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This study demonstrates a practical use of Actor-Network Theory (ANT), showing methodological, predictive and unforeseen issues that emerged during the data collection and analysis phases and how they were addressed during the development of this research.

Based on the research of reapplication of a “tecnologia social” (TS) of entrepreneurial education, this article explores the author’s reflections on the adoption of ANT as a theoretical-methodological approach, highlighting the practical implications of a social material theory during fieldwork.

The adoption of ANT places the researcher in front of methodological issues not always foreseen in the research design. Four moments to a practical path through the engagement of ANT agency are highlighted: the network of actors, monitoring of actors, interpretation of data collected and writing results. These moments correspond to methodological issues that the authors faced during the practical journey of the research. At each moment, the challenge aroused is discussed and the methodological choice chosen to address the issue is presented.

The engagement with ANT has enormous potential in the study of management and organizations phenomenon, but its methodological implications in practice are still challenging. The authors seek to share this investigation and engagement in ANT so that other researchers have a reference and a starting point to employ and engage in this theoretical-methodological lens. Thus, it may be possible to anticipate certain difficulties in future research designs and to glimpse at potential developments and paths that the research may lead.

The significance of smart mobility practices in shaping cities from a smart perspective has grown in recent years, influencing policies and the choices made by inhabitants. This transformation has led to the emergence of novel services and strategies, creating a new, vibrant and highly personalised urban environment that caters to the needs and preferences of both local residents and visitors. The purpose of this study is to evaluate the influence of smart mobility practices on tourism flows in cities, considering the moderating effect of airport activities on this relationship.

Using a generalised method of moments estimation and focusing on 20 Italian cities over an eight-year period, the authors highlight the current relationship between smart mobility practices and tourism flows. Moreover, the authors demonstrate that the yearly advancement of airports positively moderates this relationship.

The findings indicate a significant relationship between smart mobility practices in modern cities and tourism inflows because they influence the development of tourism services and emerging trends such as smart tourism and smart destinations. Furthermore, airport activities as a proxy for city openness play a crucial role in this link. The study shows that airports have an incremental impact on tourism and on the relationship between tourism and sustainable practices.

The limitations of this quantitative approach include the focus on a single country, the challenge of measuring the development of smart mobility practices due to a lack of standardised variables and the need for future research to expand the sample to different countries in relation to tourism inflows.

This study has practical implications for policymakers and governance in their task of effectively coordinating internal smart mobility practices and managing incoming tourism flows.

This study has social implications, highlighting the need for policymakers and governance to address the societal impacts of smart mobility practices and tourism inflows, ensuring inclusive and sustainable outcomes for local communities.

This study contributes to the existing literature as one of the first attempts to examine the interplay between smart mobility practices in smart cities and tourism flows. Furthermore, it emphasises the role of airports in this relationship, highlighting how the interaction between these variables benefits both stakeholders.

In this study, the authors use the actor-network theory (ANT) as a theoretical framework to better understand constructing learning as part of the networking process to produce innovations. Focussing on the antecedents of innovation within three teams in an engineering company, the authors propose a framework to enhance understanding of the innovative processes. The authors apply ANT to examine how informal learning is distributed amongst human and non-human actors.

Based on 27 interviews in a large Australian engineering company, the authors' qualitative investigation shows that innovation can have very different antecedents. The authors mobilised ANT as the authors' vantage point to explore inanimate actors and their effect on social processes or, more specifically, networks and informal learning.

The authors propose a framework to better understand innovative processes by exploring the network aspects of non-human actors and their connection to learning. More specifically, findings contribute towards a more granulated understanding of how networks, learning and non-human actors contribute towards innovations in organisations.

This study has three significant implications for managers and organisations looking to improve their innovation processes. Firstly, fostering open communication is essential for developing successful innovation processes. Secondly, a close relationship with the customer and/or the final users has often been found to positively contribute to innovation processes. Finally, intrateam motivation is also critical when it comes to creating an environment that supports innovation processes.

Surprisingly, leadership, communication and motivation did not give the best innovative outcome as the authors expected. Challenging traditional theorisations, low teamwork spirit and high individual performance orientation were some of the powerful drivers of highly innovative teams.

The development of information technologies has led to a considerable transformation in human resource management from conventional or commonly known as personnel management to modern one. Data mining technology, which has been widely used in several applications, including those that function on the web, includes clustering algorithms as a key component. Web intelligence is a recent academic field that calls for sophisticated analytics and machine learning techniques to facilitate information discovery, particularly on the web. Human resource data gathered from the web are typically enormous, highly complex, dynamic, and unstructured. Traditional clustering methods need to be upgraded because they are ineffective. Standard clustering algorithms are enhanced and expanded with optimization capabilities to address this difficulty by swarm intelligence, a subset of nature-inspired computing. We collect the initial raw human resource data and preprocess the data wherein data cleaning, data normalization, and data integration takes place. The proposed K-C-means-data driven cuckoo bat optimization algorithm (KCM-DCBOA) is used for clustering of the human resource data. The feature extraction is done using principal component analysis (PCA) and the classification of human resource data is done using support vector machine (SVM). Other approaches from the literature were contrasted with the suggested approach. According to the experimental findings, the suggested technique has extremely promising features in terms of the quality of clustering and execution time.

Crisis response has emerged as a salient concern for firms in the onset of COVID-19. While research suggests that resilience is critical during such disruptions, there remains a need to examine how firms build resilience during evolving situations. This study focuses on resiliency created through operational flexibility and examines how firms developed resiliency to COVID-19 through an adaptation of three technology-based levers of flexibility: change in a firm's product and service offerings, the channel it uses for sales and the location of a firm's workforce.

