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The purpose of this paper is to identify the radio frequency identification (RFID) strategic value attributes (RFIDSVAs) mechanism selections preferences and also integration of RFID tags with technology coordination tools (IRTWTCTs) alternatives ranking performance decisions in supply chain management (SCM). RFID-enabled techno-economic feasibility decisions are enhancing the SC visibility in apparel supply chains (ASCs). The RFIDSVAs mechanism selections have performed significant agility to strategic competitive advantages, namely, inventory visibility, multi-tags ownership transfer within trusted third party, etc.

Fuzzy analytical hierarchy process (FAHP) and FAHP-fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) approaches have been used to evaluate the quantitative assessment of RFIDSVA mechanisms selection decision based on weight priority orders and IRTWTCTs alternatives selection in ASC networks. The comparison of FAHP and FAHP-FTOPSIS approaches to evaluate the integrated framework develop in RFIDSVAs mechanisms and IRTWTCTs alternatives selection decisions in Indian multi-tier ASC networks.

The result found that the FAHP-FTOPSIS approaches have used to prioritizing the RFIDSVA mechanism selection weights and also identify the IRTWTCTs alternatives ranking preferences order in apparel SCM. The comparison between the FAHP and FAHP-FTOPSIS approach to quantitative assessments from RFIDSVA mechanisms and IRTWTCTs alternatives selection decisions, which enable them SC agility potential across multi-tier visibility in ASC networks. ASC stakeholders can be benefited by techno-economic feasibility decisions, RFID-enabled shop floor activities, multi-tags ownerships transfer in SCs and knowledge-based cryptography tags/items separation in SCs.

The research work has considered only five RFIDSVA mechanisms and also three integration of RFIDTWTCTs alternatives in multi-tier ASC. The strategic competitive advantages are achieved by RFID-enabled break-even tags price decisions and also techno-economic feasibility decision by contractual design multi-tier SC stakeholder’s involvements.

The pilot project study explores that the quantitative assessment decision has based on RFID-enable techno-economic feasibility in ASCs. Stakeholders can be benefited by inventory control of the financial losses, reducing the inventory inaccuracies and multi-tags ownership transfer within trusted third-party traceability in ASC networks.

This study explores the RFID-enabled apparel SC process and activities visibility (natural fibre’s fibre producer, fibre dyeing producer, yarn spinning producer, knitting and finishing producer).

Effective construction safety training has been considered to play a significant role in reducing the incidence of accidents. However, the current safety training methods pay less attention to the relationship between workers' personalized characteristics and their learning needs, which results in workers' low learning participation and poor training effect. The purpose of this paper is to improve the participation and effect of safety training for construction workers with a persona-based approach.

This paper presents a persona-based approach to safety tag generation and training material recommendation. By extracting the demographic characteristics and behavior patterns tags of construction workers, a neural network algorithm is introduced to calculate the learning needs tags of workers, and the collaborative filtering recommendation method is integrated to enrich the innovation of recommendation results. Offline experiments and online experiments are designed to verify the rationality of the proposed method.

The results show that the learning needs of workers are closely related to their background. The proposed method can effectively improve workers' interest in materials and the training effect compared with conventional safety training methods. The research provides a theoretical and practical reference for promoting active safety management and achieving worker-centered safety management.

First, a persona-based approach is introduced to establish a novel framework for solving the problem of personalized construction safety management. Second, an artificial intelligence algorithm is used to automatically extract the learning needs tag values and design a hybrid recommendation method for construction workers' personalized safety training. The collaborative filtering method is integrated to enrich the innovation of recommendation results.

The purpose of the research has been the primary consideration and evaluation of a cost effective, reliable, robust and simple process of radio frequency identification (RFID)-based stock control, asset management and monitoring of concrete safety bollards used in the road environment. Likewise, the consideration of the use of the same system and technology to other items in and around the general road infrastructure.

