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The main goal of this research work is the optimization of the purchasing business process in the Moroccan public sector in terms of transparency and budgetary optimization. The authors have worked on the public university as an implementation field.

The design of the research work followed the design science research (DSR) methodology for information systems. DSR is a research paradigm wherein a designer answers questions relevant to human problems through the creation of innovative artifacts, thereby contributing new knowledge to the body of scientific evidence. The authors have adopted a techno-functional approach. The technical part consists of the development of an intelligent recommendation system that supports the choice of optimal information technology (IT) equipment for decision-makers. This intelligent recommendation system relies on a set of functional and business concepts, namely the Moroccan normative laws and Control Objectives for Information and Related Technology's (COBIT) guidelines in information system governance.

The modeling of business processes in public universities is established using business process model and notation (BPMN) in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature. Implementation of artificial intelligence techniques can bring great value in terms of transparency and fluidity in purchasing business process execution.

Business limitations: First, the proposed system was modeled to handle one type products, which are computer-related equipment. Hence, the authors intend to extend the model to other types of products in future works. Conversely, the system proposes optimal purchasing order and assumes that decision makers will rely on this optimal purchasing order to choose between offers. In fact, as a perspective, the authors plan to work on a complete automation of the workflow to also include vendor selection and offer validation. Technical limitations: Natural language processing (NLP) is a widely used sentiment analysis (SA) technique that enabled the authors to validate the proposed system. Even working on samples of datasets, the authors noticed NLP dependency on huge computing power. The authors intend to experiment with learning and knowledge-based SA and assess the' computing power consumption and accuracy of the analysis compared to NLP. Another technical limitation is related to the web scraping technique; in fact, the users' reviews are crucial for the authors' system. To guarantee timeliness and reliable reviews, the system has to look automatically in websites, which confront the authors with the limitations of the web scraping like the permanent changing of website structure and scraping restrictions.

The modeling of business processes in public universities is established using BPMN in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature.

The adopted techno-functional approach enabled the authors to bring information system governance from a highly abstract level to a practical implementation where the theoretical best practices and guidelines are transformed to a tangible application.

Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic data sets on air quality (AQ) predictions has not been fully investigated. This paper aims to investigate the effects traffic data set have on the performance of machine learning (ML) predictive models in AQ prediction.

To achieve this, the authors have set up an experiment with the control data set having only the AQ data set and meteorological (Met) data set, while the experimental data set is made up of the AQ data set, Met data set and traffic data set. Several ML models (such as extra trees regressor, eXtreme gradient boosting regressor, random forest regressor, K-neighbors regressor and two others) were trained, tested and compared on these individual combinations of data sets to predict the volume of PM_2.5, PM₁₀, NO₂ and O₃ in the atmosphere at various times of the day.

The result obtained showed that various ML algorithms react differently to the traffic data set despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%.

This research is limited in terms of the study area, and the result cannot be generalized outside of the UK as some of the inherent conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research, therefore, leaving out a few other ML algorithms.

This study reinforces the belief that the traffic data set has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form of traffic data set in the development of an AQ prediction model. This implies that developers and researchers in AQ prediction need to identify the ML algorithms that behave in their best interest before implementation.

The result of this study will enable researchers to focus more on algorithms of benefit when using traffic data sets in AQ prediction.

In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

Disinformation on social media is a serious issue. This study examines the effects of disinformation on COVID-19 vaccination decision-making to understand how social media users make healthcare decisions when disinformation is presented in their social media feeds. It examines trust in post owners as a moderator on the relationship between information types (i.e. disinformation and factual information) and vaccination decision-making.

This study conducts a scenario-based web survey experiment to collect extensive survey data from social media users.

This study reveals that information types differently affect social media users' COVID-19 vaccination decision-making and finds a moderating effect of trust in post owners on the relationship between information types and vaccination decision-making. For those who have a high degree of trust in post owners, the effect of information types on vaccination decision-making becomes large. In contrast, information types do not affect the decision-making of those who have a very low degree of trust in post owners. Besides, identification and compliance are found to affect trust in post owners.

This study contributes to the literature on online disinformation and individual healthcare decision-making by demonstrating the effect of disinformation on vaccination decision-making and providing empirical evidence on how trust in post owners impacts the effects of information types on vaccination decision-making. This study focuses on trust in post owners, unlike prior studies that focus on trust in information or social media platforms.

The purpose of this paper is to study the effects of sports sponsorship on brand equity using two managerially related outcomes: price premium and market share.

This study uses a best–worst discrete choice experiment (BWDCE) and compares the outcome with that of the purchase intention scale, an established probabilistic measure of purchase intention. The total sample consists of 409 fans of three soccer teams sponsored by three different competing brands: Nike, Adidas and Puma.

