance was perceived differently by the survey respondents depending on various factors. The study also identified a number of similarities across countries, such as an increased awareness of the importance of records management shared by organizational actors. Surprisingly, the pandemic did not appear to have a great impact on the perceived quality of records management.

To the best of the authors’ knowledge, this is the first study aiming to capture records professionals’ perceptions of their role while working from home during the pandemic.

This paper aims to present investigations of the influence of sewing and adhesive bonding technology on the aesthetic, mechanical and conductive properties of the e-textile package. Commercially available conductive textiles are tested for the production of e-textile package by most common cut-and-sewn clothing production technologies.

Sewing, adhesive bonding and seam sealing technologies used to obtain e-textile packages with woven and knitted conductive textiles. Produced e-textile packages described in terms of thickness, bending rigidity and general appearance. Exploitation properties of prepared samples tested by cycle tensile experiment and discussed on the basis of variation of linear electrical resistance property.

Research has shown that a reliable e-textile package can be obtained by applying cut-and-sew technology for conductive tracks of silver coated woven and knitted material. Seam sealing by thermoplastic polymer layer has an impact on the electrical and deformation properties of the samples. To create attractive smart clothing design, the appropriate joining method and its technological parameters must be chosen to ensure the durability and safety of e-textile packages.

The findings of the research are of substantial value for the production of e-textiles by cut-and-sewn technologies. The required shape of the conductive textile element for various applications can be cut and joined to the garment parts using traditional sewing or adhesive bonding techniques.

Know your customer (KYC), accounting standards, issuance, clearing, and trade settlement became the major barrier to implement accounting, accountability and assurance process in supply chain finance (SCF). Blockchain technology features have the potential to solve accounting problems. This research focuses on exploring how blockchain technology provides solutions to overcome the barriers of accounting process in SCF. The benefits, opportunities, costs and risks related to blockchain adoption are also explored.

Multi-case study and qualitative methods are used with a framework based on blockchain role to overcome the accounting process barriers. Ten blockchain projects in SCF and 29 interviews of participants as a unit of analysis are considered.

The findings indicate that blockchain technology offers solutions to solve accounting, accountability and assurance problems in SCF. Validity, verification, smart contracts, automation and enduring data on trade transactions potentially solve those barriers. However, it is also necessary to consider costs such as implementation, technology, education and integration costs. Then there are possible risks such as regulatory compliance, operational, code development and scalability risk. This finding reflects the current status of blockchain technology roles in SCF.

This study unveils blockchain's SCF accounting potential, emphasizing multi-case method limitations and future research prospects. Diverse contexts challenge findings' applicability, warranting cross-industry studies for deeper insights. Addressing selection bias and integrating quantitative measures can enhance understanding of blockchain's accounting impact.

Accounting professionals can get an idea of the future direction and impact of blockchain technology on accounting, accountability and assurance processes.

This study provides initial findings on the potential, costs and risks of blockchain that is beneficial for parties involved in SCF, especially for banks and insurance underwriters. In addition, the findings also provide direction for the contribution of blockchain technology to accounting theory in the future.