The research approach undertaken has been an evaluation of the use of currently available RFID technology, with a key emphasis on low cost, ease of use, reliability and convenience. Practical field exercises completed in considering the relevant RFID tags and readers and associated software and apps and necessary software integration and development have been undertaken. At the same time, evaluating the specific limits created in the specific environment is being applied. Of particular interest has been the use of a moving scan in a vehicle drive-through or pass-bye, type reading system. This has been determined to be viable and completely practical, drastically reducing the key issue of time-taken. Practical application of the system from idea to real life application has been undertaken. The integration of the use of the RFID tag and reader system with necessary and related software to database upload and storage has been established. The creation of an online facility to allow the appropriate use of the data and to include the convenient output of an asset report has been undertaken.

The findings have provided the necessary insight confirming the use of RFID technology as a simple yet reliable, cost effective and adaptable stock control, asset management and geo-locating system in the road environment. The use of such systems in this particular environment is in its infancy, and is perhaps novel and original in the specific aspect of using the system to stock control, manage and monitor road safety concrete bollards and other roadside objects in the road environment.

To establish if in fact, stock control geo-locating can be reliably undertaken with the use of RFID tags and readers in the specific road and road construction environment, particularly with the use of moving RFID reading of passive tags. To establish the minimum requirements of a field usable RFID tag and reader, specifically applicable to the concrete safety bollards, however to other roadside furniture. To identify the minimum requirements of a function, simple app to minimise general requirements of the overall stock control and monitoring of the RFID-tagged objects. To establish the possibility of reading the tag data, global positioning system (GPS) location and video imaging footage as a single operation function. To determine the basic parameters or limits of the GPS geo-locating, on the proposed products selected and overall system. To determine the current best practice in respect of reasonable accuracy and detail in relation to price considerations to a fully function stock control and monitoring system. To identify the minimum requirements of an online database to receive, house and provide ongoing access to and report on the data. To identify the key differences and benefits between traditional stock control and monitoring systems, against that of proposed RFID tag, read and geo-locating system.

The purpose of this research paper is to explore and offer insightful information on the useful use of Google Tag Manager (GTM) in the context of library websites and to bridge the gap between GTM’s technical features and the practical requirements of libraries. It gives libraries the ability to use GTM’s capabilities to increase user engagement, data-driven decision-making and improve online services.

This study reviews existing literature on GTM in the context of websites and libraries. The methodology involves identifying keywords and searching terms related to GTM, digital marketing, user engagement, Web analytics and library websites. Sources and databases were consulted, including library science journals, marketing journals, academic databases, publications on digital marketing and search platforms such as Google Books, Google Scholar, Google Search Engine, JSTOR and library associations like the American Library Association. Initial screening was done based on titles and abstracts, followed by a thorough-text review, categorization and synthesizing of the findings.

GTM provides libraries with a potent tool to improve their online presence, customize user experiences and collect insightful real-time data. Libraries may harness GTM’s potential to better engage people and provide services by properly implementing it and maintaining it over time. It can be a flexible instrument that supports contemporary library services in the digital era. The findings of this study indicate that GTM technology may be used in library services; nevertheless, there are several barriers, such as librarians’ attitudes and technical abilities, that prevent GTM acceptance in library services.

This study covers the implementation of a free GTM tool in library websites that will help the library and information professionals to leverage the GTM in the library’s online presence. Furthermore, this study recommends that libraries and librarians should develop guidelines and policies for the critical adoption of a free GTM tool in the library environment, which will support improving the library’s user engagement and tracking of library website traffic.

Gamification is a booming motivational approach in information systems. Leaderboards play a key role in gamification; however, there are mixed findings regarding the heterogeneous motivational impacts of leaderboard positions. This study aims to clarify the motivational effects of high and low leaderboard positions by assembling diverse behavioral measures and self-reports. The measures used in this study shed a light on the quantitative and qualitative dynamics of motivation facilitated by leaderboard positions. The authors inspect motivation in relation to satisfaction and frustration of competence need.