With sports sponsorship, fans were willing to pay more for the sponsor’s product, with the sponsoring brand obtaining the highest market share. Prominent brands generally performed better than less prominent brands. The best–worst scaling method was also 35% more accurate in predicting brand choice than a purchase intention scale.

Future research could use the same method to study other types of sponsors, such as title sponsors or other product categories.

Sponsorship managers can use this methodology to assess the return on investment in sponsorship engagement.

Prior sponsorship studies on brand equity tend to ignore market share or fans’ willingness to pay a price premium for a sponsor’s goods and services. However, these two measures are crucial in assessing the effectiveness of sponsorship. This study demonstrates how to conduct such an assessment using the BWDCE method. It provides a clearer picture of sponsorship in terms of its economic value, which is more managerially useful.

Today, with the increasing involvement of the environment and human beings business units, paying attention to fulfilling social responsibility obligations while making a profit has become increasingly necessary for achieving sustainable development goals. Attention to profit by organizations should not be without regard to their social and environmental performance. Social responsibility accounting (SRA) is an approach that can pay more attention to the social and environmental performance of companies, but it has many barriers. Therefore, the purpose of this study is to identify barriers to SRA implementation and provide strategies to overcome these barriers.

In this study, the authors identify barriers to social responsibility accounting implementation and provide strategies to overcome these barriers. By literature review, 12 barriers and seven strategies were identified and approved using the opinions of six academic experts. Interpretive structural modeling (ISM) has been used to identify significant barriers and find textual relationships between them. The fuzzy technique for order performance by similarity to ideal solution (TOPSIS) method has been used to identify and rank strategies for overcoming these barriers. This study was undertaken in Iran (an emerging market). The data has been gathered from 18 experts selected using purposive sampling and included CEOs of the organization, senior accountants and active researchers well familiar with the field of social responsibility accounting.

Based on the results of this study, the cultural differences barrier was introduced as the primary and underlying barrier of the social responsibility accounting barriers model. At the next level, barriers such as “lack of public awareness of the importance of social responsibility accounting, lack of social responsibility accounting implementation regulations and organization size” are significant barriers to social responsibility accounting implementation. Removing these barriers will help remove other barriers in this direction. In addition, the results of the TOPSIS method showed that “mandatory regulations, the introduction of guidelines and social responsibility accounting standards,” “regulatory developments and government incentive schemes to implement social responsibility accounting,” as well as “increasing public awareness of the benefits of social responsibility accounting” are some of the essential social responsibility accounting implementation strategies.

The findings of the study have implications for both professional accounting bodies for developing the necessary standards and for policymakers for adopting policies that facilitate the implementation of social responsibility accounting to achieve sustainability.

This paper creates a new perspective on the practical implementation of social responsibility accounting, closely related to improving environmental performance and increasing social welfare through improving sustainability.

Experts believe that the strategies mentioned above will be very effective and helpful in removing the barriers of the lower level of the model. To the best of the authors’ knowledge, for the first time, this study develops a model of social responsibility accounting barriers and ranks the most critical implementation strategies.

To investigate the influence of logistics and transportation workers’ perceptions of their management’s simultaneous safety and operations focus (or lack thereof) on related worker safety and operational perceptions and behaviors.

This multi-method research consisted of two studies. Study 1 aimed to establish correlational relationships by evaluating the impact of individual-level worker perceptions of operationally focused routines (as a moderator) on the relationship between worker perceptions of safety-related routines and workers’ self-reported safety and in-role operational behaviors using a survey. Study 2 aimed to establish causal relationships by evaluating the same conceptual relationships in a behavioral-type experiment utilizing vehicle simulators. After receiving one of four pre-task briefings, participants completed a driving task scenario in a driving simulator.

In Study 1, the relationship between perceived safety focus and safety behavior/in-role operational behavior was strengthened at higher levels of perceived operations focus. In Study 2, participants who received the balanced pre-task briefing committed significantly fewer safety violations than the other 3 treatment groups. However, in-role driving deviations were not impacted as hypothesized.

This research is conducted at the individual (worker) level of analysis to capture the little-known perspectives of logistics and transportation workers and explore the influence of balanced safety and operational routines from a more micro perspective, thus contributing to a deeper understanding of how balanced routines might influence worker behavior when conducting dynamic tasks to ensure safe, effective outcomes.

In order to better optimize the internal management system of book publishing and to cope with the changes in the external market environment, the purpose of this paper is to carry out cross-border publishing with the help of a transmedia storytelling model to realize the transformation and upgrading of the industry. Focusing on the relationship between the book publishing transmedia storytelling model and business performance, the moderating effect of the innovation environment on different variables is assessed.

This paper proposes several feasible hypotheses based on existing research. The research data came from 365 managers of Chinese book publishing organizations, and the scale was validated by Cronbach’s a, composite reliability (CR) and average variance extracted (AVE). Reliability and validity were verified, and correlation and regression analyses were used to test the impact of the book publishing transmedia storytelling model on business performance and to analyze the moderating role of the innovation environment.

