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The purpose of this paper is to present results from an analysis of service processes regarding their optimization potential through mobile technologies. The analysis was performed with a company of the housing industry.

The analysis was conducted with the aim of organizing business processes more efficiently in order to realize cost savings. Therefore, a method introduced in this paper was used.

It is shown how the initial situation of the company was analyzed, which alternative process models on the basis of mobile technologies were developed and how these alternatives were economically evaluated. Furthermore, first restrictions for the software and system design were identified on the basis of one process model. Finally, it is shown how the method can be used to verify whether the adoption of mobile technologies is suitable to obtain a defined goal, and which requirements such a solution needs to fulfill.

This paper shows practitioners how to conduct a systematic analysis of business processes regarding their optimization potential through mobile technologies.

Educators recognize that group work and physical involvement with learning materials can greatly enhance the understanding and retention of difficult concepts. As a result, math manipulatives ‐ such as pattern blocks and number lines ‐ have increasingly been making their way into classrooms and children’s museums. Yet without the constant guidance of a teacher, students can easily become distracted, confused, or frustrated. Math games with tangible user interfaces can address the needs of the modern learning environment by providing the guidance that a teacher would while allowing students to work together in a physical environment. This paper describes how math games with tangible user interfaces can be rapidly developed using a library of functions that were designed specifically for tracking visual tags in math games. The paper also discusses pedagogical principles and an approach to designing and developing games that utilize tangible technologies. Examples of math games that have been prototyped this way are presented. The paper concludes with a study that suggests that this approach helps children to stay focused, think about math problems in new ways, and complete the problem at hand. It also suggests that tangible math games may help children to develop problem‐solving skills that transfer to similar problems.

The introduction of artificial intelligence (AI) technology has had a substantial influence on the retail industry. However, AI adoption entails considerable responsibilities and risks for senior managers. In this study, the authors developed an evaluation and selection mechanism for successful AI technology adoption in the retail industry. The multifaceted measurement and identification of critical factors (CFs) can enable retailers to adopt AI technology effectively and maintain a sustainable competitive advantage.

The evaluation and adoption of organisational AI technology involve multifaceted decision-making for management. Therefore, the authors used the analytic network process to develop an AI evaluation framework for calculating the weight and importance of each consideration. An expert questionnaire survey was distributed to senior retail managers and 17 valid responses were obtained. Finally, the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method was used to identify CFs for AI adoption.

The results revealed five CFs for AI adoption in the retail industry. The findings indicated that after AI adoption, top retail management is most concerned with factors pertaining to business performance and minor concerned about the internal system's functional efficiency. Retailers pay more attention to technology and organisation context, which are matters under the retailers' control, than to external uncontrollable environmental factors.

The authors developed an evaluation framework and identified CFs for AI technology adoption in the retail industry. In terms of practical application, the results of this study can help AI service providers understand the CFs of retailers when adopting AI. Moreover, retailers can use the proposed multifaceted evaluation framework to guide their adoption of AI technology.

The purpose of this paper is to present an approach to incorporating mobility into continuous manufacturing following the advent of Industry 4.0 (I4.0).

The investigation is based on a year-long canonical action research into a paper-manufacturing company implementing core I4.0 technologies.

The findings show how to: classify manufacturing mobility strategy based on the dimensions of team, task and control; design business processes enabled by mobile cyber–physical resources; involve different stakeholders in modeling mobility; and create a comprehensive guide to assist in implementing the mobile digitalization required by I4.0.

Despite the complexity, richness and depth of the insights obtained in this research for mobility management in process industries, this inquiry was conducted in a single organization.

As the fourth industrial revolution encourages decentralization and increased interaction between humans and machines, this paper presents a model to capture the mobility potential in manufacturing. The tools proposed in this research can be used to steer investments in industry transformations that fuse the physical and digital worlds, overcoming mobility constraints.

Theoretically, this paper expands the concept of manufacturing mobility in I4.0. In practice, it proposes a participative roadmap to assist technology management in increasingly decentralized environments, identifying the intertwined network of cyber–physical actors, processes and services.