The authors conducted an online experiment set in a crowdsourcing context, asking the participants to compete in an image tagging game. Participants' leaderboard positions were manipulated to be either high or low for five consecutive rounds. The number of clicks, tags, duration of tagging and persistence on the task were measured as indicators of motivation.

High ranks on leaderboards induced complacent behaviors choosing easy ways to maintain their positions, while low ranks led the participants to stick to the right process of the task with intensified motivation round after round. However, neither of the motivations seemed to be of intrinsic nature.

The present study provides conclusive evidence on the varying motivational impact of leaderboard positions. The authors also demonstrate how the “needs-as-motive” model (Sheldon and Gunz, 2009) applies to gamification. Its implications in self-determination theory and gamification literature are discussed.

Process mining has emerged in the last decade as one of the most promising tools to discover and understand the actual execution of processes. This paper addresses the application of process mining techniques to analyze the performance of automatic guided vehicles (AGVs) in one of the Body in White circuits of the factory that Stellantis has in Vigo, Spain.

Standard process mining discovery and conformance algorithms are applied to analyze the different AGV execution paths, their lead times, main sources and identify any unexpected potential situations, such as unexpected paths or loops.

Results show that this method provides very useful insights which are not evident for logistics technicians. Even with such automated devices, where the room for decreased efficiency can be apparently small, process mining shows there are cases where unexpected situations occur, leading to an increase in circuit times and different variants for the same route, which pave the road for an actual improvement in performance and efficiency.

This paper provides evidence of the usefulness of applying process mining in manufacturing processes. Practical applications of process mining have traditionally been focused on processes related to services and management, such as order to cash and purchase to pay in enterprise resource planning software. Despite its potential for use in industrial manufacturing, such contributions are scarce in the current state of the art and, as far as we are aware of, do not fully justify its application.

This paper aims to explore the recognition and success of different ways of branding native advertising in influencer marketing.

The data are evaluated using statistical tests, correlation and cluster analysis.

It was found that the higher the recognition rate of a post tagged in a particular way, the better the tagging method for influencer marketing on Instagram. Based on the findings of this study, word tag is recommended first because it is flexible and has one of the highest recognition rates.

The generalizability of the results across different regional settings requires further investigation.

Good labeling of native advertising leads to greater success.

This study can be used by marketing managers, advertisers and influencers to gain insight into the issue, as well as to better select the appropriate labeling method for their advertising content.

Este trabajo tiene como objetivo explorar el reconocimiento y el éxito de diferentes formas de branding de publicidad nativa en el marketing de influencers.

Los datos se evalúan mediante pruebas estadísticas, correlación y análisis de conglomerados.

Se encontró que cuanto mayor es la tasa de reconocimiento de un post etiquetado de una manera particular, mejor es el método de etiquetado para el marketing de influencers en Instagram. Basándose en los resultados de este estudio, se recomienda en primer lugar el etiquetado por palabras porque es flexible y tiene una de las tasas de reconocimiento más altas.

Un buen etiquetado de la publicidad nativa conduce a un mayor éxito.

Este estudio puede ser utilizado por directores de marketing, anunciantes e influencers para obtener información sobre el tema, así como para seleccionar mejor el método de etiquetado adecuado para su contenido publicitario.

La generalizabilidad de los resultados en diferentes entornos regionales requiere más investigación.