The results show that the book publishing transmedia storytelling model (content production, technology integration, organizational innovation, marketing integration) helps to improve business performance (market performance, financial performance), and the innovation environment has a positive moderating effect on the relationship between the book publishing transmedia storytelling model and business performance, which provides a guarantee for the transformation and upgrading of book publishing. The market information reflected in the innovation environment has a certain role in promoting the innovation and business performance of the book publishing transmedia storytelling model.

The empirical evidence provides a theoretical link between the book publishing transmedia storytelling model and business performance, but there are still some shortcomings, and more factors, such as equity structure, government subsidies and research and development investment, should be included in future research. In addition, the scope of the research should be broadened on this basis to make the results of the data analysis more objective.

This paper introduces the transmedia storytelling model and deeply analyzes the relationship between the book publishing transmedia storytelling model and business performance, which is of great practical significance for optimizing the application and service quality of book publishing, prolonging the industrial chain, enhancing the interaction and participation of users and perfecting the business management system of the book publishing industry.

The application and research of the book publishing transmedia storytelling model are imperfect. Therefore, this paper not only helps to promote the innovation of book publishing organizational structure and improve the management system of business performance, but also may help to improve the innovation environment of book publishing enterprises and promote the diversification of industrial structure.

Recently emerged Packaging-as-a-Service (PaaS) systems adopt aspects of access-based services and triadic frameworks, which have typically been treated as conceptually separate. The purpose of this paper is to investigate the implications of blending the two in what we call “access-based triadic systems,” by empirically evaluating intentions to adopt PaaS systems for takeaway food among restaurants and consumers.

We derived relevant attributes of PaaS systems from a qualitative pre-study with restaurants and consumers. Next, we conducted two factorial survey experiments with restaurants (N = 176) and consumers (N = 245) in Germany to quantitatively test the effects of those system attributes on their adoption intentions.

This paper highlights that the role of access-based triadic system providers as both the owners of shared assets and the operators of a triadic system is associated with a novel set of challenges and opportunities: System providers need to attract a critical mass of business and end customers while balancing asset protection and system complexity. At the same time, asset ownership introduces opportunities for improved quality control and differentiation from competition.

Conceptually, this paper extends research on access-based services and triadic frameworks by describing an unexplored hybrid form of non-ownership consumption we call “access-based triadic systems.” Empirically, this paper addresses the need to account for the demands of two distinct target groups in triadic systems and demonstrates how factorial survey experiments can be leveraged in this field.

This study aims to increase the novelty of clothing design and fabric texture. The element library that can be used for design is systematically summarized. The element database can also be continuously filled according to the existing logic to realize the diversity of design. Improve the theory of fashion design, expand the designer's design ideas and improve design efficiency. Clear design steps and logic can help students and machines learn the design process and promote the development of intelligent design. And verify the feasibility of the simulation software to assist pleated clothing design.

Firstly, according to the logical framework of origami theory, different innovative designs and combined designs are made for the basic units of hyperbolic paraboloid, and the element library that can be used for design is systematically summarized. This database can also be continuously filled according to the existing logic to realize the diversity of design. Secondly, it summarizes three methods of pleated element filling clothing – uniform filling method, the irregular filling method and geometric addition method – that improve the theory of fashion design, expand the designer's design ideas and improve design efficiency. Clear design steps and logic can help students and machines learn the design process and promote the development of intelligent design. Finally, the virtual software is used to simulate the effect of pleated clothing, and the three-dimensional simulation software 3dclo is used to make an empirical study on the application of hyperbolic paraboloid origami in clothing pleated design to verify the feasibility of the simulation software to assist pleated clothing design.

The theoretical results of hyperbolic paraboloid origami are collected and arranged to establish the element library of hyperbolic paraboloid origami. The results expand the designer's design ideas and auxiliary design technology and improve the design efficiency using a sample of hyperbolic paraboloid fabric to verify its practicability and three-dimensional clothing simulation software for exploring the design. The design rules of hyperbolic paraboloid clothing and the realization method of fabric are summarized, including the expansion and combing of elements, the application of size and shape and the method of combination.

Owing to the hyperbolic paraboloid origami’s length shrinkage, the loose computation of clothing requires targeted computation. This paper solely applies a paper model for estimating the shrinkage, and then we tend to subsequently explore the way to precisely compute the porosity, to determine the existing differences in the two-dimensional shrinkage of hyperbolic paraboloid creases of varying materials and to know if the clothing after large-scale production is capable of reaching the anticipated value.

The exploration of this experiment brings a new 3D experiment process to the design process.

This experiment brings new possibilities for the development of virtual fitting and virtual display in the industry.

This study combines hyperbolic paraboloid origami and clothing and combs and expands the unit with logical thinking to expand the designer's design ideas.