The nature of technologies that are recognised as Artificial Intelligence (AI) has continually changed over time to be something more advanced than other technologies. Despite the fluidity of understanding of AI, the most common theme that has stuck with AI is ‘human-like decision making’. Advancements in processing power, coupled with big data technologies, gave rise to highly accurate prediction algorithms. Analytical techniques which use multi-layered neural networks such as machine learning and deep learning have emerged as the drivers of these AI-based applications. Due to easy access and growing information workforce, these algorithms are extensively used in a plethora of industries ranging from healthcare, transportation, finance, legal systems, to even military. AI-tools have the potential to transform industries and societies through automation. Conversely, the undesirable or negative consequences of AI-tools have harmed their respective organisations in social, financial and legal spheres. As the use of these algorithms propagates in the industry, the AI-based decisions have the potential to affect large portions of the population, sometimes involving vulnerable groups in society. This chapter presents an overview of AI’s use in organisations by discussing the following: first, it discusses the core components of AI. Second, the chapter discusses common goals organisations can achieve with AI. Third, it examines different types of AI. Fourth, it discusses unintended consequences that may take place in organisations due to the use of AI. Fifth, it discusses vulnerabilities that may arise from AI systems. Lastly, this chapter offers some recommendations for industries to consider regarding the development and implementation of AI systems.

There is a need for more in‐depth exploration of the e‐learning experiences of disabled learners in higher education, taking into account the complex relationship between learners (skills, knowledge and beliefs), their assistive technologies and the e‐learning contexts in which learners are required to operate. Participatory methods appear to have great potential in enabling the voice of disabled learners to be a more central focus of e‐learning studies. This paper will describe and evaluate a two‐year research project called LExDis, which aims to use participatory methods to explore the e‐learning experiences of disabled learners in one higher education institution. The experience of conducting phase one of the LExDis project will be discussed with regards to three main challenges to using participatory methods: informed participation; valued participation; and empowered participation.

This paper presents an in-depth study of learners’ learning and playing styles and their implications for educational video games. This study aims to scrutinize the manifestation of learning and playing styles among learners, to identify the style predispositions and dominance and to assess the implication of these results for educational video games.

This paper proposes a structured model with a detailed methodology for evaluating and categorizing style predisposition and the learner’s dominant learning and playing style. The multimodal style predisposition aggregates several manifested styles at three distinguished levels to achieve more precise differentiation. The authors analyze the outcomes of an empirical field study of 676 K12 and university students, making an in-depth evaluation of their learning and playing styles.

Based on the presented model to determine the level of preferences and dominance of styles, the study reveals that multimodal style predisposition prevails for both learning and playing styles. Most learners manifest several dominant styles. While the Kinesthetic Visual, Auditory, Read/Write and Kinesthetic (VARK) learning style and Logician and Strategist playing styles prevail, the Read/Write and Competitor styles are the least preferred.

The survey explores particular learning and playing styles – VARK and adaptive technology-enhanced platform for edutainment (ADOPTA). It covers only Bulgarian students, who share common national cultural predispositions. The different sizes of the samples (234 K12 and 432 university students) are also a limitation. Further studies should involve international and equal samples of participants.

Educational video games should reflect the findings about learners’ preferences and predispositions at the planning, design and practical application level.

Game-based learning and gamification approaches in education should focus on aspects other than competition.

This paper presents an original methodology for modeling, evaluating and categorizing style predisposition and students’ dominant learning and playing styles and results about these styles of K12 and university students in the context of educational video games.

The objective of this paper is to persuade the reader of the potential benefits to be gained in applying to the study of information systems in Organisations concepts and theoretical tools developed elsewhere in the social sciences. A framework for analysis derived from a combination of feminist theory and social studies of technology (SST) is presented. The key analytical tools of the script and inscription, interpretative flexibility and actant, stabilisation and visibility are discussed. The paper attempts to demonstrate how these tools can be employed to go beyond the stereotypical images of gender and technology, by focusing on contradiction and resistance. An empirical study concerns an automated care planning system used and resisted by nurse users in a UK National Health Service hospital. The discussion is informed by a resultant table describing the outcome of the application of SST tools as well as points made concerning the issue of gender and technology.