This study uses a unique cross-sectional dataset generated from a survey administered by a reputable financial institution, from March 20 to June 20, during the inception of COVID crisis. This study uses ordinary least squares to analyze data from 6,076 firms across 20 countries.

Results indicate that flexibility through a combination of a change in a firm's product and service offerings, with movement to selling through a digital channel, had a positive impact on firm sales. However, flexibility through a combination of change in product and service offerings with workforce location changes had negative impacts. Robustness analysis indicates that negative impacts worsen in countries with higher digitization and in manufacturing and retail firms as compared to service firms, indicating the inflexibility of physical goods–based business models. Results highlight dimensions through which technology-based flexibility can take place and the benefits of flexibility on firm performance.

This study provides managerial insights into technology-based operational flexibility mechanisms that can be employed for building performance resilience during unexpected disruptions. Research findings inform firms facing supply chain challenges and inflation pressures of business today.

The purpose of this paper is to study the correlational and effect relationship between Halal standards and the performance of Halal-certified Palestinian Food Companies.

Quantitative method was used, using a questionnaire survey of 40 Halal-certified Palestinian organizations out of a total of 47 certified organizations, the analysis was done using the partial least squares structural equation modeling (PLS-SEM) and the literature review was conducted using a well-known systematic literature review methodology.

Halal implementation and certification had a positive impact on performance (operational, financial and marketing). The depth/intensity of implementation fully mediates operational performance and partially mediates marketing and financial performance.

As the sample size is small, it is recommended to conduct the study using a larger sample size, once the number of Palestinian Halal-certified organizations increases. A longitudinal or panel study is recommended to capture data that are more accurate and avoid objectivity and bias issues using a cross-sectional research design method. Finally, the study recommends to conduct additional research in the field of Halal awareness for customers to gage their intention and welling to buy Halal products within the Middle East region.

The importance of this study exists in the lack of previous Halal-related studies in the Palestinian context and the previously described gap in the literature. Nevertheless, the quality management drivers and impact are limited in the Palestinian context compared with other contexts; the results of the previously published studies revealed mixed results such as the drivers of quality management are based on the type of business. Finally, this research gives small insights and directions toward conducting additional studies concerning customer awareness about Halal products.

Drawing on the work of Niklas Luhmann, the paper argues that technology can be viewed as a self-referential system which is autonomous from both human beings and other function systems of society. The paper aims to develop a philosophy of technology from the work of Niklas Luhmann. To achieve this aim, it draws upon the systems-theory work of Jacques Ellul, a philosopher of technology who focuses on the autonomous potential of technological evolution.

The paper draws on the work of Niklas Luhmann and Jacques Ellul to explore the theme of autonomous technology and what this means for our thinking about technological issues in the twenty-first century. Insights from these two thinkers and researchers working in the Luhmannian sociological tradition are applied to remote work.

The sociological approach of Luhmann, coupled with Ellul's insights into the autonomous nature of technology, can help us develop a systems theory of technology which takes seriously its irreducibility to human functions.

The paper contributes to the growing sociological literature that thematizes the Luhmannian approach to technology, helping us better understand this phenomenon and think in new ways about what technological autonomy means.

The paper brings together the work of Luhmann, Ellul and contemporary researchers to advance a new understanding of technology and technological communication.

This exploratory study aims to investigate the use of Facebook as a dialogic accounting tool for promoting citizen engagement in Italian regions.

This study adopts a mixed methodology. Indeed, it first collects some quantitative data to construct an engagement index for the Facebook pages of the Italian regions, and then it performs a content analysis of some posts while also examining the tenor of the related comments and the level of interaction between regions and citizens.

The Italian regions have mainly used their Facebook pages for public communication purposes rather than for public participation. Therefore, they have conceived social pages more as an instrument of self-legitimisation and thus monologic accounting and have rarely considered them as a tool for engaging citizens who, in turn, showed low interest in participating in online debates. Nature and environment, tourism promotion and sport were the most engaging content types. Findings also confirm that posting many messages does not automatically increase engagement.

This study is one of the first to investigate the potential of social media from a dialogic accounting perspective, especially in the public sector. Additionally, it focuses on regions which are understudied in the literature, although they are critical actors in implementing public policies. Last but not least, this study offers a framework that integrates the literature on the use of social media for citizen engagement and research on such platforms as dialogic accounting tools.

Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the success and diffusion of smart grids that needs to be addressed. The purpose of this study is to determine the critical criteria that affect smart grid reliability from the perspective of users and investigate the role big data plays in smart grid reliability.

This study presents a model to investigate and identify criteria that influence smart grid reliability from the perspective of users. The model consists of 12 sub-criteria covering big data management, communication system and system characteristics aspects. Multi-criteria decision-making approach is applied to analyze data and prioritize the criteria using the fuzzy analytic hierarchy process based on the triangular fuzzy numbers. Data was collected from 16 experts in the fields of smart grid and Internet of things.

The results show that the “Big Data Management” criterion has a significant impact on smart grid reliability followed by the “System Characteristics” criterion. The “Data Analytics” and the “Data Visualization” were ranked as the most influential sub-criteria on smart grid reliability. Moreover, sensitivity analysis has been applied to investigate the stability and robustness of results. The findings of this paper provide useful implications for academicians, engineers, policymakers and many other smart grid stakeholders.

The users are not expected to actively participate in smart grid and its services without understanding their perceptions on smart grid reliability. Very few works have studied smart grid reliability from the perspective of users. This study attempts to fill this considerable gap in literature by proposing a fuzzy model to prioritize smart grid reliability criteria.

This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.

The authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.

All the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.

The results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.

A storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.

Previous research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.