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Previous studies have vague views about whether employees who are required to complete large amounts of work (i.e. role overload) would proactively create a change in their job characteristics (i.e. job crafting), because the cognitive mechanism underlying the nexus between role overload and job crafting is unclear. The aim of this study is to identify why and when role overload has an impact on job crafting.

This study builds a second-stage moderated mediation model. Using a two-wave panel field study of 213 employee–supervisor matched data, this study examines the proposed hypotheses.

Results show that role overload decreases construal level, which can determine the tendency of employees to focus on the feasibility (low level of construal) or desirability (high level of construal) of behaviors. Goal self-concordance is the degree to which employees pursue their personal goals based on feelings of personal interests and values. The authors find that goal self-concordance guides employees who have higher levels of construal to exert more effort in job crafting. The authors further find that goal self-concordance moderates the mediating role of construal level. Specifically, for employees in pursuit of self-concordant goals, role overload reduces their construal level, resulting in less effort in job crafting. For employees who do not pursue self-concordant goals, role overload decreases their construal level, thereby improving job crafting.

The findings of this study enrich the literature on role overload and job crafting by revealing the mechanism and boundary conditions of the relationship between role overload and job crafting.

This study aims to explore the associations linking employees’ challenge-hindrance appraisals toward artificial intelligence (AI) to service performance while considering the dual mediating roles of job crafting and job insecurity, as well as the moderating role of AI knowledge.

A survey was administered to a sample of 297 service industry employees. This study examined all the hypotheses with Mplus 8.0.

This study confirms that challenge appraisal toward AI has an indirect positive influence on service performance via job crafting (motivation process), whereas hindrance appraisal toward AI has an indirect negative influence on service performance via job insecurity (strain process). Meanwhile, AI knowledge, serving as a key personal resource, could strengthen the positive impacts of challenge appraisal toward AI on job crafting and of hindrance appraisal toward AI on job insecurity.

Organizational decision-makers should first survey employees’ appraisals toward AI and then adopt targeted managerial strategies. From the perspective of service industry employees, employees should adopt proactive coping strategies and enrich their knowledge of AI to meet the challenges brought by this technology.

The primary contribution of this study is that we enrich the literature on AI by exploring the dual mediators (i.e. job crafting and job insecurity) through which AI awareness affects service performance. Moreover, this study advances our understanding of when appraisals toward AI influence job outcomes by identifying the moderating role of AI knowledge.

This paper aims to explore the role of family members in human trafficking and how their roles impact and are perceived by their children and wards.

This paper uses data collected through a longitudinal, cross-country study. The study was conducted among 31 female, Nigerian victims of trafficking in Italy.

The authors argue that family members play important, howbeit diverse roles across space and time, in the different stages of the trafficking process, echoing a relational approach of their geographies.

This paper discusses the under-researched role of how family members may (wilfully or unknowingly) facilitate and aid the trafficking of their dependents and the consequences of their involvement on their children and wards.

The Recast Energy Efficiency Directive 2023 has defined the concept of “split incentive,” also known as “tenant-owner dilemma.” This dilemma refers to the situation where neither landlords nor tenants have incentives to invest in energy efficiency upgrades. Although the Energy Efficiency Directive calls Member States to overcome legal barriers to remove split incentives and to encourage retrofits, the list of possible measures is too vague. This paper aims to discuss tenancy law measures designed to increase the energy efficiency of residential housing and to detect which Member States have already addressed this phenomenon.

This paper analyses, from a civil legal perspective, the possible private law barriers arising from the tenant-owner dilemma when performing energy efficiency works in selected countries and proposes legal reforms in tenancy law and related policies to overcome them. To do so, this paper follows a legal-dogmatic and comparative law methodology.

This paper concludes that some tenancy law provisions, such as the possibility to increase the rent after energy efficiency renovations and long-term leases, may challenge the tenant-owner dilemma in private rented markets, thus promoting renovations and retrofitting for energy efficiency purposes. It also proposes other policies intended to increase parties’ willingness to undertake works.

More research on the economic and legal efficiency to regulate some of the civil law measures to challenge the tenant-owner dilemma should be necessary.

The civil law measures included in this paper may help national policymakers meet the energy efficiency targets, according to what is established in the Recast Energy Efficiency Directive 2023.