本文旨在探讨影响者营销中不同方式的品牌原生广告的识别和成功。

使用统计测试、相关性和聚类分析对数据进行评估。

研究发现, 以特定方式标记的帖子的识别率越高, Instagram上影响者营销的标记方式就越好。基于这项研究的结果, 首先推荐单词标签, 因为它很灵活, 而且有最高的识别率之一。

对原生广告进行良好的标注会带来更大的成功。

本研究可供营销经理、广告商和影响者使用, 以深入了解这一问题, 并更好地为其广告内容选择合适的标签方法。

研究结果在不同地区环境中的普适性需要进一步调查。

There is a growing trend among online merchants to conduct help-request marketing campaigns (HMCs), which refers to a kind of marketing campaign that leverages participants' help-request to encourage the subsequent engagement of participants' online friends. The paper aims to investigate how individuals respond to online HMCs in social networking groups (SNGs). Integrating the norm activation model and regulatory focus theory, this paper examines the mediation effects of the two facets of responsibility perception, i.e. perceived causality and perceived answerability.

A field experiment was conducted by organizing a real HMC on WeChat. To manipulate request individuation, experimental confederates were engaged to serve as requesters in the HMC. The actual responses provided by the recipients (subjects) were captured via the HMC pages. The multiple-group analysis was used for data analysis.

Empirical results reveal that request individuation strengthens the effect of relationship closeness on perceived causality but reverses the effect of relationship closeness on perceived answerability from being positive to negative. Except for the negligible impact of perceived answerability on inaction, both perceived causality and perceived answerability affect recipients' reactions to HMCs as expected.

First, social media platforms should promote other-oriented prosocial values when designing features or launching campaigns. Second, the designers of HMCs should introduce a “tagging” feature in HMCs and provide additional bonuses for requesters who perform tagging. Third, HMC requesters should prudently select tagging targets when making a request.

First, this paper contributes to the literature on social media engagement by identifying responsibility as an other-oriented motivation for individuals' social media engagement. Second, this paper also extends our understanding of responsibility by dividing it into perceived causality and answerability as well as measuring them with self-developed instruments. Third, this study contributes to the research on WOM by demonstrating that individuals' response behaviors toward help-requests embedded in HMCs can take the form of proactive helping, reactive helping or inaction.

Online question-and-answer (Q&A) communities serve as important channels for knowledge diffusion. The purpose of this study is to investigate the dynamic development process of online knowledge systems and explore the final or progressive state of system development. By measuring the nonlinear characteristics of knowledge systems from the perspective of complexity science, the authors aim to enrich the perspective and method of the research on the dynamics of knowledge systems, and to deeply understand the behavior rules of knowledge systems.

The authors collected data from the programming-related Q&A site Stack Overflow for a ten-year period (2008–2017) and included 48,373 tags in the analyses. The number of tags is taken as the time series, the correlation dimension and the maximum Lyapunov index are used to examine the chaos of the system and the Volterra series multistep forecast method is used to predict the system state.

There are strange attractors in the system, the whole system is complex but bounded and its evolution is bound to approach a relatively stable range. Empirical analyses indicate that chaos exists in the process of knowledge sharing in this social labeling system, and the period of change over time is about one week.

This study contributes to revealing the evolutionary cycle of knowledge stock in online knowledge systems and further indicates how this dynamic evolution can help in the setting of platform mechanics and resource inputs.

This study assessed two technology systems aimed at enabling a man with intellectual disability, blindness, deafness and motor and tactile discrimination problems to make verbal requests through simple one-hand signs.

The study was conducted according to an ABAB design. During the B (intervention) phases, the man used the two systems, which included (1) nine mini recording devices fixed on the man’s clothes or wheelchair (i.e. in positions the man touched with his sign movements) and (2) nine tags with radio frequency identification codes (fixed at approximately the same positions as the mini recording devices) and a dedicated tag reader, respectively. Making a sign (i.e. touching a recording device or reaching a tag) led to the verbalization of the request related to that sign.

During baseline, the mean frequency of signs/requests made was below 2 per session, and only some of those requests were identified/satisfied. During the intervention, the mean frequency of requests made and satisfied was about 10 per session with each of the systems.

The results, which are to be taken with caution given the preliminary nature of the study, seem to suggest that the systems can help translate simple signs into verbal requests.