Based on the economic theory of the tenant-owner dilemma, this paper investigates the elements of tenancy law that may contribute to less energy-efficient homes, proposing policies for those countries interested in addressing the energy-efficiency challenge from a private law point of view.

Delay in housing adaptation is a major problem, especially in assessing if homes are suitable for the occupants and in determining if the occupants are qualified for the Disabled Facilities Grant (DFG). This paper describes the development of two self-administered intelligent integrated assessment tools from the DFG Adapt-ABLE system: (1) The Home Suitability Assessment Platform, which is a preventive mechanism that allows assessment of the suitability of homes based on occupants’ mobility status and (2) an indicative assessment platform that determines if the applicants are qualified for the DFG to prevent lengthy delays.

The adopted method aligned with a development study approach: a grounded literature review, a severity measurement approach, two stakeholder engagement workshops, four brainstorming sessions and four focus group exercises. The system development relied on Entity–Relationship Diagram (ERD) technique for data structures and database systems design. It uses DFG context sensitivity with alignment with DFG guidance, interlinkages and interoperability between the assessment tools and other platforms of the integrated Adapt-ABLE system.

The assessment tools are client-level outcomes related to accessibility, usability and activity based on the assessment process. The home suitability platform shows the percentage of the suitability of a home with assessment results that suggest appropriate action plans based on individual mobility status. The indicative assessment combines the function of referral, allocation, assessment and test of resources into an integrated platform. This enables timely assessment, decision-making and case-escalation by Occupational Therapists based on needs criteria and the eligibility threshold.

These assessment tools are useful for understanding occupants’ perception of their physical housing environment in terms of accessibility, suitability and usability based on basic activities of daily living and their mobility status. The indicative self-assessment tool will substantially cut down the application journey. The developed tools have been recommended for use in the CSJ Disability Commission report and the UK government Guidance on DFGs for local authorities in England.

This paper aims to develop predictive methods, based on recurrent neural networks, useful to support facility managers in building maintenance tasks, by collecting information coming from a computerized maintenance management system (CMMS).

This study applies data-driven and text-mining approaches to a CMMS data set comprising more than 14,500 end-users’ requests for corrective maintenance actions, collected over 14 months. Unidirectional long short-term memory (LSTM) and bidirectional LSTM (Bi-LSTM) recurrent neural networks are trained to predict the priority of each maintenance request and the related technical staff assignment. The data set is also used to depict an overview of corrective maintenance needs and related performances and to verify the most relevant elements in the building and how the current facility management (FM) relates to the requests.

The study shows that LSTM and Bi-LSTM recurrent neural networks can properly recognize the words contained in the requests, thus correctly and automatically assigning the priority and predicting the technical staff to assign for each end-user’s maintenance request. The obtained global accuracy is very high, reaching 93.3% for priority identification and 96.7% for technical staff assignment. Results also show the main critical building elements for maintenance requests and the related intervention timings.

This work shows that LSTM and Bi-LSTM recurrent neural networks can automate the assignment process of end-users’ maintenance requests if trained with historical CMMS data. Results are promising; however, the trained LSTM and Bi-LSTM RNN can be applied only to different hospitals adopting similar categorization.

The data-driven and text-mining approaches can be integrated into the CMMS to support corrective maintenance management by facilities management contractors, i.e. to properly and timely identify the actions to be carried out and the technical staff to assign.

The improvement of the maintenance of the health-care system is a key component of improving health service delivery. This work shows how to reduce health-care service interruptions due to maintenance needs through machine learning methods.

This study develops original methods and tools easily integrable into IT workflow systems (i.e. CMMS) in the FM field.

This research investigates the distinct characteristics of blockchain technology to safeguard against the deterioration of handover information quality in the post-construction phase. The significance of effective management of handover information is highlighted by global building failures, such as the Grenfell Tower fire in London, UK. Despite existing technological interventions, there remains a paucity of understanding regarding the factors contributing to the decline in the quality of handover information during the post-construction phase.

This study employed a multi-case studies approach across five higher education institutions. It involved conducting semi-structured interviews with 52 asset management professionals, uncovering the underlying reasons for the decline in handover information quality. Building on these insights, the study performed a mapping exercise to align these identified factors with blockchain technology features and information quality dimensions, aiming to evaluate blockchain’s potential in managing quality handover information.

The study findings suggest that blockchain technology offers advantages but has limitations in addressing all the identified quality issues of managing handover information. Due to the lack of an automated process and file-based information exchange, updating handover information still requires an error-prone manual process, leading to potential information loss. Additionally, no solutions are available for encoding drawings for updates and validation.

This study proposes a framework integrating blockchain to enhance the information management process and improve handover information quality.

This study aims to improve the use of digitalization in facilities management (FM) for shopping complex facilities in the post-COVID-19 era. The resumption of economic activities, especially in shopping complexes, poses challenges for FM with throngs of shoppers. To tackle these challenges, enhanced and innovative FM practices are necessary.

The study used a qualitative research approach, incorporating case studies, interviews, observations and documentation. It focused on super-regional shopping complexes in the Klang Valley, Malaysia, selecting two complexes for qualitative data collection. Supplementary data were gathered from various sources, including government policy publications, websites, books, journal papers and archival records.

The research provides valuable insights into FM innovations and the application of FM digitalization in shopping complexes after the COVID-19 pandemic. It also addresses challenges faced by FM teams during this period. Recommendations for implementing FM digitalization in super-regional shopping complexes post-COVID-19 include developing skilled personnel, defining appropriate work scopes, strategies and policies, using cost-effective software, and increasing occupant awareness. The involvement of outsourced service providers is advised, emphasizing their understanding of the organization’s business model and innovative approaches.

The findings offer new perspectives on the characteristics of FM digitalization in the commercial sector during business disruptions caused by the pandemic. The proposed strategies are grounded in real industry implementations, aiming to enhance the FM digitalization approach for improved business performance.

The purpose of this paper is to understand how digital interventions are mediating the identity work of community health workers (CHWs) in the context of two African countries.

This paper analyzes the everyday work of CHWs in two low- and middle-income country (LMIC) contexts (Uganda and Malawi) and seeks to understand changes in collective identity and the role of Information and Communication Technologies (ICTs) in mediating this “identity work”. As CHWs conduct their everyday tasks of care giving, data reporting and maintaining social interactions, they play two primary roles. One is the care giving role oriented towards the community, and two, is reporting and administrative work by virtue of them being affiliated with the Ministry of Health, either in formal or voluntary capacity. The ambivalence which they experience as they move back and forth between these two worlds of work is significantly now mediated through ICTs. The paper analyzes these dynamics and identifies three key sets of ambivalence in identity work: (1) role embracing-institutional distancing; (2) conformist-resistant and (3) dramaturgical-transformative. The paper makes unique contributions to information systems (IS) and ICT for development (ICT4D) studies in that it focuses on a nonprofessional group, which plays a fundamental role in providing care to underserved populations and also conducts data work which provides the foundation of the national health information system. This contrasts with dominant research in the field which focuses on professional groups, largely based in Western business organizations.

The paper identifies identity related tensions that emerge with the mediation of digital technologies in the work world of CHWs. These include tensions of conformist-resistant; and (3) dramaturgical-transformative. These findings are relevant and unique to the field of IS and ICT4D studies in that it focuses on a nonprofessional group, which plays a fundamental role in providing care to underserved populations and also conducts data work which provides the foundation of the national health information system.

While acknowledging identity construction and negotiation is a function of both work and social lives, in this paper we could only focus on the work lives.

As digital interventions in the health sector of low and middle income countries is becoming increasingly widespread, often the focus is more on the supply side (the supply of the technology) rather than on the demand side (users experiences and aspirations). Identity becomes a lens to understand these demand side dynamics, which helps provides practical guidance on implementation approaches to ensure that the technology adds value to user work processes and there is a seamless and not a disruptive transition.

CHWs are the most neglected cadre in the health system of low and middle income countries, even though they provide the cutting edge in care provision work to the most marginalized populations, living in rural and underserved areas. By focusing on how technologies can be more effectively implemented to support these care processes, the paper provides important social implications both for practice and research.

Analysis of identity construction and negotiation of informal groups in the unorganized sector of low and middle income countries has not received adequate attention in IS research. The paper seeks to fill this important gap.